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# Loss functions
import torch
import torch.nn as nn
import numpy as np
from utils.general import bbox_iou
from utils.torch_utils import is_parallel
def smooth_BCE(eps=0.1): # https://github.com/ultralytics/yolov3/issues/238#issuecomment-598028441
# return positive, negative label smoothing BCE targets
return 1.0 - 0.5 * eps, 0.5 * eps
class BCEBlurWithLogitsLoss(nn.Module):
# BCEwithLogitLoss() with reduced missing label effects.
def __init__(self, alpha=0.05):
super(BCEBlurWithLogitsLoss, self).__init__()
self.loss_fcn = nn.BCEWithLogitsLoss(reduction='none') # must be nn.BCEWithLogitsLoss()
self.alpha = alpha
def forward(self, pred, true):
loss = self.loss_fcn(pred, true)
pred = torch.sigmoid(pred) # prob from logits
dx = pred - true # reduce only missing label effects
# dx = (pred - true).abs() # reduce missing label and false label effects
alpha_factor = 1 - torch.exp((dx - 1) / (self.alpha + 1e-4))
loss *= alpha_factor
return loss.mean()
class FocalLoss(nn.Module):
# Wraps focal loss around existing loss_fcn(), i.e. criteria = FocalLoss(nn.BCEWithLogitsLoss(), gamma=1.5)
def __init__(self, loss_fcn, gamma=1.5, alpha=0.25):
super(FocalLoss, self).__init__()
self.loss_fcn = loss_fcn # must be nn.BCEWithLogitsLoss()
self.gamma = gamma
self.alpha = alpha
self.reduction = loss_fcn.reduction
self.loss_fcn.reduction = 'none' # required to apply FL to each element
def forward(self, pred, true):
loss = self.loss_fcn(pred, true)
# p_t = torch.exp(-loss)
# loss *= self.alpha * (1.000001 - p_t) ** self.gamma # non-zero power for gradient stability
# TF implementation https://github.com/tensorflow/addons/blob/v0.7.1/tensorflow_addons/losses/focal_loss.py
pred_prob = torch.sigmoid(pred) # prob from logits
p_t = true * pred_prob + (1 - true) * (1 - pred_prob)
alpha_factor = true * self.alpha + (1 - true) * (1 - self.alpha)
modulating_factor = (1.0 - p_t) ** self.gamma
loss *= alpha_factor * modulating_factor
if self.reduction == 'mean':
return loss.mean()
elif self.reduction == 'sum':
return loss.sum()
else: # 'none'
return loss
class QFocalLoss(nn.Module):
# Wraps Quality focal loss around existing loss_fcn(), i.e. criteria = FocalLoss(nn.BCEWithLogitsLoss(), gamma=1.5)
def __init__(self, loss_fcn, gamma=1.5, alpha=0.25):
super(QFocalLoss, self).__init__()
self.loss_fcn = loss_fcn # must be nn.BCEWithLogitsLoss()
self.gamma = gamma
self.alpha = alpha
self.reduction = loss_fcn.reduction
self.loss_fcn.reduction = 'none' # required to apply FL to each element
def forward(self, pred, true):
loss = self.loss_fcn(pred, true)
pred_prob = torch.sigmoid(pred) # prob from logits
alpha_factor = true * self.alpha + (1 - true) * (1 - self.alpha)
modulating_factor = torch.abs(true - pred_prob) ** self.gamma
loss *= alpha_factor * modulating_factor
if self.reduction == 'mean':
return loss.mean()
elif self.reduction == 'sum':
return loss.sum()
else: # 'none'
return loss
class WingLoss(nn.Module):
def __init__(self, w=10, e=2):
super(WingLoss, self).__init__()
# https://arxiv.org/pdf/1711.06753v4.pdf Figure 5
self.w = w
self.e = e
self.C = self.w - self.w * np.log(1 + self.w / self.e)
def forward(self, x, t, sigma=1):
weight = torch.ones_like(t)
weight[torch.where(t==-1)] = 0
diff = weight * (x - t)
abs_diff = diff.abs()
flag = (abs_diff.data < self.w).float()
y = flag * self.w * torch.log(1 + abs_diff / self.e) + (1 - flag) * (abs_diff - self.C)
return y.sum()
class KPTLoss(nn.Module):
# BCEwithLogitLoss() with reduced missing label effects.
def __init__(self, alpha=1.0):
super(KPTLoss, self).__init__()
self.loss_fcn = WingLoss()#nn.SmoothL1Loss(reduction='sum')
self.alpha = alpha
def forward(self, pred, truel, mask):
loss = self.loss_fcn(pred*mask, truel*mask)
return loss / (torch.sum(mask) + 10e-14)
class ComputeLoss:
# Compute losses
def __init__(self, model, autobalance=False, kpt_label=False):
super(ComputeLoss, self).__init__()
self.kpt_label = kpt_label
device = next(model.parameters()).device # get model device
h = model.hyp # hyperparameters
# Define criteria
BCEcls = nn.BCEWithLogitsLoss(pos_weight=torch.tensor([h['cls_pw']], device=device))
BCEobj = nn.BCEWithLogitsLoss(pos_weight=torch.tensor([h['obj_pw']], device=device))
BCE_kptv = nn.BCEWithLogitsLoss(pos_weight=torch.tensor([h['obj_pw']], device=device))
self.kptloss = KPTLoss()
# Class label smoothing https://arxiv.org/pdf/1902.04103.pdf eqn 3
self.cp, self.cn = smooth_BCE(eps=h.get('label_smoothing', 0.0)) # positive, negative BCE targets
# Focal loss
g = h['fl_gamma'] # focal loss gamma
if g > 0:
BCEcls, BCEobj = FocalLoss(BCEcls, g), FocalLoss(BCEobj, g)
det = model.module.model[-1] if is_parallel(model) else model.model[-1] # Detect() module
self.balance = {3: [4.0, 1.0, 0.4]}.get(det.nl, [4.0, 1.0, 0.25, 0.06, .02]) # P3-P7
self.ssi = list(det.stride).index(16) if autobalance else 0 # stride 16 index
self.BCEcls, self.BCEobj, self.gr, self.hyp, self.autobalance = BCEcls, BCEobj, model.gr, h, autobalance
for k in 'na', 'nc', 'nl', 'anchors', 'nkpt':
setattr(self, k, getattr(det, k))
def __call__(self, p, targets): # predictions, targets, model
device = targets.device
lcls, lbox, lobj, lkpt, lkptv = torch.zeros(1, device=device), torch.zeros(1, device=device), torch.zeros(1, device=device), torch.zeros(1, device=device), torch.zeros(1, device=device)
tcls, tbox, tkpt, indices, anchors = self.build_targets(p, targets) # targets
# Losses
for i, pi in enumerate(p): # layer index, layer predictions
b, a, gj, gi = indices[i] # image, anchor, gridy, gridx
tobj = torch.zeros_like(pi[..., 0], device=device) # target obj
n = b.shape[0] # number of targets
if n:
ps = pi[b, a, gj, gi] # prediction subset corresponding to targets
# Regression
pxy = ps[:, :2].sigmoid() * 2. - 0.5
pwh = (ps[:, 2:4].sigmoid() * 2) ** 2 * anchors[i]
pbox = torch.cat((pxy, pwh), 1) # predicted box
iou = bbox_iou(pbox.T, tbox[i], x1y1x2y2=False, CIoU=True) # iou(prediction, target)
lbox += (1.0 - iou).mean() # iou loss
if self.kpt_label:
#Direct kpt prediction
pkpt_x = ps[:, 5+self.nc::3] * 2. - 0.5
pkpt_y = ps[:, 6+self.nc::3] * 2. - 0.5
pkpt_score = ps[:, 7+self.nc::3]
#mask
kpt_mask = (tkpt[i][:, 0::2] != 0)
lkptv += self.BCEcls(pkpt_score, kpt_mask.float())
#l2 distance based loss
lkpt += (self.kptloss(tkpt[i][:,0::2], pkpt_x, kpt_mask) + self.kptloss(tkpt[i][:,1::2], pkpt_y, kpt_mask)) / 2
#lkpt += (((pkpt-tkpt[i])*kpt_mask)**2).mean() #Try to make this loss based on distance instead of ordinary difference
#oks based loss
#d = (pkpt_x-tkpt[i][:,0::2])**2 + (pkpt_y-tkpt[i][:,1::2])**2
#s = torch.prod(tbox[i][:,-2:], dim=1, keepdim=True)
#kpt_loss_factor = (torch.sum(kpt_mask != 0) + torch.sum(kpt_mask == 0))/torch.sum(kpt_mask != 0)
#lkpt += kpt_loss_factor*((1 - torch.exp(-d/(s*(4*sigmas**2)+1e-9)))*kpt_mask).mean()
# Objectness
tobj[b, a, gj, gi] = (1.0 - self.gr) + self.gr * iou.detach().clamp(0).type(tobj.dtype) # iou ratio
# Classification
if self.nc > 1: # cls loss (only if multiple classes)
t = torch.full_like(ps[:, 5:5+self.nc], self.cn, device=device) # targets
t[range(n), tcls[i]] = self.cp
lcls += self.BCEcls(ps[:, 5:5+self.nc], t) # BCE
# Append targets to text file
# with open('targets.txt', 'a') as file:
# [file.write('%11.5g ' * 4 % tuple(x) + '\n') for x in torch.cat((txy[i], twh[i]), 1)]
obji = self.BCEobj(pi[..., 4], tobj)
lobj += obji * self.balance[i] # obj loss
if self.autobalance:
self.balance[i] = self.balance[i] * 0.9999 + 0.0001 / obji.detach().item()
if self.autobalance:
self.balance = [x / self.balance[self.ssi] for x in self.balance]
lbox *= self.hyp['box']
lobj *= self.hyp['obj']
lcls *= self.hyp['cls']
lkptv *= self.hyp['cls']
lkpt *= self.hyp['kpt']
bs = tobj.shape[0] # batch size
loss = lbox + lobj + lcls + lkpt + lkptv
return loss * bs, torch.cat((lbox, lobj, lcls, lkpt, lkptv, loss)).detach()
def build_targets(self, p, targets):
# Build targets for compute_loss(), input targets(image,class,x,y,w,h)
na, nt = self.na, targets.shape[0] # number of anchors, targets
tcls, tbox, tkpt, indices, anch = [], [], [], [], []
if self.kpt_label:
gain = torch.ones(self.kpt_label*2+7, device=targets.device).long() # normalized to gridspace gain
else:
gain = torch.ones(7, device=targets.device).long() # normalized to gridspace gain
ai = torch.arange(na, device=targets.device).float().view(na, 1).repeat(1, nt) # same as .repeat_interleave(nt)
targets = torch.cat((targets.repeat(na, 1, 1), ai[:, :, None]), 2) # append anchor indices
g = 0.5 # bias
off = torch.tensor([[0, 0],
[1, 0], [0, 1], [-1, 0], [0, -1], # j,k,l,m
# [1, 1], [1, -1], [-1, 1], [-1, -1], # jk,jm,lk,lm
], device=targets.device).float() * g # offsets
for i in range(self.nl):
anchors = self.anchors[i]
if self.kpt_label:
gain[2:self.kpt_label*2+6] = torch.tensor(p[i].shape)[(self.kpt_label+2)*[3, 2]] # xyxy gain
else:
gain[2:6] = torch.tensor(p[i].shape)[[3, 2, 3, 2]] # xyxy gain
# Match targets to anchors
t = targets * gain
if nt:
# Matches
r = t[:, :, 4:6] / anchors[:, None] # wh ratio
j = torch.max(r, 1. / r).max(2)[0] < self.hyp['anchor_t'] # compare
# j = wh_iou(anchors, t[:, 4:6]) > model.hyp['iou_t'] # iou(3,n)=wh_iou(anchors(3,2), gwh(n,2))
t = t[j] # filter
# Offsets
gxy = t[:, 2:4] # grid xy
gxi = gain[[2, 3]] - gxy # inverse
j, k = ((gxy % 1. < g) & (gxy > 1.)).T
l, m = ((gxi % 1. < g) & (gxi > 1.)).T
j = torch.stack((torch.ones_like(j), j, k, l, m))
t = t.repeat((5, 1, 1))[j]
offsets = (torch.zeros_like(gxy)[None] + off[:, None])[j]
else:
t = targets[0]
offsets = 0
# Define
b, c = t[:, :2].long().T # image, class
gxy = t[:, 2:4] # grid xy
gwh = t[:, 4:6] # grid wh
gij = (gxy - offsets).long()
gi, gj = gij.T # grid xy indices
# Append
a = t[:, -1].long() # anchor indices
indices.append((b, a, gj.clamp_(0, gain[3] - 1), gi.clamp_(0, gain[2] - 1))) # image, anchor, grid indices
tbox.append(torch.cat((gxy - gij, gwh), 1)) # box
if self.kpt_label:
for kpt in range(self.nkpt):
t[:, 6+2*kpt: 6+2*(kpt+1)][t[:,6+2*kpt: 6+2*(kpt+1)] !=0] -= gij[t[:,6+2*kpt: 6+2*(kpt+1)] !=0]
tkpt.append(t[:, 6:-1])
anch.append(anchors[a]) # anchors
tcls.append(c) # class
return tcls, tbox, tkpt, indices, anch
|
2301_81045437/yolov7_plate
|
utils/loss.py
|
Python
|
unknown
| 12,603
|
# Model validation metrics
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import torch
from . import general
def fitness(x):
# Model fitness as a weighted combination of metrics
w = [0.0, 0.0, 0.1, 0.9] # weights for [P, R, mAP@0.5, mAP@0.5:0.95]
return (x[:, :4] * w).sum(1)
def ap_per_class(tp, conf, pred_cls, target_cls, plot=False, save_dir='.', names=()):
""" Compute the average precision, given the recall and precision curves.
Source: https://github.com/rafaelpadilla/Object-Detection-Metrics.
# Arguments
tp: True positives (nparray, nx1 or nx10).
conf: Objectness value from 0-1 (nparray).
pred_cls: Predicted object classes (nparray).
target_cls: True object classes (nparray).
plot: Plot precision-recall curve at mAP@0.5
save_dir: Plot save directory
# Returns
The average precision as computed in py-faster-rcnn.
"""
# Sort by objectness
i = np.argsort(-conf)
tp, conf, pred_cls = tp[i], conf[i], pred_cls[i]
# Find unique classes
unique_classes = np.unique(target_cls)
nc = unique_classes.shape[0] # number of classes, number of detections
# Create Precision-Recall curve and compute AP for each class
px, py = np.linspace(0, 1, 1000), [] # for plotting
ap, p, r = np.zeros((nc, tp.shape[1])), np.zeros((nc, 1000)), np.zeros((nc, 1000))
for ci, c in enumerate(unique_classes):
i = pred_cls == c
n_l = (target_cls == c).sum() # number of labels
n_p = i.sum() # number of predictions
if n_p == 0 or n_l == 0:
continue
else:
# Accumulate FPs and TPs
fpc = (1 - tp[i]).cumsum(0)
tpc = tp[i].cumsum(0)
# Recall
recall = tpc / (n_l + 1e-16) # recall curve
r[ci] = np.interp(-px, -conf[i], recall[:, 0], left=0) # negative x, xp because xp decreases
# Precision
precision = tpc / (tpc + fpc) # precision curve
p[ci] = np.interp(-px, -conf[i], precision[:, 0], left=1) # p at pr_score
# AP from recall-precision curve
for j in range(tp.shape[1]):
ap[ci, j], mpre, mrec = compute_ap(recall[:, j], precision[:, j])
if plot and j == 0:
py.append(np.interp(px, mrec, mpre)) # precision at mAP@0.5
# Compute F1 (harmonic mean of precision and recall)
f1 = 2 * p * r / (p + r + 1e-16)
if plot:
plot_pr_curve(px, py, ap, Path(save_dir) / 'PR_curve.png', names)
plot_mc_curve(px, f1, Path(save_dir) / 'F1_curve.png', names, ylabel='F1')
plot_mc_curve(px, p, Path(save_dir) / 'P_curve.png', names, ylabel='Precision')
plot_mc_curve(px, r, Path(save_dir) / 'R_curve.png', names, ylabel='Recall')
i = f1.mean(0).argmax() # max F1 index
return p[:, i], r[:, i], ap, f1[:, i], unique_classes.astype('int32')
def compute_ap(recall, precision):
""" Compute the average precision, given the recall and precision curves
# Arguments
recall: The recall curve (list)
precision: The precision curve (list)
# Returns
Average precision, precision curve, recall curve
"""
# Append sentinel values to beginning and end
mrec = np.concatenate(([0.], recall, [recall[-1] + 0.01]))
mpre = np.concatenate(([1.], precision, [0.]))
# Compute the precision envelope
mpre = np.flip(np.maximum.accumulate(np.flip(mpre)))
# Integrate area under curve
method = 'interp' # methods: 'continuous', 'interp'
if method == 'interp':
x = np.linspace(0, 1, 101) # 101-point interp (COCO)
ap = np.trapz(np.interp(x, mrec, mpre), x) # integrate
else: # 'continuous'
i = np.where(mrec[1:] != mrec[:-1])[0] # points where x axis (recall) changes
ap = np.sum((mrec[i + 1] - mrec[i]) * mpre[i + 1]) # area under curve
return ap, mpre, mrec
class ConfusionMatrix:
# Updated version of https://github.com/kaanakan/object_detection_confusion_matrix
def __init__(self, nc, conf=0.25, iou_thres=0.45):
self.matrix = np.zeros((nc + 1, nc + 1))
self.nc = nc # number of classes
self.conf = conf
self.iou_thres = iou_thres
def process_batch(self, detections, labels):
"""
Return intersection-over-union (Jaccard index) of boxes.
Both sets of boxes are expected to be in (x1, y1, x2, y2) format.
Arguments:
detections (Array[N, 6]), x1, y1, x2, y2, conf, class
labels (Array[M, 5]), class, x1, y1, x2, y2
Returns:
None, updates confusion matrix accordingly
"""
detections = detections[detections[:, 4] > self.conf]
gt_classes = labels[:, 0].int()
detection_classes = detections[:, 5].int()
iou = general.box_iou(labels[:, 1:], detections[:, :4])
x = torch.where(iou > self.iou_thres)
if x[0].shape[0]:
matches = torch.cat((torch.stack(x, 1), iou[x[0], x[1]][:, None]), 1).cpu().numpy()
if x[0].shape[0] > 1:
matches = matches[matches[:, 2].argsort()[::-1]]
matches = matches[np.unique(matches[:, 1], return_index=True)[1]]
matches = matches[matches[:, 2].argsort()[::-1]]
matches = matches[np.unique(matches[:, 0], return_index=True)[1]]
else:
matches = np.zeros((0, 3))
n = matches.shape[0] > 0
m0, m1, _ = matches.transpose().astype(np.int16)
for i, gc in enumerate(gt_classes):
j = m0 == i
if n and sum(j) == 1:
self.matrix[detection_classes[m1[j]], gc] += 1 # correct
else:
self.matrix[self.nc, gc] += 1 # background FP
if n:
for i, dc in enumerate(detection_classes):
if not any(m1 == i):
self.matrix[dc, self.nc] += 1 # background FN
def matrix(self):
return self.matrix
def plot(self, save_dir='', names=()):
try:
import seaborn as sn
array = self.matrix / (self.matrix.sum(0).reshape(1, self.nc + 1) + 1E-6) # normalize
array[array < 0.005] = np.nan # don't annotate (would appear as 0.00)
fig = plt.figure(figsize=(12, 9), tight_layout=True)
sn.set(font_scale=1.0 if self.nc < 50 else 0.8) # for label size
labels = (0 < len(names) < 99) and len(names) == self.nc # apply names to ticklabels
sn.heatmap(array, annot=self.nc < 30, annot_kws={"size": 8}, cmap='Blues', fmt='.2f', square=True,
xticklabels=names + ['background FP'] if labels else "auto",
yticklabels=names + ['background FN'] if labels else "auto").set_facecolor((1, 1, 1))
fig.axes[0].set_xlabel('True')
fig.axes[0].set_ylabel('Predicted')
fig.savefig(Path(save_dir) / 'confusion_matrix.png', dpi=250)
except Exception as e:
pass
def print(self):
for i in range(self.nc + 1):
print(' '.join(map(str, self.matrix[i])))
# Plots ----------------------------------------------------------------------------------------------------------------
def plot_pr_curve(px, py, ap, save_dir='pr_curve.png', names=()):
# Precision-recall curve
fig, ax = plt.subplots(1, 1, figsize=(9, 6), tight_layout=True)
py = np.stack(py, axis=1)
if 0 < len(names) < 21: # display per-class legend if < 21 classes
for i, y in enumerate(py.T):
ax.plot(px, y, linewidth=1, label=f'{names[i]} {ap[i, 0]:.3f}') # plot(recall, precision)
else:
ax.plot(px, py, linewidth=1, color='grey') # plot(recall, precision)
ax.plot(px, py.mean(1), linewidth=3, color='blue', label='all classes %.3f mAP@0.5' % ap[:, 0].mean())
ax.set_xlabel('Recall')
ax.set_ylabel('Precision')
ax.set_xlim(0, 1)
ax.set_ylim(0, 1)
plt.legend(bbox_to_anchor=(1.04, 1), loc="upper left")
fig.savefig(Path(save_dir), dpi=250)
def plot_mc_curve(px, py, save_dir='mc_curve.png', names=(), xlabel='Confidence', ylabel='Metric'):
# Metric-confidence curve
fig, ax = plt.subplots(1, 1, figsize=(9, 6), tight_layout=True)
if 0 < len(names) < 21: # display per-class legend if < 21 classes
for i, y in enumerate(py):
ax.plot(px, y, linewidth=1, label=f'{names[i]}') # plot(confidence, metric)
else:
ax.plot(px, py.T, linewidth=1, color='grey') # plot(confidence, metric)
y = py.mean(0)
ax.plot(px, y, linewidth=3, color='blue', label=f'all classes {y.max():.2f} at {px[y.argmax()]:.3f}')
ax.set_xlabel(xlabel)
ax.set_ylabel(ylabel)
ax.set_xlim(0, 1)
ax.set_ylim(0, 1)
plt.legend(bbox_to_anchor=(1.04, 1), loc="upper left")
fig.savefig(Path(save_dir), dpi=250)
|
2301_81045437/yolov7_plate
|
utils/metrics.py
|
Python
|
unknown
| 8,969
|
# Plotting utils
import glob
import math
import os
import random
from copy import copy
from pathlib import Path
import cv2
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import torch
import yaml
from PIL import Image, ImageDraw, ImageFont
from utils.general import xywh2xyxy, xyxy2xywh
from utils.metrics import fitness
# Settings
matplotlib.rc('font', **{'size': 11})
matplotlib.use('Agg') # for writing to files only
class Colors:
# Ultralytics color palette https://ultralytics.com/
def __init__(self):
self.palette = [self.hex2rgb(c) for c in matplotlib.colors.TABLEAU_COLORS.values()]
self.n = len(self.palette)
def __call__(self, i, bgr=False):
c = self.palette[int(i) % self.n]
return (c[2], c[1], c[0]) if bgr else c
@staticmethod
def hex2rgb(h): # rgb order (PIL)
return tuple(int(h[1 + i:1 + i + 2], 16) for i in (0, 2, 4))
colors = Colors() # create instance for 'from utils.plots import colors'
def hist2d(x, y, n=100):
# 2d histogram used in labels.png and evolve.png
xedges, yedges = np.linspace(x.min(), x.max(), n), np.linspace(y.min(), y.max(), n)
hist, xedges, yedges = np.histogram2d(x, y, (xedges, yedges))
xidx = np.clip(np.digitize(x, xedges) - 1, 0, hist.shape[0] - 1)
yidx = np.clip(np.digitize(y, yedges) - 1, 0, hist.shape[1] - 1)
return np.log(hist[xidx, yidx])
def butter_lowpass_filtfilt(data, cutoff=1500, fs=50000, order=5):
from scipy.signal import butter, filtfilt
# https://stackoverflow.com/questions/28536191/how-to-filter-smooth-with-scipy-numpy
def butter_lowpass(cutoff, fs, order):
nyq = 0.5 * fs
normal_cutoff = cutoff / nyq
return butter(order, normal_cutoff, btype='low', analog=False)
b, a = butter_lowpass(cutoff, fs, order=order)
return filtfilt(b, a, data) # forward-backward filter
def plot_one_box(x, im, color=None, label=None, line_thickness=3, kpt_label=False, kpts=None, steps=2, orig_shape=None):
# Plots one bounding box on image 'im' using OpenCV
assert im.data.contiguous, 'Image not contiguous. Apply np.ascontiguousarray(im) to plot_on_box() input image.'
tl = line_thickness or round(0.002 * (im.shape[0] + im.shape[1]) / 2) + 1 # line/font thickness
color = color or [random.randint(0, 255) for _ in range(3)]
c1, c2 = (int(x[0]), int(x[1])), (int(x[2]), int(x[3]))
cv2.rectangle(im, c1, c2, (255,0,0), thickness=tl*1//3, lineType=cv2.LINE_AA)
if label:
if len(label.split(' ')) > 1:
label = label.split(' ')[-1]
tf = max(tl - 1, 1) # font thickness
t_size = cv2.getTextSize(label, 0, fontScale=tl / 6, thickness=tf)[0]
c2 = c1[0] + t_size[0], c1[1] - t_size[1] - 3
cv2.rectangle(im, c1, c2, color, -1, cv2.LINE_AA) # filled
cv2.putText(im, label, (c1[0], c1[1] - 2), 0, tl / 6, [225, 255, 255], thickness=tf//2, lineType=cv2.LINE_AA)
if kpt_label:
plot_skeleton_kpts(im, kpts, steps, orig_shape=orig_shape)
def plot_skeleton_kpts(im, kpts, steps, orig_shape=None):
#Plot the skeleton and keypointsfor coco datatset
palette = np.array([[255, 128, 0], [255, 153, 51], [255, 178, 102],
[230, 230, 0], [255, 153, 255], [153, 204, 255],
[255, 102, 255], [255, 51, 255], [102, 178, 255],
[51, 153, 255], [255, 153, 153], [255, 102, 102],
[255, 51, 51], [153, 255, 153], [102, 255, 102],
[51, 255, 51], [0, 255, 0], [0, 0, 255], [255, 0, 0],
[255, 255, 255]])
radius = 2
num_kpts = len(kpts) // steps
for kid in range(num_kpts):
r, g, b = palette[kid]
x_coord, y_coord = kpts[steps * kid], kpts[steps * kid + 1]
if not (x_coord % 640 == 0 or y_coord % 640 == 0):
if steps == 3:
conf = kpts[steps * kid + 2]
if conf < 0.5:
continue
cv2.circle(im, (int(x_coord), int(y_coord)), radius, (int(r), int(g), int(b)), -1)
def plot_one_box_PIL(box, im, color=None, label=None, line_thickness=None):
# Plots one bounding box on image 'im' using PIL
im = Image.fromarray(im)
draw = ImageDraw.Draw(im)
line_thickness = line_thickness or max(int(min(im.size) / 200), 2)
draw.rectangle(box, width=line_thickness, outline=tuple(color)) # plot
if label:
fontsize = max(round(max(im.size) / 40), 12)
font = ImageFont.truetype("Arial.ttf", fontsize)
txt_width, txt_height = font.getsize(label)
#draw.rectangle([box[0], box[1] - txt_height + 4, box[0] + txt_width, box[1]], fill=tuple(color))
draw.text((box[0], box[1] - txt_height + 1), label, fill=(255, 255, 255), font=font)
return np.asarray(im)
def plot_wh_methods(): # from utils.plots import *; plot_wh_methods()
# Compares the two methods for width-height anchor multiplication
# https://github.com/ultralytics/yolov3/issues/168
x = np.arange(-4.0, 4.0, .1)
ya = np.exp(x)
yb = torch.sigmoid(torch.from_numpy(x)).numpy() * 2
fig = plt.figure(figsize=(6, 3), tight_layout=True)
plt.plot(x, ya, '.-', label='YOLOv3')
plt.plot(x, yb ** 2, '.-', label='YOLOv5 ^2')
plt.plot(x, yb ** 1.6, '.-', label='YOLOv5 ^1.6')
plt.xlim(left=-4, right=4)
plt.ylim(bottom=0, top=6)
plt.xlabel('input')
plt.ylabel('output')
plt.grid()
plt.legend()
fig.savefig('comparison.png', dpi=200)
def output_to_target(output):
# Convert model output to target format [batch_id, class_id, x, y, w, h, conf]
targets = []
for i, o in enumerate(output):
kpts = o[:,6:]
o = o[:,:6]
for index, (*box, conf, cls) in enumerate(o.cpu().numpy()):
targets.append([i, cls, *list(*xyxy2xywh(np.array(box)[None])), conf, *list(kpts.cpu().numpy()[index])])
return np.array(targets)
def plot_images(images, targets, paths=None, fname='images.jpg', names=None, max_size=640, max_subplots=16, kpt_label=True, steps=2, orig_shape=None):
# Plot image grid with labels
if isinstance(images, torch.Tensor):
images = images.cpu().float().numpy()
if isinstance(targets, torch.Tensor):
targets = targets.cpu().numpy()
# un-normalise
if np.max(images[0]) <= 1:
images *= 255
tl = 3 # line thickness
tf = max(tl - 1, 1) # font thickness
bs, _, h, w = images.shape # batch size, _, height, width
bs = min(bs, max_subplots) # limit plot images
ns = np.ceil(bs ** 0.5) # number of subplots (square)
# Check if we should resize
scale_factor = max_size / max(h, w)
if scale_factor < 1:
h = math.ceil(scale_factor * h)
w = math.ceil(scale_factor * w)
mosaic = np.full((int(ns * h), int(ns * w), 3), 255, dtype=np.uint8) # init
for i, img in enumerate(images):
if i == max_subplots: # if last batch has fewer images than we expect
break
block_x = int(w * (i // ns))
block_y = int(h * (i % ns))
img = img.transpose(1, 2, 0)
if scale_factor < 1:
img = cv2.resize(img, (w, h))
mosaic[block_y:block_y + h, block_x:block_x + w, :] = img
if len(targets) > 0:
image_targets = targets[targets[:, 0] == i]
boxes = xywh2xyxy(image_targets[:, 2:6]).T
classes = image_targets[:, 1].astype('int')
labels = image_targets.shape[1] == kpt_label*2+6 if kpt_label else image_targets.shape[1] == 6 # labels if no conf column
conf = None if labels else image_targets[:, 6] # check for confidence presence (label vs pred)
if kpt_label:
if conf is None:
kpts = image_targets[:, 6:].T #kpts for GT
else:
kpts = image_targets[:, 7:].T #kpts for prediction
else:
kpts = None
if boxes.shape[1]:
if boxes.max() <= 1.01: # if normalized with tolerance 0.01
boxes[[0, 2]] *= w # scale to pixels
boxes[[1, 3]] *= h
elif scale_factor < 1: # absolute coords need scale if image scales
boxes *= scale_factor
boxes[[0, 2]] += block_x
boxes[[1, 3]] += block_y
if kpt_label and kpts.shape[1]:
if kpts.max()<1.01:
kpts[list(range(0,len(kpts),steps))] *=w # scale to pixels
kpts[list(range(1,len(kpts),steps))] *= h
elif scale_factor < 1 :
kpts[list(range(0, len(kpts), steps))] *= scale_factor
kpts[list(range(1, len(kpts), steps))] *= scale_factor
kpts[list(range(0, len(kpts), steps))] += block_x
kpts[list(range(1, len(kpts), steps))] += block_y
for j, box in enumerate(boxes.T):
cls = int(classes[j])
color = colors(cls)
cls = names[cls] if names else cls
if labels or conf[j] > 0.1: # 0.25 conf thresh
label = '%s' % cls if labels else '%s %.1f' % (cls, conf[j])
if kpt_label:
plot_one_box(box, mosaic, label=label, color=color, line_thickness=tl, kpt_label=kpt_label, kpts=kpts[:,j], steps=steps, orig_shape=orig_shape)
else:
plot_one_box(box, mosaic, label=label, color=color, line_thickness=tl, kpt_label=kpt_label, orig_shape=orig_shape)
#cv2.imwrite(Path(paths[i]).name.split('.')[0] + "_box_{}.".format(j) + Path(paths[i]).name.split('.')[1], mosaic[:,:,::-1]) # used for debugging the dataloader pipeline
# Draw image filename labels
if paths:
label = Path(paths[i]).name[:40] # trim to 40 char
t_size = cv2.getTextSize(label, 0, fontScale=tl / 6, thickness=tf)[0]
cv2.putText(mosaic, label, (block_x + 5, block_y + t_size[1] + 5), 0, tl / 6, [220, 220, 220], thickness=tf,
lineType=cv2.LINE_AA)
# Image border
cv2.rectangle(mosaic, (block_x, block_y), (block_x + w, block_y + h), (255, 255, 255), thickness=3)
if fname:
r = min(1280. / max(h, w) / ns, 1.0) # ratio to limit image size
mosaic = cv2.resize(mosaic, (int(ns * w * r), int(ns * h * r)), interpolation=cv2.INTER_AREA)
#padH = int(orig_shape[1][1][1])
#padW = int(orig_shape[1][1][0])
#mosaic = mosaic[padH: -1-padH, padW:-1-padW,:]
#cv2.imwrite(fname, cv2.cvtColor(mosaic, cv2.COLOR_BGR2RGB)) # cv2 save
Image.fromarray(mosaic).save(fname) # PIL save
return mosaic
def plot_lr_scheduler(optimizer, scheduler, epochs=300, save_dir=''):
# Plot LR simulating training for full epochs
optimizer, scheduler = copy(optimizer), copy(scheduler) # do not modify originals
y = []
for _ in range(epochs):
scheduler.step()
y.append(optimizer.param_groups[0]['lr'])
plt.plot(y, '.-', label='LR')
plt.xlabel('epoch')
plt.ylabel('LR')
plt.grid()
plt.xlim(0, epochs)
plt.ylim(0)
plt.savefig(Path(save_dir) / 'LR.png', dpi=200)
plt.close()
def plot_test_txt(): # from utils.plots import *; plot_test()
# Plot test.txt histograms
x = np.loadtxt('test.txt', dtype=np.float32)
box = xyxy2xywh(x[:, :4])
cx, cy = box[:, 0], box[:, 1]
fig, ax = plt.subplots(1, 1, figsize=(6, 6), tight_layout=True)
ax.hist2d(cx, cy, bins=600, cmax=10, cmin=0)
ax.set_aspect('equal')
plt.savefig('hist2d.png', dpi=300)
fig, ax = plt.subplots(1, 2, figsize=(12, 6), tight_layout=True)
ax[0].hist(cx, bins=600)
ax[1].hist(cy, bins=600)
plt.savefig('hist1d.png', dpi=200)
def plot_targets_txt(): # from utils.plots import *; plot_targets_txt()
# Plot targets.txt histograms
x = np.loadtxt('targets.txt', dtype=np.float32).T
s = ['x targets', 'y targets', 'width targets', 'height targets']
fig, ax = plt.subplots(2, 2, figsize=(8, 8), tight_layout=True)
ax = ax.ravel()
for i in range(4):
ax[i].hist(x[i], bins=100, label='%.3g +/- %.3g' % (x[i].mean(), x[i].std()))
ax[i].legend()
ax[i].set_title(s[i])
plt.savefig('targets.jpg', dpi=200)
def plot_study_txt(path='', x=None): # from utils.plots import *; plot_study_txt()
# Plot study.txt generated by test.py
fig, ax = plt.subplots(2, 4, figsize=(10, 6), tight_layout=True)
# ax = ax.ravel()
fig2, ax2 = plt.subplots(1, 1, figsize=(8, 4), tight_layout=True)
# for f in [Path(path) / f'study_coco_{x}.txt' for x in ['yolov5s6', 'yolov5m6', 'yolov5l6', 'yolov5x6']]:
for f in sorted(Path(path).glob('study*.txt')):
y = np.loadtxt(f, dtype=np.float32, usecols=[0, 1, 2, 3, 7, 8, 9], ndmin=2).T
x = np.arange(y.shape[1]) if x is None else np.array(x)
s = ['P', 'R', 'mAP@.5', 'mAP@.5:.95', 't_inference (ms/img)', 't_NMS (ms/img)', 't_total (ms/img)']
# for i in range(7):
# ax[i].plot(x, y[i], '.-', linewidth=2, markersize=8)
# ax[i].set_title(s[i])
j = y[3].argmax() + 1
ax2.plot(y[6, 1:j], y[3, 1:j] * 1E2, '.-', linewidth=2, markersize=8,
label=f.stem.replace('study_coco_', '').replace('yolo', 'YOLO'))
ax2.plot(1E3 / np.array([209, 140, 97, 58, 35, 18]), [34.6, 40.5, 43.0, 47.5, 49.7, 51.5],
'k.-', linewidth=2, markersize=8, alpha=.25, label='EfficientDet')
ax2.grid(alpha=0.2)
ax2.set_yticks(np.arange(20, 60, 5))
ax2.set_xlim(0, 57)
ax2.set_ylim(30, 55)
ax2.set_xlabel('GPU Speed (ms/img)')
ax2.set_ylabel('COCO AP val')
ax2.legend(loc='lower right')
plt.savefig(str(Path(path).name) + '.png', dpi=300)
def plot_labels(labels, names=(), save_dir=Path(''), loggers=None):
# plot dataset labels
print('Plotting labels... ')
c, b, kpts = labels[:, 0], labels[:, 1:5].transpose(), labels[:, 5:].transpose() # classes, boxes
nc = int(c.max() + 1) # number of classes
x = pd.DataFrame(b.transpose(), columns=['x', 'y', 'width', 'height'])
# seaborn correlogram
sns.pairplot(x, corner=True, diag_kind='auto', kind='hist', diag_kws=dict(bins=50), plot_kws=dict(pmax=0.9))
plt.savefig(save_dir / 'labels_correlogram.jpg', dpi=200)
plt.close()
# matplotlib labels
matplotlib.use('svg') # faster
ax = plt.subplots(2, 2, figsize=(8, 8), tight_layout=True)[1].ravel()
ax[0].hist(c, bins=np.linspace(0, nc, nc + 1) - 0.5, rwidth=0.8)
ax[0].set_ylabel('instances')
if 0 < len(names) < 30:
ax[0].set_xticks(range(len(names)))
ax[0].set_xticklabels(names, rotation=90, fontsize=10)
else:
ax[0].set_xlabel('classes')
sns.histplot(x, x='x', y='y', ax=ax[2], bins=50, pmax=0.9)
sns.histplot(x, x='width', y='height', ax=ax[3], bins=50, pmax=0.9)
# rectangles
labels[:, 1:3] = 0.5 # center
labels[:, 1:] = xywh2xyxy(labels[:, 1:]) * 2000
img = Image.fromarray(np.ones((2000, 2000, 3), dtype=np.uint8) * 255)
for cls, *box in labels[:1000, :5]:
ImageDraw.Draw(img).rectangle(box, width=1, outline=colors(cls)) # plot
ax[1].imshow(img)
ax[1].axis('off')
for a in [0, 1, 2, 3]:
for s in ['top', 'right', 'left', 'bottom']:
ax[a].spines[s].set_visible(False)
plt.savefig(save_dir / 'labels.jpg', dpi=200)
matplotlib.use('Agg')
plt.close()
# loggers
for k, v in loggers.items() or {}:
if k == 'wandb' and v:
v.log({"Labels": [v.Image(str(x), caption=x.name) for x in save_dir.glob('*labels*.jpg')]}, commit=False)
def plot_evolution(yaml_file='data/hyp.finetune.yaml'): # from utils.plots import *; plot_evolution()
# Plot hyperparameter evolution results in evolve.txt
with open(yaml_file) as f:
hyp = yaml.safe_load(f)
x = np.loadtxt('evolve.txt', ndmin=2)
f = fitness(x)
# weights = (f - f.min()) ** 2 # for weighted results
plt.figure(figsize=(10, 12), tight_layout=True)
matplotlib.rc('font', **{'size': 8})
for i, (k, v) in enumerate(hyp.items()):
y = x[:, i + 7]
# mu = (y * weights).sum() / weights.sum() # best weighted result
mu = y[f.argmax()] # best single result
plt.subplot(6, 5, i + 1)
plt.scatter(y, f, c=hist2d(y, f, 20), cmap='viridis', alpha=.8, edgecolors='none')
plt.plot(mu, f.max(), 'k+', markersize=15)
plt.title('%s = %.3g' % (k, mu), fontdict={'size': 9}) # limit to 40 characters
if i % 5 != 0:
plt.yticks([])
print('%15s: %.3g' % (k, mu))
plt.savefig('evolve.png', dpi=200)
print('\nPlot saved as evolve.png')
def profile_idetection(start=0, stop=0, labels=(), save_dir=''):
# Plot iDetection '*.txt' per-image logs. from utils.plots import *; profile_idetection()
ax = plt.subplots(2, 4, figsize=(12, 6), tight_layout=True)[1].ravel()
s = ['Images', 'Free Storage (GB)', 'RAM Usage (GB)', 'Battery', 'dt_raw (ms)', 'dt_smooth (ms)', 'real-world FPS']
files = list(Path(save_dir).glob('frames*.txt'))
for fi, f in enumerate(files):
try:
results = np.loadtxt(f, ndmin=2).T[:, 90:-30] # clip first and last rows
n = results.shape[1] # number of rows
x = np.arange(start, min(stop, n) if stop else n)
results = results[:, x]
t = (results[0] - results[0].min()) # set t0=0s
results[0] = x
for i, a in enumerate(ax):
if i < len(results):
label = labels[fi] if len(labels) else f.stem.replace('frames_', '')
a.plot(t, results[i], marker='.', label=label, linewidth=1, markersize=5)
a.set_title(s[i])
a.set_xlabel('time (s)')
# if fi == len(files) - 1:
# a.set_ylim(bottom=0)
for side in ['top', 'right']:
a.spines[side].set_visible(False)
else:
a.remove()
except Exception as e:
print('Warning: Plotting error for %s; %s' % (f, e))
ax[1].legend()
plt.savefig(Path(save_dir) / 'idetection_profile.png', dpi=200)
def plot_results_overlay(start=0, stop=0): # from utils.plots import *; plot_results_overlay()
# Plot training 'results*.txt', overlaying train and val losses
s = ['train', 'train', 'train', 'Precision', 'mAP@0.5', 'val', 'val', 'val', 'Recall', 'mAP@0.5:0.95'] # legends
t = ['Box', 'Objectness', 'Classification', 'P-R', 'mAP-F1'] # titles
for f in sorted(glob.glob('results*.txt') + glob.glob('../../Downloads/results*.txt')):
results = np.loadtxt(f, usecols=[2, 3, 4, 8, 9, 12, 13, 14, 10, 11], ndmin=2).T
n = results.shape[1] # number of rows
x = range(start, min(stop, n) if stop else n)
fig, ax = plt.subplots(1, 5, figsize=(14, 3.5), tight_layout=True)
ax = ax.ravel()
for i in range(5):
for j in [i, i + 5]:
y = results[j, x]
ax[i].plot(x, y, marker='.', label=s[j])
# y_smooth = butter_lowpass_filtfilt(y)
# ax[i].plot(x, np.gradient(y_smooth), marker='.', label=s[j])
ax[i].set_title(t[i])
ax[i].legend()
ax[i].set_ylabel(f) if i == 0 else None # add filename
fig.savefig(f.replace('.txt', '.png'), dpi=200)
def plot_results(start=0, stop=0, bucket='', id=(), labels=(), save_dir=''):
# Plot training 'results*.txt'. from utils.plots import *; plot_results(save_dir='runs/train/exp')
fig, ax = plt.subplots(2, 5, figsize=(12, 6), tight_layout=True)
ax = ax.ravel()
s = ['Box', 'Objectness', 'Classification', 'Precision', 'Recall',
'val Box', 'val Objectness', 'val Classification', 'mAP@0.5', 'mAP@0.5:0.95']
if bucket:
# files = ['https://storage.googleapis.com/%s/results%g.txt' % (bucket, x) for x in id]
files = ['results%g.txt' % x for x in id]
c = ('gsutil cp ' + '%s ' * len(files) + '.') % tuple('gs://%s/results%g.txt' % (bucket, x) for x in id)
os.system(c)
else:
files = list(Path(save_dir).glob('results*.txt'))
assert len(files), 'No results.txt files found in %s, nothing to plot.' % os.path.abspath(save_dir)
for fi, f in enumerate(files):
try:
results = np.loadtxt(f, usecols=[2, 3, 4, 8, 9, 12, 13, 14, 10, 11], ndmin=2).T
n = results.shape[1] # number of rows
x = range(start, min(stop, n) if stop else n)
for i in range(10):
y = results[i, x]
if i in [0, 1, 2, 5, 6, 7]:
y[y == 0] = np.nan # don't show zero loss values
# y /= y[0] # normalize
label = labels[fi] if len(labels) else f.stem
ax[i].plot(x, y, marker='.', label=label, linewidth=2, markersize=8)
ax[i].set_title(s[i])
# if i in [5, 6, 7]: # share train and val loss y axes
# ax[i].get_shared_y_axes().join(ax[i], ax[i - 5])
except Exception as e:
print('Warning: Plotting error for %s; %s' % (f, e))
ax[1].legend()
fig.savefig(Path(save_dir) / 'results.png', dpi=200)
|
2301_81045437/yolov7_plate
|
utils/plots.py
|
Python
|
unknown
| 21,564
|
# PyTorch utils
import datetime
import logging
import math
import os
import platform
import subprocess
import time
from contextlib import contextmanager
from copy import deepcopy
from pathlib import Path
import torch
import torch.backends.cudnn as cudnn
import torch.nn as nn
import torch.nn.functional as F
import torchvision
try:
import thop # for FLOPS computation
except ImportError:
thop = None
logger = logging.getLogger(__name__)
@contextmanager
def torch_distributed_zero_first(local_rank: int):
"""
Decorator to make all processes in distributed training wait for each local_master to do something.
"""
if local_rank not in [-1, 0]:
torch.distributed.barrier()
yield
if local_rank == 0:
torch.distributed.barrier()
def init_torch_seeds(seed=0):
# Speed-reproducibility tradeoff https://pytorch.org/docs/stable/notes/randomness.html
torch.manual_seed(seed)
if seed == 0: # slower, more reproducible
cudnn.benchmark, cudnn.deterministic = False, True
else: # faster, less reproducible
cudnn.benchmark, cudnn.deterministic = True, False
def date_modified(path=__file__):
# return human-readable file modification date, i.e. '2021-3-26'
t = datetime.datetime.fromtimestamp(Path(path).stat().st_mtime)
return f'{t.year}-{t.month}-{t.day}'
def git_describe(path=Path(__file__).parent): # path must be a directory
# return human-readable git description, i.e. v5.0-5-g3e25f1e https://git-scm.com/docs/git-describe
s = f'git -C {path} describe --tags --long --always'
try:
return subprocess.check_output(s, shell=True, stderr=subprocess.STDOUT).decode()[:-1]
except subprocess.CalledProcessError as e:
return '' # not a git repository
def select_device(device='', batch_size=None):
# device = 'cpu' or '0' or '0,1,2,3'
s = f'YOLOv5 � {git_describe() or date_modified()} torch {torch.__version__} ' # string
cpu = device.lower() == 'cpu'
if cpu:
os.environ['CUDA_VISIBLE_DEVICES'] = '-1' # force torch.cuda.is_available() = False
elif device: # non-cpu device requested
os.environ['CUDA_VISIBLE_DEVICES'] = device # set environment variable
assert torch.cuda.is_available(), f'CUDA unavailable, invalid device {device} requested' # check availability
cuda = not cpu and torch.cuda.is_available()
if cuda:
n = torch.cuda.device_count()
if n > 1 and batch_size: # check that batch_size is compatible with device_count
assert batch_size % n == 0, f'batch-size {batch_size} not multiple of GPU count {n}'
space = ' ' * len(s)
for i, d in enumerate(device.split(',') if device else range(n)):
p = torch.cuda.get_device_properties(i)
s += f"{'' if i == 0 else space}CUDA:{d} ({p.name}, {p.total_memory / 1024 ** 2}MB)\n" # bytes to MB
else:
s += 'CPU\n'
logger.info(s.encode().decode('ascii', 'ignore') if platform.system() == 'Windows' else s) # emoji-safe
return torch.device('cuda:0' if cuda else 'cpu')
def time_synchronized():
# pytorch-accurate time
if torch.cuda.is_available():
torch.cuda.synchronize()
return time.time()
def profile(x, ops, n=100, device=None):
# profile a pytorch module or list of modules. Example usage:
# x = torch.randn(16, 3, 640, 640) # input
# m1 = lambda x: x * torch.sigmoid(x)
# m2 = nn.SiLU()
# profile(x, [m1, m2], n=100) # profile speed over 100 iterations
device = device or torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
x = x.to(device)
x.requires_grad = True
print(torch.__version__, device.type, torch.cuda.get_device_properties(0) if device.type == 'cuda' else '')
print(f"\n{'Params':>12s}{'GFLOPS':>12s}{'forward (ms)':>16s}{'backward (ms)':>16s}{'input':>24s}{'output':>24s}")
for m in ops if isinstance(ops, list) else [ops]:
m = m.to(device) if hasattr(m, 'to') else m # device
m = m.half() if hasattr(m, 'half') and isinstance(x, torch.Tensor) and x.dtype is torch.float16 else m # type
dtf, dtb, t = 0., 0., [0., 0., 0.] # dt forward, backward
try:
flops = thop.profile(m, inputs=(x,), verbose=False)[0] / 1E9 * 2 # GFLOPS
except:
flops = 0
for _ in range(n):
t[0] = time_synchronized()
y = m(x)
t[1] = time_synchronized()
try:
_ = y.sum().backward()
t[2] = time_synchronized()
except: # no backward method
t[2] = float('nan')
dtf += (t[1] - t[0]) * 1000 / n # ms per op forward
dtb += (t[2] - t[1]) * 1000 / n # ms per op backward
s_in = tuple(x.shape) if isinstance(x, torch.Tensor) else 'list'
s_out = tuple(y.shape) if isinstance(y, torch.Tensor) else 'list'
p = sum(list(x.numel() for x in m.parameters())) if isinstance(m, nn.Module) else 0 # parameters
print(f'{p:12}{flops:12.4g}{dtf:16.4g}{dtb:16.4g}{str(s_in):>24s}{str(s_out):>24s}')
def is_parallel(model):
return type(model) in (nn.parallel.DataParallel, nn.parallel.DistributedDataParallel)
def intersect_dicts(da, db, exclude=()):
# Dictionary intersection of matching keys and shapes, omitting 'exclude' keys, using da values
return {k: v for k, v in da.items() if k in db and not any(x in k for x in exclude) and v.shape == db[k].shape}
def initialize_weights(model):
for m in model.modules():
t = type(m)
if t is nn.Conv2d:
pass # nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu')
elif t is nn.BatchNorm2d:
m.eps = 1e-3
m.momentum = 0.03
elif t in [nn.Hardswish, nn.LeakyReLU, nn.ReLU, nn.ReLU6]:
m.inplace = True
def find_modules(model, mclass=nn.Conv2d):
# Finds layer indices matching module class 'mclass'
return [i for i, m in enumerate(model.module_list) if isinstance(m, mclass)]
def sparsity(model):
# Return global model sparsity
a, b = 0., 0.
for p in model.parameters():
a += p.numel()
b += (p == 0).sum()
return b / a
def prune(model, amount=0.3):
# Prune model to requested global sparsity
import torch.nn.utils.prune as prune
print('Pruning model... ', end='')
for name, m in model.named_modules():
if isinstance(m, nn.Conv2d):
prune.l1_unstructured(m, name='weight', amount=amount) # prune
prune.remove(m, 'weight') # make permanent
print(' %.3g global sparsity' % sparsity(model))
def fuse_conv_and_bn(conv, bn):
# Fuse convolution and batchnorm layers https://tehnokv.com/posts/fusing-batchnorm-and-conv/
fusedconv = nn.Conv2d(conv.in_channels,
conv.out_channels,
kernel_size=conv.kernel_size,
stride=conv.stride,
padding=conv.padding,
groups=conv.groups,
bias=True).requires_grad_(False).to(conv.weight.device)
# prepare filters
w_conv = conv.weight.clone().view(conv.out_channels, -1)
w_bn = torch.diag(bn.weight.div(torch.sqrt(bn.eps + bn.running_var)))
fusedconv.weight.copy_(torch.mm(w_bn, w_conv).view(fusedconv.weight.shape))
# prepare spatial bias
b_conv = torch.zeros(conv.weight.size(0), device=conv.weight.device) if conv.bias is None else conv.bias
b_bn = bn.bias - bn.weight.mul(bn.running_mean).div(torch.sqrt(bn.running_var + bn.eps))
fusedconv.bias.copy_(torch.mm(w_bn, b_conv.reshape(-1, 1)).reshape(-1) + b_bn)
return fusedconv
def model_info(model, verbose=False, img_size=640):
# Model information. img_size may be int or list, i.e. img_size=640 or img_size=[640, 320]
n_p = sum(x.numel() for x in model.parameters()) # number parameters
n_g = sum(x.numel() for x in model.parameters() if x.requires_grad) # number gradients
if verbose:
print('%5s %40s %9s %12s %20s %10s %10s' % ('layer', 'name', 'gradient', 'parameters', 'shape', 'mu', 'sigma'))
for i, (name, p) in enumerate(model.named_parameters()):
name = name.replace('module_list.', '')
print('%5g %40s %9s %12g %20s %10.3g %10.3g' %
(i, name, p.requires_grad, p.numel(), list(p.shape), p.mean(), p.std()))
try: # FLOPS
from thop import profile
stride = max(int(model.stride.max()), 32) if hasattr(model, 'stride') else 32
img = torch.zeros((1, model.yaml.get('ch', 3), stride, stride), device=next(model.parameters()).device) # input
flops = profile(deepcopy(model), inputs=(img,), verbose=False)[0] / 1E9 * 2 # stride GFLOPS
img_size = img_size if isinstance(img_size, list) else [img_size, img_size] # expand if int/float
fs = ', %.1f GFLOPS' % (flops * img_size[0] / stride * img_size[1] / stride) # 640x640 GFLOPS
except (ImportError, Exception):
fs = ''
logger.info(f"Model Summary: {len(list(model.modules()))} layers, {n_p} parameters, {n_g} gradients{fs}")
def load_classifier(name='resnet101', n=2):
# Loads a pretrained model reshaped to n-class output
model = torchvision.models.__dict__[name](pretrained=True)
# ResNet model properties
# input_size = [3, 224, 224]
# input_space = 'RGB'
# input_range = [0, 1]
# mean = [0.485, 0.456, 0.406]
# std = [0.229, 0.224, 0.225]
# Reshape output to n classes
filters = model.fc.weight.shape[1]
model.fc.bias = nn.Parameter(torch.zeros(n), requires_grad=True)
model.fc.weight = nn.Parameter(torch.zeros(n, filters), requires_grad=True)
model.fc.out_features = n
return model
def scale_img(img, ratio=1.0, same_shape=False, gs=32): # img(16,3,256,416)
# scales img(bs,3,y,x) by ratio constrained to gs-multiple
if ratio == 1.0:
return img
else:
h, w = img.shape[2:]
s = (int(h * ratio), int(w * ratio)) # new size
img = F.interpolate(img, size=s, mode='bilinear', align_corners=False) # resize
if not same_shape: # pad/crop img
h, w = [math.ceil(x * ratio / gs) * gs for x in (h, w)]
return F.pad(img, [0, w - s[1], 0, h - s[0]], value=0.447) # value = imagenet mean
def copy_attr(a, b, include=(), exclude=()):
# Copy attributes from b to a, options to only include [...] and to exclude [...]
for k, v in b.__dict__.items():
if (len(include) and k not in include) or k.startswith('_') or k in exclude:
continue
else:
setattr(a, k, v)
class ModelEMA:
""" Model Exponential Moving Average from https://github.com/rwightman/pytorch-image-models
Keep a moving average of everything in the model state_dict (parameters and buffers).
This is intended to allow functionality like
https://www.tensorflow.org/api_docs/python/tf/train/ExponentialMovingAverage
A smoothed version of the weights is necessary for some training schemes to perform well.
This class is sensitive where it is initialized in the sequence of model init,
GPU assignment and distributed training wrappers.
"""
def __init__(self, model, decay=0.9999, updates=0):
# Create EMA
self.ema = deepcopy(model.module if is_parallel(model) else model).eval() # FP32 EMA
# if next(model.parameters()).device.type != 'cpu':
# self.ema.half() # FP16 EMA
self.updates = updates # number of EMA updates
self.decay = lambda x: decay * (1 - math.exp(-x / 2000)) # decay exponential ramp (to help early epochs)
for p in self.ema.parameters():
p.requires_grad_(False)
def update(self, model):
# Update EMA parameters
with torch.no_grad():
self.updates += 1
d = self.decay(self.updates)
msd = model.module.state_dict() if is_parallel(model) else model.state_dict() # model state_dict
for k, v in self.ema.state_dict().items():
if v.dtype.is_floating_point:
v *= d
v += (1. - d) * msd[k].detach()
def update_attr(self, model, include=(), exclude=('process_group', 'reducer')):
# Update EMA attributes
copy_attr(self.ema, model, include, exclude)
|
2301_81045437/yolov7_plate
|
utils/torch_utils.py
|
Python
|
unknown
| 12,430
|
# init
|
2301_81045437/yolov7_plate
|
utils/wandb_logging/__init__.py
|
Python
|
unknown
| 6
|
import argparse
import yaml
from wandb_utils import WandbLogger
WANDB_ARTIFACT_PREFIX = 'wandb-artifact://'
def create_dataset_artifact(opt):
with open(opt.data) as f:
data = yaml.safe_load(f) # data dict
logger = WandbLogger(opt, '', None, data, job_type='Dataset Creation')
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--data', type=str, default='data/coco128.yaml', help='data.yaml path')
parser.add_argument('--single-cls', action='store_true', help='train as single-class dataset')
parser.add_argument('--project', type=str, default='YOLOv5', help='name of W&B Project')
opt = parser.parse_args()
opt.resume = False # Explicitly disallow resume check for dataset upload job
create_dataset_artifact(opt)
|
2301_81045437/yolov7_plate
|
utils/wandb_logging/log_dataset.py
|
Python
|
unknown
| 800
|
import json
import sys
from pathlib import Path
import torch
import yaml
from tqdm import tqdm
sys.path.append(str(Path(__file__).parent.parent.parent)) # add utils/ to path
from utils.datasets import LoadImagesAndLabels
from utils.datasets import img2label_paths
from utils.general import colorstr, xywh2xyxy, check_dataset
try:
import wandb
from wandb import init, finish
except ImportError:
wandb = None
WANDB_ARTIFACT_PREFIX = 'wandb-artifact://'
def remove_prefix(from_string, prefix=WANDB_ARTIFACT_PREFIX):
return from_string[len(prefix):]
def check_wandb_config_file(data_config_file):
wandb_config = '_wandb.'.join(data_config_file.rsplit('.', 1)) # updated data.yaml path
if Path(wandb_config).is_file():
return wandb_config
return data_config_file
def get_run_info(run_path):
run_path = Path(remove_prefix(run_path, WANDB_ARTIFACT_PREFIX))
run_id = run_path.stem
project = run_path.parent.stem
model_artifact_name = 'run_' + run_id + '_model'
return run_id, project, model_artifact_name
def check_wandb_resume(opt):
process_wandb_config_ddp_mode(opt) if opt.global_rank not in [-1, 0] else None
if isinstance(opt.resume, str):
if opt.resume.startswith(WANDB_ARTIFACT_PREFIX):
if opt.global_rank not in [-1, 0]: # For resuming DDP runs
run_id, project, model_artifact_name = get_run_info(opt.resume)
api = wandb.Api()
artifact = api.artifact(project + '/' + model_artifact_name + ':latest')
modeldir = artifact.download()
opt.weights = str(Path(modeldir) / "last.pt")
return True
return None
def process_wandb_config_ddp_mode(opt):
with open(opt.data) as f:
data_dict = yaml.safe_load(f) # data dict
train_dir, val_dir = None, None
if isinstance(data_dict['train'], str) and data_dict['train'].startswith(WANDB_ARTIFACT_PREFIX):
api = wandb.Api()
train_artifact = api.artifact(remove_prefix(data_dict['train']) + ':' + opt.artifact_alias)
train_dir = train_artifact.download()
train_path = Path(train_dir) / 'data/images/'
data_dict['train'] = str(train_path)
if isinstance(data_dict['val'], str) and data_dict['val'].startswith(WANDB_ARTIFACT_PREFIX):
api = wandb.Api()
val_artifact = api.artifact(remove_prefix(data_dict['val']) + ':' + opt.artifact_alias)
val_dir = val_artifact.download()
val_path = Path(val_dir) / 'data/images/'
data_dict['val'] = str(val_path)
if train_dir or val_dir:
ddp_data_path = str(Path(val_dir) / 'wandb_local_data.yaml')
with open(ddp_data_path, 'w') as f:
yaml.safe_dump(data_dict, f)
opt.data = ddp_data_path
class WandbLogger():
def __init__(self, opt, name, run_id, data_dict, job_type='Training'):
# Pre-training routine --
self.job_type = job_type
self.wandb, self.wandb_run, self.data_dict = wandb, None if not wandb else wandb.run, data_dict
# It's more elegant to stick to 1 wandb.init call, but useful config data is overwritten in the WandbLogger's wandb.init call
if isinstance(opt.resume, str): # checks resume from artifact
if opt.resume.startswith(WANDB_ARTIFACT_PREFIX):
run_id, project, model_artifact_name = get_run_info(opt.resume)
model_artifact_name = WANDB_ARTIFACT_PREFIX + model_artifact_name
assert wandb, 'install wandb to resume wandb runs'
# Resume wandb-artifact:// runs here| workaround for not overwriting wandb.config
self.wandb_run = wandb.init(id=run_id, project=project, resume='allow')
opt.resume = model_artifact_name
elif self.wandb:
self.wandb_run = wandb.init(config=opt,
resume="allow",
project='YOLOv5' if opt.project == 'runs/train' else Path(opt.project).stem,
name=name,
job_type=job_type,
id=run_id) if not wandb.run else wandb.run
if self.wandb_run:
if self.job_type == 'Training':
if not opt.resume:
wandb_data_dict = self.check_and_upload_dataset(opt) if opt.upload_dataset else data_dict
# Info useful for resuming from artifacts
self.wandb_run.config.opt = vars(opt)
self.wandb_run.config.data_dict = wandb_data_dict
self.data_dict = self.setup_training(opt, data_dict)
if self.job_type == 'Dataset Creation':
self.data_dict = self.check_and_upload_dataset(opt)
else:
prefix = colorstr('wandb: ')
print(f"{prefix}Install Weights & Biases for YOLOv5 logging with 'pip install wandb' (recommended)")
def check_and_upload_dataset(self, opt):
assert wandb, 'Install wandb to upload dataset'
check_dataset(self.data_dict)
config_path = self.log_dataset_artifact(opt.data,
opt.single_cls,
'YOLOv5' if opt.project == 'runs/train' else Path(opt.project).stem)
print("Created dataset config file ", config_path)
with open(config_path) as f:
wandb_data_dict = yaml.safe_load(f)
return wandb_data_dict
def setup_training(self, opt, data_dict):
self.log_dict, self.current_epoch, self.log_imgs = {}, 0, 16 # Logging Constants
self.bbox_interval = opt.bbox_interval
if isinstance(opt.resume, str):
modeldir, _ = self.download_model_artifact(opt)
if modeldir:
self.weights = Path(modeldir) / "last.pt"
config = self.wandb_run.config
opt.weights, opt.save_period, opt.batch_size, opt.bbox_interval, opt.epochs, opt.hyp = str(
self.weights), config.save_period, config.total_batch_size, config.bbox_interval, config.epochs, \
config.opt['hyp']
data_dict = dict(self.wandb_run.config.data_dict) # eliminates the need for config file to resume
if 'val_artifact' not in self.__dict__: # If --upload_dataset is set, use the existing artifact, don't download
self.train_artifact_path, self.train_artifact = self.download_dataset_artifact(data_dict.get('train'),
opt.artifact_alias)
self.val_artifact_path, self.val_artifact = self.download_dataset_artifact(data_dict.get('val'),
opt.artifact_alias)
self.result_artifact, self.result_table, self.val_table, self.weights = None, None, None, None
if self.train_artifact_path is not None:
train_path = Path(self.train_artifact_path) / 'data/images/'
data_dict['train'] = str(train_path)
if self.val_artifact_path is not None:
val_path = Path(self.val_artifact_path) / 'data/images/'
data_dict['val'] = str(val_path)
self.val_table = self.val_artifact.get("val")
self.map_val_table_path()
if self.val_artifact is not None:
self.result_artifact = wandb.Artifact("run_" + wandb.run.id + "_progress", "evaluation")
self.result_table = wandb.Table(["epoch", "id", "prediction", "avg_confidence"])
if opt.bbox_interval == -1:
self.bbox_interval = opt.bbox_interval = (opt.epochs // 10) if opt.epochs > 10 else 1
return data_dict
def download_dataset_artifact(self, path, alias):
if isinstance(path, str) and path.startswith(WANDB_ARTIFACT_PREFIX):
dataset_artifact = wandb.use_artifact(remove_prefix(path, WANDB_ARTIFACT_PREFIX) + ":" + alias)
assert dataset_artifact is not None, "'Error: W&B dataset artifact doesn\'t exist'"
datadir = dataset_artifact.download()
return datadir, dataset_artifact
return None, None
def download_model_artifact(self, opt):
if opt.resume.startswith(WANDB_ARTIFACT_PREFIX):
model_artifact = wandb.use_artifact(remove_prefix(opt.resume, WANDB_ARTIFACT_PREFIX) + ":latest")
assert model_artifact is not None, 'Error: W&B model artifact doesn\'t exist'
modeldir = model_artifact.download()
epochs_trained = model_artifact.metadata.get('epochs_trained')
total_epochs = model_artifact.metadata.get('total_epochs')
assert epochs_trained < total_epochs, 'training to %g epochs is finished, nothing to resume.' % (
total_epochs)
return modeldir, model_artifact
return None, None
def log_model(self, path, opt, epoch, fitness_score, best_model=False):
model_artifact = wandb.Artifact('run_' + wandb.run.id + '_model', type='model', metadata={
'original_url': str(path),
'epochs_trained': epoch + 1,
'save period': opt.save_period,
'project': opt.project,
'total_epochs': opt.epochs,
'fitness_score': fitness_score
})
model_artifact.add_file(str(path / 'last.pt'), name='last.pt')
wandb.log_artifact(model_artifact,
aliases=['latest', 'epoch ' + str(self.current_epoch), 'best' if best_model else ''])
print("Saving model artifact on epoch ", epoch + 1)
def log_dataset_artifact(self, data_file, single_cls, project, overwrite_config=False):
with open(data_file) as f:
data = yaml.safe_load(f) # data dict
nc, names = (1, ['item']) if single_cls else (int(data['nc']), data['names'])
names = {k: v for k, v in enumerate(names)} # to index dictionary
self.train_artifact = self.create_dataset_table(LoadImagesAndLabels(
data['train'], rect=True, batch_size=1), names, name='train') if data.get('train') else None
self.val_artifact = self.create_dataset_table(LoadImagesAndLabels(
data['val'], rect=True, batch_size=1), names, name='val') if data.get('val') else None
if data.get('train'):
data['train'] = WANDB_ARTIFACT_PREFIX + str(Path(project) / 'train')
if data.get('val'):
data['val'] = WANDB_ARTIFACT_PREFIX + str(Path(project) / 'val')
path = data_file if overwrite_config else '_wandb.'.join(data_file.rsplit('.', 1)) # updated data.yaml path
data.pop('download', None)
with open(path, 'w') as f:
yaml.safe_dump(data, f)
if self.job_type == 'Training': # builds correct artifact pipeline graph
self.wandb_run.use_artifact(self.val_artifact)
self.wandb_run.use_artifact(self.train_artifact)
self.val_artifact.wait()
self.val_table = self.val_artifact.get('val')
self.map_val_table_path()
else:
self.wandb_run.log_artifact(self.train_artifact)
self.wandb_run.log_artifact(self.val_artifact)
return path
def map_val_table_path(self):
self.val_table_map = {}
print("Mapping dataset")
for i, data in enumerate(tqdm(self.val_table.data)):
self.val_table_map[data[3]] = data[0]
def create_dataset_table(self, dataset, class_to_id, name='dataset'):
# TODO: Explore multiprocessing to slpit this loop parallely| This is essential for speeding up the the logging
artifact = wandb.Artifact(name=name, type="dataset")
img_files = tqdm([dataset.path]) if isinstance(dataset.path, str) and Path(dataset.path).is_dir() else None
img_files = tqdm(dataset.img_files) if not img_files else img_files
for img_file in img_files:
if Path(img_file).is_dir():
artifact.add_dir(img_file, name='data/images')
labels_path = 'labels'.join(dataset.path.rsplit('images', 1))
artifact.add_dir(labels_path, name='data/labels')
else:
artifact.add_file(img_file, name='data/images/' + Path(img_file).name)
label_file = Path(img2label_paths([img_file])[0])
artifact.add_file(str(label_file),
name='data/labels/' + label_file.name) if label_file.exists() else None
table = wandb.Table(columns=["id", "train_image", "Classes", "name"])
class_set = wandb.Classes([{'id': id, 'name': name} for id, name in class_to_id.items()])
for si, (img, labels, paths, shapes) in enumerate(tqdm(dataset)):
box_data, img_classes = [], {}
for cls, *xywh in labels[:, 1:].tolist():
cls = int(cls)
box_data.append({"position": {"middle": [xywh[0], xywh[1]], "width": xywh[2], "height": xywh[3]},
"class_id": cls,
"box_caption": "%s" % (class_to_id[cls])})
img_classes[cls] = class_to_id[cls]
boxes = {"ground_truth": {"box_data": box_data, "class_labels": class_to_id}} # inference-space
table.add_data(si, wandb.Image(paths, classes=class_set, boxes=boxes), json.dumps(img_classes),
Path(paths).name)
artifact.add(table, name)
return artifact
def log_training_progress(self, predn, path, names):
if self.val_table and self.result_table:
class_set = wandb.Classes([{'id': id, 'name': name} for id, name in names.items()])
box_data = []
total_conf = 0
for *xyxy, conf, cls in predn.tolist():
if conf >= 0.25:
box_data.append(
{"position": {"minX": xyxy[0], "minY": xyxy[1], "maxX": xyxy[2], "maxY": xyxy[3]},
"class_id": int(cls),
"box_caption": "%s %.3f" % (names[cls], conf),
"scores": {"class_score": conf},
"domain": "pixel"})
total_conf = total_conf + conf
boxes = {"predictions": {"box_data": box_data, "class_labels": names}} # inference-space
id = self.val_table_map[Path(path).name]
self.result_table.add_data(self.current_epoch,
id,
wandb.Image(self.val_table.data[id][1], boxes=boxes, classes=class_set),
total_conf / max(1, len(box_data))
)
def log(self, log_dict):
if self.wandb_run:
for key, value in log_dict.items():
self.log_dict[key] = value
def end_epoch(self, best_result=False):
if self.wandb_run:
wandb.log(self.log_dict)
self.log_dict = {}
if self.result_artifact:
train_results = wandb.JoinedTable(self.val_table, self.result_table, "id")
self.result_artifact.add(train_results, 'result')
wandb.log_artifact(self.result_artifact, aliases=['latest', 'epoch ' + str(self.current_epoch),
('best' if best_result else '')])
self.result_table = wandb.Table(["epoch", "id", "prediction", "avg_confidence"])
self.result_artifact = wandb.Artifact("run_" + wandb.run.id + "_progress", "evaluation")
def finish_run(self):
if self.wandb_run:
if self.log_dict:
wandb.log(self.log_dict)
wandb.run.finish()
|
2301_81045437/yolov7_plate
|
utils/wandb_logging/wandb_utils.py
|
Python
|
unknown
| 16,011
|
<!doctype html>
<meta charset="utf-8">
<title>登录 / 借阅系统</title>
<style>
body{font-family:Arial,Helvetica,sans-serif;font-size:14px}
table{border-collapse:collapse;margin-top:6px}
td,th{border:1px solid #999;padding:4px 8px}
button{margin:0 2px;padding:2px 6px}
.hide{display:none}
input[type=text],input[type=number]{width:120px;margin-right:4px}
</style>
<form id="f">
<input name="u" placeholder="用户名" required>
<input name="p" type="password" placeholder="密码" required>
<button type="submit" id="btn">登录</button>
</form>
<a href="#" id="toggle">切换注册</a>
<div id="info" class="hide">
欢迎 <span id="username"></span>（ID：<span id="uid"></span>） 权限：<span id="perm"></span>
</div>
<!-- 管理员 -->
<div id="adminPanel" class="hide">
<h3>管理员操作</h3>
<div>
<input id="newTitle" placeholder="书名">
<input id="newAuthor" placeholder="作者">
<button onclick="addBook()">添加书籍</button>
</div>
<div style="margin-top:4px">
<input id="updBookId" type="number" placeholder="书籍ID">
<input id="updStockValue" type="number" placeholder="新库存">
<button onclick="updStock()">修改库存</button>
</div>
</div>
<h3>全部书籍</h3>
<table id="bookTable">
<thead>
<tr><th>ID</th><th>书名</th><th>作者</th><th>库存</th><th>操作</th></tr>
</thead>
<tbody></tbody>
</table>
<h3 id="borrowTitle" class="hide">借阅记录</h3>
<table id="borrowTable" class="hide">
<thead>
<tr>
<th>借阅ID</th><th>书名</th><th>作者</th><th>用户名</th>
<th>借阅日期</th><th>归还日期</th><th>操作</th>
</tr>
</thead>
<tbody></tbody>
</table>
<script>
const base = 'http://192.168.232.129:8080';
const shortDate = str => str ? str.split('T')[0] : '';
async function get(url){return fetch(url).then(r=>r.json())}
async function post(url){return fetch(url,{method:'POST'}).then(r=>r.text())}
let isLogin = 1, curUser = null;
toggle.onclick=()=>{
isLogin=!isLogin;
btn.textContent=isLogin?'登录':'注册';
toggle.textContent=isLogin?'切换注册':'切换登录';
};
f.onsubmit=async e=>{
e.preventDefault();
const {u,p}=f;
if(isLogin){
const loginTxt=await post(`${base}/users/loginByName/?username=${u.value}&userpassword=${p.value}`);
if(loginTxt!=='Login successful'){alert(loginTxt);return;}
curUser=await get(`${base}/users/byName/?username=${u.value}`);
}else{
const regTxt=await post(`${base}/users/?username=${u.value}&userpassword=${p.value}&permission=normal`);
alert(regTxt);
if(regTxt!=='User registered successfully')return;
curUser=await get(`${base}/users/byName/?username=${u.value}`);
}
username.textContent=curUser.username;
uid.textContent=curUser.id;
perm.textContent=curUser.permission;
info.classList.remove('hide');
if(curUser.permission==='admin') adminPanel.classList.remove('hide');
await refreshAll();
f.reset();
};
async function refreshAll(){
await loadBooks();
await loadBorrowRecords();
}
async function loadBooks(){
const books=await get(`${base}/books/all`);
const tbody=bookTable.querySelector('tbody');
tbody.innerHTML='';
books.forEach(b=>{
const canBorrow=+b.stock>0;
tbody.insertAdjacentHTML('beforeend',
`<tr>
<td>${b.id}</td><td>${b.title}</td><td>${b.author}</td><td>${b.stock}</td>
<td>
${curUser ? `<button onclick="borrow(${b.id})" ${canBorrow?'':'disabled'}>借书</button>` : ''}
</td>
</tr>`);
});
}
async function loadBorrowRecords(){
let records;
if(curUser.permission==='admin'){
records=await get(`${base}/borrow-records`);
}else{
records=await get(`${base}/borrow-records/byUserId/?user_id=${curUser.id}`);
}
const tbody=borrowTable.querySelector('tbody');
tbody.innerHTML='';
for(const r of records){
const [book,user]=await Promise.all([
get(`${base}/books/byId/?id=${r.book_id}`),
get(`${base}/users/byId/?id=${r.user_id}`)
]);
const canReturn=curUser.permission==='admin' || r.user_id===curUser.id;
const returned=r.return_date && r.return_date!=='null';
tbody.insertAdjacentHTML('beforeend',
`<tr>
<td>${r.id}</td><td>${book.title}</td><td>${book.author}</td><td>${user.username}</td>
<td>${shortDate(r.borrow_date)}</td>
<td>${returned?shortDate(r.return_date):'未归还'}</td>
<td>
${canReturn && !returned
? `<button onclick="returnBook(${r.id})">还书</button>` : ''}
</td>
</tr>`);
}
borrowTitle.classList.remove('hide');
borrowTable.classList.remove('hide');
}
async function borrow(bookId){
const txt=await post(`${base}/borrow-records/borrow?user_id=${curUser.id}&book_id=${bookId}`);
alert(txt);
await refreshAll();
}
async function returnBook(recordId){
const txt=await post(`${base}/borrow-records/return?record_id=${recordId}`);
alert(txt);
await refreshAll();
}
async function addBook(){
const title=newTitle.value.trim(),author=newAuthor.value.trim();
if(!title||!author){alert('请输入书名和作者');return;}
const txt=await post(`${base}/books?title=${encodeURIComponent(title)}&author=${encodeURIComponent(author)}`);
alert(txt);
newTitle.value=''; newAuthor.value='';
await refreshAll();
}
async function updStock(){
const bookId=updBookId.value,stock=updStockValue.value;
if(!bookId||stock===''){alert('请输入书籍ID和新库存');return;}
const txt=await post(`${base}/books/updateStock/?book_id=${bookId}&new_stock=${stock}`);
alert(txt);
updBookId.value=''; updStock.value='';
await refreshAll();
}
loadBooks();
</script>
|
2301_79626091/JIT-Cangjie-examples
|
hanzongao/web/index.html
|
HTML
|
apache-2.0
| 5,699
|
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Document</title>
<link rel="stylesheet" href="./main.css">
</head>
<body>
<h1>Coffee Order</h1>
<ul id="orders">
<!-- <li class="order" id="1">
<p>
Name:
<span class="name">John</span>
<input type="text" class="name nonedit">
</p>
<p>
Drink:
<span class="drink">Coffee</span>
<input type="text" class="drink nonedit">
</p>
<button data-id="1" class="delete-order">Delete</button>
<button class="edit-order">Edit</button>
<button class="save-edit nonedit">Save</button>
<button class="cancel-edit nonedit">Cancel</button>
</li>
<li class="order" id="2">
<p>
Name:
<span class="name">Emily</span>
<input type="text" class="name nonedit">
</p>
<p>
Drink:
<span class="drink">Mocha</span>
<input type="text" class="drink nonedit">
</p>
<button data-id="2" class="delete-order">Delete</button>
<button class="edit-order">Edit</button>
<button class="save-edit nonedit">Save</button>
<button class="cancel-edit nonedit">Cancel</button>
</li> -->
</ul>
<h4>Add a Coffee Order</h4>
<p>name: <input type="text" id="name"></p>
<p>drink: <input type="text" id="drink"></p>
<button id="add-order">Add!</button>
<script src="./jquery-3.5.1.js"></script>
<script src="./script.js"></script>
</body>
</html>
|
2301_79626091/JIT-Cangjie-examples
|
songqvlv/CoffeeOrder/src/public/index.html
|
HTML
|
apache-2.0
| 1,811
|
* {
padding: 0;
margin: 10px;
}
#orders {
list-style-type: none;
margin: 0;
}
#orders .order {
background-color: #c4c4c4;
padding: 5px;
}
#orders .nonedit {
display: none;
}
#orders .edit {
display: none;
}
button {
padding: 5px 10px;
}
|
2301_79626091/JIT-Cangjie-examples
|
songqvlv/CoffeeOrder/src/public/main.css
|
CSS
|
apache-2.0
| 277
|
$(function () {
let $name = $('#name')
let $drink = $('#drink')
let $orders = $('#orders')
function addOrder(order) {
$orders.append(`<li class="order" id="${order.id}">
<p>
Name: <span class="name">${order.name}</span>
<input type="text" class="name nonedit">
</p>
<p>
Drink: <span class="drink">${order.drink}</span>
<input type="text" class="drink nonedit">
</p>
<!--<button data-id="${order.id}" class="delete-order">Delete</button>
<button data-id="${order.id}" class="edit-order">Edit</button>
<button data-id="${order.id}" class="save-edit nonedit">Save</button>
<button data-id="${order.id}" class="cancel-edit nonedit">Cancel</button>-->
</li>`)
}
$.ajax({
url: '/orders',
type: 'GET',
dataType: 'json',
success: function (data) {
console.log(data)
//let orders = JSON.parse(data)这里的data已经是js对象了，而且是个对象数组
$.each(data, function (index, order) {
addOrder(order)
})
},
error: function () {
alert('error in GET')
}
})
$('#add-order').on('click', function () {
if($name.val() === '' || $drink.val() === ''){
alert('Please input name and drink')
return
}
$.ajax({
url: '/orders',
type: 'POST',
dataType: 'json', //服务器返回的数据类型
contentType: 'application/json', //发送的数据类型
data: JSON.stringify({
name: $name.val(),
drink: $drink.val()
}),
success: function (data) {
console.log(data)
addOrder(data)
},
error: function () {
alert('error in POST')
}
})
//清空输入框
$name.val('')
$drink.val('')
})
/* $orders.delegate('.delete-order', 'click', function () {
$li = $(this).closest('.order')
$.ajax({
url: `/orders/${$li.attr('id')}`,
type: 'DELETE',
success: function () {
$li.slideUp(300, function () {
$li.remove() // 从DOM中移除元素，slideUp()不会移除而是添加了display:none
})
},
error: function () {
alert('error in DELETE')
}
})
})
$orders.delegate('.edit-order', 'click', function () {
$li = $(this).closest('.order')
$li.find('input.name').val($li.find('span.name').text())
$li.find('input.drink').val($li.find('span.drink').text())
$li.find('span,.edit-order').addClass('edit')
$li.find('.nonedit').removeClass('nonedit')
})
$orders.delegate('.cancel-edit', 'click', function () {
$li = $(this).closest('.order')
$li.find('span,.edit-order').removeClass('edit')
$li.find('input,.save-edit,.cancel-edit').addClass('nonedit')
})
$orders.delegate('.save-edit', 'click', function () {
$li = $(this).closest('.order')
$.ajax({
url: `/orders/${$li.attr('id')}`,
type: 'PUT',
dataType: 'json',
contentType: 'application/json',
data: JSON.stringify({
name: $li.find('input.name').val(),
drink: $li.find('input.drink').val()
}),
success: function () {
$li.find('span.name').text($li.find('input.name').val())
$li.find('span.drink').text($li.find('input.drink').val())
$li.find('span,.edit-order').removeClass('edit')
$li.find('input,.save-edit,.cancel-edit').addClass('nonedit')
},
error: function () {
alert('error in PUT')
}
})
})*/
})
|
2301_79626091/JIT-Cangjie-examples
|
songqvlv/CoffeeOrder/src/public/script.js
|
JavaScript
|
apache-2.0
| 4,073
|
import os
from pathlib import Path
import argparse
def get_args() -> argparse.Namespace:
parser = argparse.ArgumentParser()
parser.add_argument("--fix", default=False, help="将文件的换行符转换为 LF", action="store_true")
parser.add_argument("--build", default=False, help = "生成 Dialog 列表和帮助列表", action="store_true")
parser.add_argument("--sort", default=False, help = "对列表标签重新排序", action="store_true")
parser.add_argument("--check", default=False, help = "检查是否包含重复的模型或插件", action="store_true")
return parser.parse_args()
def get_content(file: str) -> list:
content = []
if not os.path.exists(file):
print(f"{file} 未找到")
return content
with open(file, "r", encoding = "utf8") as f:
# content = f.readlines()
content = f.read().split("\n")
return content
def write_content(content: list, path: str) -> None:
if len(content) == 0:
return
with open(path, "w", encoding="utf8", newline="\n") as f:
for item in content:
f.write(item + "\n")
def build_extension_list(input_file: str, output_file: str) -> None:
ori_content = get_content(input_file)
content = []
for line in ori_content:
if line == "":
continue
if len(line.split()) < 5:
print(f"{input_file} 出现元素缺失, 缺失元素的内容为: {line}")
return
point = line.split()[0]
name = line.split()[2].split("/").pop()
status = line.split()[4]
text = f"{point} {name} {status}"
content.append(text)
write_content(content, output_file)
def build_sd_webui_extension_desc(input_file: str, output_file: str) -> None:
ori_content = get_content(input_file)
content = []
content.append("Stable Diffusion WebUI 插件说明：")
content.append("注：")
content.append("1、有些插件因为年久失修，可能会出现兼容性问题。具体介绍请通过链接查看项目的说明")
content.append("2、在名称右上角标 * 的为安装时默认勾选的插件")
count = 0
for line in ori_content:
if line == "":
continue
if len(line.split()) < 7:
print(f"{input_file} 出现元素缺失, 缺失元素的内容为: {line}")
return
count += 1
link = line.split()[2]
ext_name = link.split("/").pop()
status = "*" if line.split()[4] == "ON" else ""
desc = line.split()[6]
text = f"\n{count}、{ext_name}{status}\n描述：{desc}\n链接：{link}"
content.append(text)
write_content(content, output_file)
def build_comfyui_extension_desc(input_file_1: str, input_file_2: str, output_file: str) -> None:
ori_content_1 = get_content(input_file_1)
ori_content_2 = get_content(input_file_2)
content = []
content.append("ComfyUI 插件 / 自定义节点说明：")
content.append("注：")
content.append("1、有些插件因为年久失修，可能会出现兼容性问题。具体介绍请通过链接查看项目的说明")
content.append("2、在名称右上角标 * 的为安装时默认勾选的插件")
# 插件
content.append("\n插件：")
count = 0
for line in ori_content_1:
if line == "":
continue
if len(line.split()) < 7:
print(f"{input_file_1} 出现元素缺失, 缺失元素的内容为: {line}")
return
count += 1
link = line.split()[2]
ext_name = link.split("/").pop()
status = "*" if line.split()[4] == "ON" else ""
desc = line.split()[6]
text = f"\n{count}、{ext_name}{status}\n描述：{desc}\n链接：{link}"
content.append(text)
# 自定义节点
content.append("\n自定义节点：")
count = 0
for line in ori_content_2:
if line == "":
continue
if len(line.split()) < 5:
print(f"{input_file_2} 出现元素缺失, 缺失元素的内容为: {line}")
return
count += 1
link = line.split()[2]
ext_name = link.split("/").pop()
status = "*" if line.split()[4] == "ON" else ""
desc = line.split()[6]
text = f"\n{count}、{ext_name}{status}\n描述：{desc}\n链接：{link}"
content.append(text)
write_content(content, output_file)
def build_invokeai_custom_node_desc(input_file: str, output_file: str) ->None:
ori_content = get_content(input_file)
content = []
content.append("InvokeAI 自定义节点说明：")
content.append("注：")
content.append("1、有些插件因为年久失修，可能会出现兼容性问题。具体介绍请通过链接查看项目的说明")
content.append("2、在名称右上角标 * 的为安装时默认勾选的插件")
count = 0
for line in ori_content:
if line == "":
continue
if len(line.split()) < 7:
print(f"{input_file} 出现元素缺失, 缺失元素的内容为: {line}")
return
count += 1
link = line.split()[2]
ext_name = link.split("/").pop()
status = "*" if line.split()[4] == "ON" else ""
desc = line.split()[6]
text = f"\n{count}、{ext_name}{status}\n描述：{desc}\n链接：{link}"
content.append(text)
write_content(content, output_file)
def build_model_list(input_file: str, output_file: str) -> None:
ori_content = get_content(input_file)
content = []
for line in ori_content:
if line == "":
continue
point = line.split()[0]
name = line.split()[-2]
status = line.split()[-1]
text = f"{point} {name} {status}"
content.append(text)
write_content(content, output_file)
def sort_point(head_point: str, file: str) -> None:
ori_content = get_content(file)
content = []
count = 0
for line in ori_content:
if line == "":
continue
count += 1
line = line.split()
line[0] = f"{head_point}{count}"
text = " ".join(line)
content.append(text)
write_content(content, file)
def dos2unix(input_file: str) -> None:
with open(input_file, "r", encoding="utf8") as file:
content = file.read()
content = content.replace("\r\n", "\n")
with open(input_file, "w", encoding="utf8", newline="\n") as file:
file.write(content)
def get_all_file(directory):
import os
file_list = []
for dirname, _, filenames in os.walk(directory):
for filename in filenames:
file_list.append(os.path.join(dirname, filename))
return file_list
def detect_uplicate(list_type: str,file: str) -> None:
content = get_content(file)
if list_type == "model":
list_column = 2
elif list_type == "extension":
list_column = 2
point_1 = 0
point_2 = 0
for i in content:
point_1 += 1
point_2 = 0
for j in content:
point_2 += 1
if i == j:
continue
if point_1 > point_2:
continue
if len(i.split()) >= list_column and len(j.split()) >= list_column and i.split()[list_column] == j.split()[list_column]:
print(f"{file} 存在重复{'模型' if list_type == 'model' else '插件'}, 在 {i.split()[0]} 和 {j.split()[0]}")
print(f"重复内容: {i.split()[list_column]}")
if __name__ == "__main__":
root_path = os.path.dirname(os.path.abspath(__file__))
os.chdir(root_path)
print(f"脚本路径: {root_path}")
args = get_args()
if args.sort:
print("排序头标签")
sort_point("__term_sd_task_pre_model_", "install/sd_webui/sd_webui_hf_model.sh")
sort_point("__term_sd_task_pre_model_", "install/sd_webui/sd_webui_ms_model.sh")
sort_point("__term_sd_task_pre_model_", "install/comfyui/comfyui_hf_model.sh")
sort_point("__term_sd_task_pre_model_", "install/comfyui/comfyui_ms_model.sh")
sort_point("__term_sd_task_pre_model_", "install/fooocus/fooocus_hf_model.sh")
sort_point("__term_sd_task_pre_model_", "install/fooocus/fooocus_ms_model.sh")
sort_point("__term_sd_task_pre_model_", "install/invokeai/invokeai_hf_model.sh")
sort_point("__term_sd_task_pre_model_", "install/invokeai/invokeai_ms_model.sh")
sort_point("__term_sd_task_pre_model_", "install/lora_scripts/lora_scripts_hf_model.sh")
sort_point("__term_sd_task_pre_model_", "install/lora_scripts/lora_scripts_ms_model.sh")
sort_point("__term_sd_task_pre_model_", "install/kohya_ss/kohya_ss_hf_model.sh")
sort_point("__term_sd_task_pre_model_", "install/kohya_ss/kohya_ss_ms_model.sh")
sort_point("__term_sd_task_pre_ext_", "install/sd_webui/sd_webui_extension.sh")
sort_point("__term_sd_task_pre_ext_", "install/comfyui/comfyui_custom_node.sh")
sort_point("__term_sd_task_pre_ext_", "install/comfyui/comfyui_extension.sh")
sort_point("__term_sd_task_pre_ext_", "install/invokeai/invokeai_custom_node.sh")
if args.build:
print("构建 Dialog 列表")
build_extension_list("install/sd_webui/sd_webui_extension.sh", "install/sd_webui/dialog_sd_webui_extension.sh")
build_extension_list("install/comfyui/comfyui_custom_node.sh", "install/comfyui/dialog_comfyui_custom_node.sh")
build_extension_list("install/comfyui/comfyui_extension.sh", "install/comfyui/dialog_comfyui_extension.sh")
build_extension_list("install/invokeai/invokeai_custom_node.sh", "install/invokeai/dialog_invokeai_custom_node.sh")
build_sd_webui_extension_desc("install/sd_webui/sd_webui_extension.sh", "help/sd_webui_extension_description.md")
build_comfyui_extension_desc("install/comfyui/comfyui_extension.sh", "install/comfyui/comfyui_custom_node.sh", "help/comfyui_extension_description.md")
build_invokeai_custom_node_desc("install/invokeai/invokeai_custom_node.sh", "help/invokeai_custom_node_description.md")
build_model_list("install/sd_webui/sd_webui_hf_model.sh", "install/sd_webui/dialog_sd_webui_hf_model.sh")
build_model_list("install/sd_webui/sd_webui_ms_model.sh", "install/sd_webui/dialog_sd_webui_ms_model.sh")
build_model_list("install/comfyui/comfyui_hf_model.sh", "install/comfyui/dialog_comfyui_hf_model.sh")
build_model_list("install/comfyui/comfyui_ms_model.sh", "install/comfyui/dialog_comfyui_ms_model.sh")
build_model_list("install/fooocus/fooocus_hf_model.sh", "install/fooocus/dialog_fooocus_hf_model.sh")
build_model_list("install/fooocus/fooocus_ms_model.sh", "install/fooocus/dialog_fooocus_ms_model.sh")
build_model_list("install/invokeai/invokeai_hf_model.sh", "install/invokeai/dialog_invokeai_hf_model.sh")
build_model_list("install/invokeai/invokeai_ms_model.sh", "install/invokeai/dialog_invokeai_ms_model.sh")
build_model_list("install/lora_scripts/lora_scripts_hf_model.sh", "install/lora_scripts/dialog_lora_scripts_hf_model.sh")
build_model_list("install/lora_scripts/lora_scripts_ms_model.sh", "install/lora_scripts/dialog_lora_scripts_ms_model.sh")
build_model_list("install/kohya_ss/kohya_ss_hf_model.sh", "install/kohya_ss/dialog_kohya_ss_hf_model.sh")
build_model_list("install/kohya_ss/kohya_ss_ms_model.sh", "install/kohya_ss/dialog_kohya_ss_ms_model.sh")
if args.fix:
print("将所有文件的换行符转换为 LF")
file_list = []
for dir in ["extra", "config", "help", "install", "modules", "task", "python_modules"]:
file_list += get_all_file(dir)
for file in file_list:
dos2unix(file)
dos2unix("term-sd.sh")
dos2unix("build.sh")
dos2unix("README.md")
if args.sort:
print("查找重复模型 / 插件列表")
detect_uplicate("model", "install/sd_webui/sd_webui_hf_model.sh")
detect_uplicate("model", "install/sd_webui/sd_webui_ms_model.sh")
detect_uplicate("model", "install/comfyui/comfyui_hf_model.sh")
detect_uplicate("model", "install/comfyui/comfyui_ms_model.sh")
detect_uplicate("model", "install/fooocus/fooocus_hf_model.sh")
detect_uplicate("model", "install/fooocus/fooocus_ms_model.sh")
detect_uplicate("model", "install/invokeai/invokeai_hf_model.sh")
detect_uplicate("model", "install/invokeai/invokeai_ms_model.sh")
detect_uplicate("model", "install/lora_scripts/lora_scripts_hf_model.sh")
detect_uplicate("model", "install/lora_scripts/lora_scripts_ms_model.sh")
detect_uplicate("model", "install/kohya_ss/kohya_ss_hf_model.sh")
detect_uplicate("model", "install/kohya_ss/kohya_ss_ms_model.sh")
detect_uplicate("extension", "install/sd_webui/sd_webui_extension.sh")
detect_uplicate("extension", "install/comfyui/comfyui_custom_node.sh")
detect_uplicate("extension", "install/comfyui/comfyui_extension.sh")
detect_uplicate("extension", "install/invokeai/invokeai_custom_node.sh")
|
2301_81996401/term-sd
|
build.py
|
Python
|
agpl-3.0
| 13,244
|
#!/bin/bash
# 该脚本用于生成 Dialog 界面所需的选项
# 生成插件列表
build_list() {
local point
local name
local describe
local count=1
local flag=0
local input_file=$1
local output_file=$2
while true; do
point=$(cat ${input_file} | awk 'NR=='${count}' {print $1}')
name=$(cat ${input_file} | awk 'NR=='${count}' {print $3}' | awk -F '/' '{print $NF}')
describe=$(cat ${input_file} | awk 'NR=='${count}' {print $5}')
if [[ -z "${point}" ]]; then
break
else
if [[ -z "$(echo ${point} | grep __term_sd_task_sys)" ]]; then
echo "${point} ${name} ${describe}" >> "${output_file}"
fi
fi
count=$(( count + 1 ))
done
}
# 生成模型列表
build_list_for_model() {
local input_file=$1
local output_file=$2
cat "${input_file}" | awk '{if ($NF!="") {print $1 " " $(NF-1) " " $NF} }' >> "${output_file}"
}
# 生成 Dialog 列表
build_dialog_list() {
local start_time=$(date +'%Y-%m-%d %H:%M:%S')
local start_time_seconds=$(date --date="${start_time}" +%s)
local input_file=$1
local output_file=$2
local end_time
local end_time_seconds
local time_span
if [[ -f "${output_file}" ]]; then
rm -f "${output_file}"
fi
echo ":: 生成 ${output_file} 中"
build_list "${input_file}" "${output_file}"
end_time=$(date +'%Y-%m-%d %H:%M:%S')
end_time_seconds=$(date --date="${end_time}" +%s)
time_span=$(( end_time_seconds - start_time_seconds )) # 计算相隔时间
echo ":: 完成, 用时: ${time_span} sec"
}
# 生成 SD WebUI 插件说明
build_dialog_list_sd_webui() {
local start_time=$(date +'%Y-%m-%d %H:%M:%S')
local start_time_seconds=$(date --date="${start_time}" +%s)
local input_file=$1
local output_file=$2
local cache_file="task/dialog_cache.sh"
local flag=0
local count=1
local end_time
local end_time_seconds
local time_span
if [[ -f "${output_file}" ]]; then
rm -f "${output_file}"
fi
echo ":: 生成 ${output_file} 中"
echo "Stable Diffusion WebUI 插件说明：" >> "${output_file}"
echo "注：" >> "${output_file}"
echo "1、有些插件因为年久失修，可能会出现兼容性问题。具体介绍请通过链接查看项目的说明" >> "${output_file}"
echo "2、在名称右上角标 * 的为安装时默认勾选的插件" >> "${output_file}"
while true; do
extension_url=$(cat "${input_file}" | awk 'NR=='${count}' {print $3}')
extension_name=$(cat "${input_file}" | awk 'NR=='${count}' {print $3}' | awk -F '/' '{print $NF}')
extension_description=$(cat "${input_file}" | awk 'NR=='${count}' {print $7}')
list_head=$(cat "${input_file}" | awk 'NR=='${count}' {print $1}')
normal_install_info=$([ "$(cat "${input_file}" | awk 'NR=='${count}' {print $5}')" = "ON" ] && echo "*")
if [[ -z "${list_head}" ]]; then
break
else
if [[ -z "$(grep __term_sd_task_sys <<< ${list_head})" ]]; then
echo "" >> "${output_file}"
echo "${count}、${extension_name}${normal_install_info}" >> "${output_file}"
echo "描述：${extension_description}" >> "${output_file}"
echo "链接：${extension_url}" >> "${output_file}"
fi
fi
count=$(( count + 1 ))
done
end_time=$(date +'%Y-%m-%d %H:%M:%S')
end_time_seconds=$(date --date="${end_time}" +%s)
time_span=$(( end_time_seconds - start_time_seconds )) # 计算相隔时间
echo ":: 完成, 用时: ${time_span} sec"
}
# 生成 ComfyUI 扩展说明
build_dialog_list_comfyui() {
local start_time=$(date +'%Y-%m-%d %H:%M:%S')
local start_time_seconds=$(date --date="${start_time}" +%s)
local input_file_1=$1
local input_file_2=$2
local output_file=$3
local count=1
local end_time
local end_time_seconds
local time_span
if [[ -f "${output_file}" ]]; then
rm -f "${output_file}"
fi
echo ":: 生成 ${output_file} 中"
echo "ComfyUI 插件 / 自定义节点说明：" >> "${output_file}"
echo "注：" >> "${output_file}"
echo "1、有些插件因为年久失修，可能会出现兼容性问题。具体介绍请通过链接查看项目的说明" >> "${output_file}"
echo "2、在名称右上角标 * 的为安装时默认勾选的插件" >> "${output_file}"
echo "" >> "${output_file}"
echo "插件：" >> "${output_file}"
while true; do
extension_url=$(cat "${input_file_1}" | awk 'NR=='${count}' {print $3}')
extension_name=$(cat "${input_file_1}" | awk 'NR=='${count}' {print $3}' | awk -F '/' '{print $NF}')
extension_description=$(cat "${input_file_1}" | awk 'NR=='${count}' {print $7}')
list_head=$(cat "${input_file_1}" | awk 'NR=='${count}' {print $1}')
normal_install_info=$([ "$(cat "${input_file_1}" | awk 'NR=='${count}' {print $5}')" = "ON" ] && echo "*")
if [[ -z "${list_head}" ]]; then
break
else
if [ -z "$(echo "${list_head}" | grep __term_sd_task_sys)" ]; then
echo "" >> "${output_file}"
echo "${count}、${extension_name}${normal_install_info}" >> "${output_file}"
echo "描述：${extension_description}" >> "${output_file}"
echo "链接：${extension_url}" >> "${output_file}"
fi
fi
count=$(( count + 1 ))
done
echo "" >> "${output_file}"
echo "自定义节点：" >> "${output_file}"
count=1
while true; do
extension_url=$(cat "${input_file_2}" | awk 'NR=='${count}' {print $3}')
extension_name=$(cat "${input_file_2}" | awk 'NR=='${count}' {print $3}' | awk -F '/' '{print $NF}')
extension_description=$(cat "${input_file_2}" | awk 'NR=='${count}' {print $7}')
list_head=$(cat "${input_file_2}" | awk 'NR=='${count}' {print $1}')
normal_install_info=$([ "$(cat "${input_file_2}" | awk 'NR=='${count}' {print $5}')" = "ON" ] && echo "*")
if [[ -z "${list_head}" ]]; then
break
else
if [[ -z "$(echo "${list_head}" | grep __term_sd_task_sys)" ]]; then
echo "" >> "${output_file}"
echo "$count、${extension_name}${normal_install_info}" >> "${output_file}"
echo "描述：${extension_description}" >> "${output_file}"
echo "链接：${extension_url}" >> "${output_file}"
fi
fi
count=$(( count + 1 ))
done
end_time=$(date +'%Y-%m-%d %H:%M:%S')
end_time_seconds=$(date --date="${end_time}" +%s)
time_span=$(( end_time_seconds - start_time_seconds )) # 计算相隔时间
echo ":: 完成, 用时: ${time_span} sec"
}
# 生成 InvokeAI 自定义节点说明
build_dialog_list_invokeai() {
local start_time=$(date +'%Y-%m-%d %H:%M:%S')
local start_time_seconds=$(date --date="${start_time}" +%s)
local input_file=$1
local output_file=$2
local cache_file="task/dialog_cache.sh"
local flag=0
local count=1
local end_time
local end_time_seconds
local time_span
if [[ -f "${output_file}" ]]; then
rm -f "${output_file}"
fi
echo ":: 生成 ${output_file} 中"
echo "InvokeAI 自定义节点说明：" >> "${output_file}"
echo "注：" >> "${output_file}"
echo "1、有些插件因为年久失修，可能会出现兼容性问题。具体介绍请通过链接查看项目的说明" >> "${output_file}"
echo "2、在名称右上角标 * 的为安装时默认勾选的插件" >> "${output_file}"
while true; do
extension_url=$(cat "${input_file}" | awk 'NR=='${count}' {print $3}')
extension_name=$(cat "${input_file}" | awk 'NR=='${count}' {print $3}' | awk -F '/' '{print $NF}')
extension_description=$(cat "${input_file}" | awk 'NR=='${count}' {print $7}')
list_head=$(cat "${input_file}" | awk 'NR=='${count}' {print $1}')
normal_install_info=$([ "$(cat "${input_file}" | awk 'NR=='${count}' {print $5}')" = "ON" ] && echo "*")
if [[ -z "${list_head}" ]]; then
break
else
if [[ -z "$(grep __term_sd_task_sys <<< ${list_head})" ]]; then
echo "" >> "${output_file}"
echo "${count}、${extension_name}${normal_install_info}" >> "${output_file}"
echo "描述：${extension_description}" >> "${output_file}"
echo "链接：${extension_url}" >> "${output_file}"
fi
fi
count=$(( count + 1 ))
done
end_time=$(date +'%Y-%m-%d %H:%M:%S')
end_time_seconds=$(date --date="${end_time}" +%s)
time_span=$(( end_time_seconds - start_time_seconds )) # 计算相隔时间
echo ":: 完成, 用时: ${time_span} sec"
}
# 生成模型选择列表
build_dialog_list_model() {
local start_time=$(date +'%Y-%m-%d %H:%M:%S')
local start_time_seconds=$(date --date="${start_time}" +%s)
local input_file=$1
local output_file=$2
local end_time
local end_time_seconds
local time_span
if [[ -f "${output_file}" ]]; then
rm -f "${output_file}"
fi
echo ":: 生成 ${output_file} 中"
build_list_for_model "${input_file}" "${output_file}"
end_time=$(date +'%Y-%m-%d %H:%M:%S')
end_time_seconds=$(date --date="${end_time}" +%s)
time_span=$(( end_time_seconds - start_time_seconds )) # 计算相隔时间
echo ":: 完成, 用时: ${time_span} sec"
}
# 从列表截取命令
get_task_cmd() {
local task_cmd_sign
local task_cmd
task_cmd_sign=$(echo $@ | awk '{print $1}')
task_cmd=$(echo $@ | awk '{sub("'$task_cmd_sign' ","")}1')
echo "${task_cmd}"
}
# 重排序标签
sort_head_point() {
local cmd_sum
local cmd_point
local input_file=$2
local input_file_name=$(basename "${input_file}")
local start_time=$(date +'%Y-%m-%d %H:%M:%S')
local start_time_seconds=$(date --date="${start_time}" +%s)
local head_point=$1
local end_time
local end_time_seconds
local time_span
echo ":: 生成 ${input_file} 中"
mv "${input_file}" task/
cmd_sum=$(( $(cat "task/${input_file_name}" | wc -l) + 1)) # 统计命令行数
for (( cmd_point=1; cmd_point <= cmd_sum; cmd_point++ )); do
install_cmd=$(get_task_cmd $(cat "task/${input_file_name}" | awk 'NR=='${cmd_point}'{print $0}'))
if [[ ! -z "${install_cmd}" ]]; then
echo "${head_point}${cmd_point} ${install_cmd}" >> "${input_file}"
fi
done
rm "task/${input_file_name}"
end_time=$(date +'%Y-%m-%d %H:%M:%S')
end_time_seconds=$(date --date="${end_time}" +%s)
time_span=$(( end_time_seconds - start_time_seconds )) # 计算相隔时间
echo ":: 完成, 用时: ${time_span} sec"
}
# 链接查重
detect_uplicate() {
local list_type=$1
local file_path=$2
local cmd_sum=$(( $(cat "${file_path}" | wc -l) + 1)) # 统计命令行数
local start_time=$(date +'%Y-%m-%d %H:%M:%S')
local start_time_seconds=$(date --date="${start_time}" +%s)
local end_time
local end_time_seconds
local time_span
local flag=0
local install_cmd_1
local install_cmd_2
if [[ "${list_type}" == "model" ]]; then
list_column=3
type_name="模型链接"
elif [[ "${list_type}" == "extension" ]]; then
list_column=4
type_name="扩展链接"
fi
echo ":: 检测 $file_path 中重复的${type_name}中"
for ((i = 1; i <= cmd_sum; i++)); do
if [[ "${list_type}" == "model" ]]; then
install_cmd_1=$(cat "${file_path}" | awk 'NR=='${i}' { print $3 }')
elif [[ "${list_type}" == "extension" ]]; then
install_cmd_1=$(cat "${file_path}" | awk 'NR=='${i}' { print $4 }')
fi
for (( j = i; j <= cmd_sum; j++ )); do
[[ "${i}" = "${j}" ]] && continue
if [[ "${list_type}" == "model" ]]; then
install_cmd_2=$(cat "${file_path}" | awk 'NR=='${j}'{print $3}')
elif [[ "${list_type}" = "extension" ]]; then
install_cmd_2=$(cat "${file_path}" | awk 'NR=='${j}'{print $4}')
fi
if [[ "${install_cmd_1}" == "${install_cmd_2}" ]]; then
echo ":: 检测到重复${type_name}, 出现在第 ${i} 行和第 ${j} 行"
flag=1
fi
done
done
end_time=$(date +'%Y-%m-%d %H:%M:%S')
end_time_seconds=$(date --date="${end_time}" +%s)
time_span=$(( end_time_seconds - start_time_seconds )) # 计算相隔时间
if [[ "${flag}" == 0 ]]; then
echo ":: 无重复${type_name}"
else
echo ":: 出现重复${type_name}, 待解决"
fi
echo ":: 完成, 用时: ${time_span} sec"
}
#############################
if [[ ! -d "modules" ]] || [[ ! -d "install" ]] || [[ ! -d "task" ]] || [[ ! -d "help" ]]; then
echo ":: 目录错误"
exit 1
elif [[ ! "$(dirname "$0")" = "." ]]; then
echo ":: 目录错误"
exit 1
fi
if [[ ! -z "$@" ]]; then
echo "----------build----------"
start_time_sum=$(date +'%Y-%m-%d %H:%M:%S')
start_time_seconds_sum=$(date --date="$start_time_sum" +%s)
for n in $@ ;do
case "${n}" in
--fix)
echo ":: 格式转换"
list=$(find extra config help install modules task python_modules)
for i in ${list}; do
if [[ -f "${i}" ]]; then
dos2unix "${i}"
fi
done
dos2unix term-sd.sh
dos2unix build.sh
dos2unix README.md
;;
--build)
echo ":: 构建列表"
build_dialog_list install/sd_webui/sd_webui_extension.sh install/sd_webui/dialog_sd_webui_extension.sh
build_dialog_list install/comfyui/comfyui_custom_node.sh install/comfyui/dialog_comfyui_custom_node.sh
build_dialog_list install/comfyui/comfyui_extension.sh install/comfyui/dialog_comfyui_extension.sh
build_dialog_list install/invokeai/invokeai_custom_node.sh install/invokeai/dialog_invokeai_custom_node.sh
build_dialog_list_sd_webui install/sd_webui/sd_webui_extension.sh help/sd_webui_extension_description.md
build_dialog_list_comfyui install/comfyui/comfyui_extension.sh install/comfyui/comfyui_custom_node.sh help/comfyui_extension_description.md
build_dialog_list_invokeai install/invokeai/invokeai_custom_node.sh help/invokeai_custom_node_description.md
build_dialog_list_model install/sd_webui/sd_webui_hf_model.sh install/sd_webui/dialog_sd_webui_hf_model.sh
build_dialog_list_model install/sd_webui/sd_webui_ms_model.sh install/sd_webui/dialog_sd_webui_ms_model.sh
build_dialog_list_model install/comfyui/comfyui_hf_model.sh install/comfyui/dialog_comfyui_hf_model.sh
build_dialog_list_model install/comfyui/comfyui_ms_model.sh install/comfyui/dialog_comfyui_ms_model.sh
build_dialog_list_model install/fooocus/fooocus_hf_model.sh install/fooocus/dialog_fooocus_hf_model.sh
build_dialog_list_model install/fooocus/fooocus_ms_model.sh install/fooocus/dialog_fooocus_ms_model.sh
build_dialog_list_model install/invokeai/invokeai_hf_model.sh install/invokeai/dialog_invokeai_hf_model.sh
build_dialog_list_model install/invokeai/invokeai_ms_model.sh install/invokeai/dialog_invokeai_ms_model.sh
build_dialog_list_model install/lora_scripts/lora_scripts_hf_model.sh install/lora_scripts/dialog_lora_scripts_hf_model.sh
build_dialog_list_model install/lora_scripts/lora_scripts_ms_model.sh install/lora_scripts/dialog_lora_scripts_ms_model.sh
build_dialog_list_model install/kohya_ss/kohya_ss_hf_model.sh install/kohya_ss/dialog_kohya_ss_hf_model.sh
build_dialog_list_model install/kohya_ss/kohya_ss_ms_model.sh install/kohya_ss/dialog_kohya_ss_ms_model.sh
;;
--sort)
echo ":: 头标签排序"
sort_head_point __term_sd_task_pre_model_ install/sd_webui/sd_webui_hf_model.sh
sort_head_point __term_sd_task_pre_model_ install/sd_webui/sd_webui_ms_model.sh
sort_head_point __term_sd_task_pre_model_ install/comfyui/comfyui_hf_model.sh
sort_head_point __term_sd_task_pre_model_ install/comfyui/comfyui_ms_model.sh
sort_head_point __term_sd_task_pre_model_ install/fooocus/fooocus_hf_model.sh
sort_head_point __term_sd_task_pre_model_ install/fooocus/fooocus_ms_model.sh
sort_head_point __term_sd_task_pre_model_ install/invokeai/invokeai_hf_model.sh
sort_head_point __term_sd_task_pre_model_ install/invokeai/invokeai_ms_model.sh
sort_head_point __term_sd_task_pre_model_ install/lora_scripts/lora_scripts_hf_model.sh
sort_head_point __term_sd_task_pre_model_ install/lora_scripts/lora_scripts_ms_model.sh
sort_head_point __term_sd_task_pre_model_ install/kohya_ss/kohya_ss_hf_model.sh
sort_head_point __term_sd_task_pre_model_ install/kohya_ss/kohya_ss_ms_model.sh
sort_head_point __term_sd_task_pre_ext_ install/sd_webui/sd_webui_extension.sh
sort_head_point __term_sd_task_pre_ext_ install/comfyui/comfyui_custom_node.sh
sort_head_point __term_sd_task_pre_ext_ install/comfyui/comfyui_extension.sh
sort_head_point __term_sd_task_pre_ext_ install/invokeai/invokeai_custom_node.sh
;;
--check)
echo ":: 重复链接检测"
detect_uplicate model install/sd_webui/sd_webui_hf_model.sh
detect_uplicate model install/sd_webui/sd_webui_ms_model.sh
detect_uplicate model install/comfyui/comfyui_hf_model.sh
detect_uplicate model install/comfyui/comfyui_ms_model.sh
detect_uplicate model install/fooocus/fooocus_hf_model.sh
detect_uplicate model install/fooocus/fooocus_ms_model.sh
detect_uplicate model install/invokeai/invokeai_hf_model.sh
detect_uplicate model install/invokeai/invokeai_ms_model.sh
detect_uplicate model install/lora_scripts/lora_scripts_hf_model.sh
detect_uplicate model install/lora_scripts/lora_scripts_ms_model.sh
detect_uplicate model install/kohya_ss/kohya_ss_hf_model.sh
detect_uplicate model install/kohya_ss/kohya_ss_ms_model.sh
detect_uplicate extension install/sd_webui/sd_webui_extension.sh
detect_uplicate extension install/comfyui/comfyui_custom_node.sh
detect_uplicate extension install/comfyui/comfyui_extension.sh
detect_uplicate extension install/invokeai/invokeai_custom_node.sh
;;
*)
echo ":: 未知参数: \"${n}\""
;;
esac
done
echo "----------done----------"
end_time_sum=$(date +'%Y-%m-%d %H:%M:%S')
end_time_seconds_sum=$(date --date="${end_time_sum}" +%s)
time_span_sum=$(( end_time_seconds_sum - start_time_seconds_sum )) # 计算相隔时间
echo ":: 总共用时: ${time_span_sum} sec"
else
echo ":: 使用："
echo "build.sh [--fix] [--build] [--sort] [--check]"
echo ":: 未指定操作"
fi
|
2301_81996401/term-sd
|
build.sh
|
Shell
|
agpl-3.0
| 19,736
|
#!/bin/bash
. "${START_PATH}"/term-sd/modules/term_sd_python_cmd.sh
. "${START_PATH}"/term-sd/modules/term_sd_git.sh
term_sd_echo "开始清理缓存中"
if [[ -d "${SD_WEBUI_ROOT_PATH}" ]]; then
term_sd_echo "清理 Stable-Diffusion—WebUI 缓存中"
git -C "${SD_WEBUI_ROOT_PATH}" gc
for i in "${SD_WEBUI_ROOT_PATH}"/repositories/*
do
if is_git_repo "${i}"; then
term_sd_echo "清理 $(basename "${i}") 组件缓存中"
git -C "${i}" gc
fi
done
term_sd_echo "清理 Stable-Diffusion—WebUI 插件缓存中"
for i in "${SD_WEBUI_ROOT_PATH}"/extensions/*; do
if is_git_repo "${i}"; then
term_sd_echo "清理 $(basename "${i}") 插件缓存中"
git -C "${i}" gc
fi
done
term_sd_echo "清理 Stable-Diffusion—WebUI 缓存完成"
fi
if [[ -d "${COMFYUI_ROOT_PATH}" ]]; then
term_sd_echo "清理 ComfyUI 缓存中"
git -C "${COMFYUI_ROOT_PATH}" gc
term_sd_echo "清理 ComfyUI 插件缓存中"
for i in "${COMFYUI_ROOT_PATH}"/web/extensions/*; do
if is_git_repo "${i}"; then
term_sd_echo "清理 $(basename "${i}") 插件缓存中"
git -C "${i}" gc
fi
done
term_sd_echo "清理 ComfyUI 自定义节点缓存中"
for i in "${COMFYUI_ROOT_PATH}"/custom_nodes/*; do
if is_git_repo "${i}"; then
term_sd_echo "清理 $(basename "${i}") 自定义节点缓存中"
git -C "${i}" gc
fi
done
term_sd_echo "清理 ComfyUI 缓存完成"
fi
if [[ -d "${FOOOCUS_ROOT_PATH}" ]]; then
term_sd_echo "清理 Fooocus 缓存中"
git -C "${FOOOCUS_ROOT_PATH}" gc
term_sd_echo "清理 Fooocus 缓存完成"
fi
if [[ -d "${LORA_SCRIPTS_ROOT_PATH}" ]]; then
term_sd_echo "清理 lora-scrips 缓存中"
git -C "${LORA_SCRIPTS_ROOT_PATH}" gc
term_sd_echo "清理 lora-scrips 缓存完成"
fi
if [[ -d "${KOHYA_SS_ROOT_PATH}" ]]; then
term_sd_echo "清理 kohya_ss 缓存中"
git -C "${KOHYA_SS_ROOT_PATH}" gc
term_sd_echo "清理 kohya_ss 缓存完成"
fi
term_sd_echo "清理 Term-SD 缓存中"
git -C "${START_PATH}"/term-sd gc
term_sd_echo "清理 Term-SD 缓存完成"
term_sd_echo "清理 Pip 缓存中"
term_sd_pip cache purge
term_sd_uv cache clean
term_sd_echo "清理 Pip 缓存完成"
term_sd_echo "缓存清理结束"
|
2301_81996401/term-sd
|
extra/clean-cache.sh
|
Shell
|
agpl-3.0
| 2,380
|
#!/bin/bash
. "${START_PATH}"/term-sd/modules/install_prepare.sh
. "${START_PATH}"/term-sd/modules/get_modelscope_model.sh
. "${START_PATH}"/term-sd/modules/term_sd_git.sh
. "${START_PATH}"/term-sd/modules/term_sd_task_manager.sh
. "${START_PATH}"/term-sd/modules/term_sd_manager.sh
. "${START_PATH}"/term-sd/modules/term_sd_proxy.sh
. "${START_PATH}"/term-sd/modules/term_sd_try.sh
if [[ ! -d "${COMFYUI_ROOT_PATH}" ]]; then
term_sd_echo "未安装 ComfyUI"
else
rm -f "${START_PATH}/term-sd/task/comfyui_install_extension.sh"
download_mirror_select # 下载镜像源选择
# 插件选择
COMFYUI_EXTENSION_INSTALL_LIST=$(dialog --erase-on-exit --notags \
--title "ComfyUI 安装" \
--backtitle "ComfyUI 插件安装选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要安装的 ComfyUI 插件" \
$(get_dialog_size_menu) \
$(cat "${START_PATH}/term-sd/install/comfyui/dialog_comfyui_extension.sh" | awk '{print $1 " " $2 " OFF"}') \
3>&1 1>&2 2>&3)
# 自定义节点选择
COMFYUI_CUSTOM_NODE_INSTALL_LIST=$(dialog --erase-on-exit --notags \
--title "ComfyUI 安装" \
--backtitle "ComfyUI 自定义节点安装选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要安装的 ComfyUI 自定义节点" \
$(get_dialog_size_menu) \
$(cat "${START_PATH}/term-sd/install/comfyui/dialog_comfyui_custom_node.sh" | awk '{print $1 " " $2 " OFF"}') \
3>&1 1>&2 2>&3)
if is_use_modelscope_src; then
comfyui_custom_node_model_list_file="comfyui_custom_node_ms_model.sh"
else
comfyui_custom_node_model_list_file="comfyui_custom_node_hf_model.sh"
fi
term_sd_echo "生成模型选择列表中"
# 查找插件对应模型的编号
for i in ${COMFYUI_CUSTOM_NODE_INSTALL_LIST}; do
comfyui_custom_node_model_list="${comfyui_custom_node_model_list} $(cat "${START_PATH}"/term-sd/install/comfyui/${comfyui_custom_node_model_list_file} | grep -w ${i} | awk 'NR==1{if ($NF!="") {print $1 " " $(NF-1) " " $NF} }' | awk '{sub($NF,"OFF")}1')"
done
# 模型选择
COMFYUI_DOWNLOAD_MODEL_LIST=$(dialog --erase-on-exit --notags \
--title "ComfyUI 安装" \
--backtitle "ComfyUI 模型下载选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要下载的 ComfyUI 扩展模型" \
$(get_dialog_size_menu) \
"_null_" "=====扩展模型选择=====" OFF \
${comfyui_custom_node_model_list} \
3>&1 1>&2 2>&3)
# 安装确认
if term_sd_install_confirm "是否安装 ComfyUI 插件 / 自定义节点 ?"; then
term_sd_echo "生成任务队列"
touch "${START_PATH}/term-sd/task/comfyui_install_extension.sh"
# 插件
if [[ ! -z "${COMFYUI_EXTENSION_INSTALL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"安装插件中\"" >> "${START_PATH}/term-sd/task/comfyui_install_extension.sh"
for i in ${COMFYUI_EXTENSION_INSTALL_LIST} ;do
cat "${START_PATH}/term-sd/install/comfyui/comfyui_extension.sh" | grep -w ${i} | awk '{sub(" ON "," ") ; sub(" OFF "," ")}1' >> "${START_PATH}/term-sd/task/comfyui_install_extension.sh" # 插件
done
fi
term_sd_add_blank_line "${START_PATH}"/term-sd/task/comfyui_install_extension.sh
# 自定义节点
if [[ ! -z "${COMFYUI_CUSTOM_NODE_INSTALL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"安装自定义节点中\"" >> "${START_PATH}/term-sd/task/comfyui_install_extension.sh"
for i in $COMFYUI_CUSTOM_NODE_INSTALL_LIST ;do
cat "${START_PATH}/term-sd/install/comfyui/comfyui_custom_node.sh" | grep -w ${i} | awk '{sub(" ON "," ") ; sub(" OFF "," ")}1' >> "${START_PATH}/term-sd/task/comfyui_install_extension.sh" # 插件
done
fi
# 扩展的模型
if [[ ! -z "${COMFYUI_DOWNLOAD_MODEL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"安装自定义节点中\"" >> "${START_PATH}/term-sd/task/comfyui_install_extension.sh"
if is_use_modelscope_src; then
for i in ${COMFYUI_DOWNLOAD_MODEL_LIST} ;do
echo "__term_sd_task_sys term_sd_tmp_disable_proxy" >> "${START_PATH}/term-sd/task/comfyui_install_extension.sh"
cat "${START_PATH}/term-sd/install/comfyui/comfyui_custom_node_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/comfyui_install_extension.sh" # 自定义节点所需的模型
done
else
for i in $COMFYUI_DOWNLOAD_MODEL_LIST ;do
cat "${START_PATH}/term-sd/install/comfyui/comfyui_custom_node_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/comfyui_install_extension.sh" # 自定义节点所需的模型
done
fi
fi
term_sd_echo "任务队列生成完成"
term_sd_echo "开始下载 ComfyUI 插件 / 自定义节点"
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/comfyui_install_extension.sh" | wc -l) + 1 )) # 统计命令行数
for ((cmd_point=1;cmd_point<=cmd_sum;cmd_point++))
do
term_sd_echo "ComfyUI 安装进度: [$cmd_point/$cmd_sum]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/comfyui_install_extension.sh" ${cmd_point}
done
term_sd_tmp_enable_proxy # 恢复代理
term_sd_echo "ComfyUI 插件 / 自定义节点下载结束"
rm -f "${START_PATH}/term-sd/task/comfyui_install_extension.sh" # 删除任务文件
else
term_sd_echo "取消下载 ComfyUI 插件 / 自定义节点"
fi
fi
|
2301_81996401/term-sd
|
extra/download-comfyui-extension.sh
|
Shell
|
agpl-3.0
| 5,770
|
#!/bin/bash
. "${START_PATH}"/term-sd/modules/term_sd_try.sh
. "${START_PATH}"/term-sd/modules/term_sd_manager.sh
# 下载源选择
download_hanamizuki_resource_select() {
while true; do
term_sd_echo "请选择绘世启动器下载源"
term_sd_echo "1、Github 源 (速度可能比较慢)"
term_sd_echo "2、Gitee 源"
term_sd_echo "3、退出"
case "$(term_sd_read)" in
1)
term_sd_echo "选择 Github 源"
download_hanamizuki_resource="https://github.com/licyk/term-sd/releases/download/archive/hanamizuki.exe"
return 0
;;
2)
term_sd_echo "选择 Gitee 源"
download_hanamizuki_resource="https://gitee.com/licyk/term-sd/releases/download/archive/hanamizuki.exe"
return 0
;;
3)
return 1
;;
*)
term_sd_echo "输入有误, 请重试"
;;
esac
done
}
# 绘世启动器下载
download_hanamizuki() {
aria2_download ${download_hanamizuki_resource} term-sd/task "绘世.exe"
if [[ "$?" == 0 ]]; then
install_hanamizuki "$SD_WEBUI_ROOT_PATH" "Stable-Diffusion-WebUI"
install_hanamizuki "$COMFYUI_ROOT_PATH" "ComfyUI"
install_hanamizuki "$FOOOCUS_ROOT_PATH" "Fooocus"
install_hanamizuki "$LORA_SCRIPTS_ROOT_PATH" "lora-scripts"
rm -f "term-sd/task/绘世.exe"
else
term_sd_echo "下载失败"
fi
}
# 将绘世启动器复制到 AI 软件目录中
install_hanamizuki() {
local install_path=$1
local sd_name=$2
if [[ -d "${install_path}" ]]; then
if [[ -f "${install_path}"/*绘世*.exe ]] \
|| [[ -f "${install_path}"/A*.exe ]] \
|| [[ -f "${install_path}"/*启动器.exe ]]; then
term_sd_echo "绘世启动器已存在于 ${sd_name} 文件夹中"
else
term_sd_echo "将绘世启动器复制到 ${sd_name} 文件夹: ${install_path}"
cp -f "term-sd/task/绘世.exe" "${install_path}"
fi
else
term_sd_echo "${sd_name} 未安装"
fi
}
#############################
if is_windows_platform; then
if download_hanamizuki_resource_select; then
download_hanamizuki
else
term_sd_echo "取消下载绘世启动器"
fi
else
term_sd_echo "检测到系统不是 Windows 系统, 无法使用绘世启动器"
fi
|
2301_81996401/term-sd
|
extra/download-hanamizuki.sh
|
Shell
|
agpl-3.0
| 2,498
|
#!/bin/bash
. "${START_PATH}"/term-sd/modules/install_prepare.sh
. "${START_PATH}"/term-sd/modules/get_modelscope_model.sh
. "${START_PATH}"/term-sd/modules/term_sd_git.sh
. "${START_PATH}"/term-sd/modules/term_sd_task_manager.sh
. "${START_PATH}"/term-sd/modules/term_sd_manager.sh
. "${START_PATH}"/term-sd/modules/term_sd_proxy.sh
. "${START_PATH}"/term-sd/modules/term_sd_try.sh
if [[ ! -d "${INVOKEAI_ROOT_PATH}" ]]; then
term_sd_echo "未安装 InvokeAI"
else
# 删除 InvokeAI 自定义节点安装任务文件
rm -f "${START_PATH}/term-sd/task/invokeai_install_custom_node.sh"
download_mirror_select # 下载镜像源选择
# 自定义节点选择
INVOKEAI_INSTALL_CUSTOM_NODE_LIST=$(dialog --erase-on-exit --notags \
--title "InvokeAI 安装" \
--backtitle "InvokeAI 自定义节点安装选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要安装的 InvokeAI 自定义节点" \
$(get_dialog_size_menu) \
$(cat "${START_PATH}/term-sd/install/invokeai/dialog_invokeai_custom_node.sh" | awk '{print $1 " " $2 " OFF"}') \
3>&1 1>&2 2>&3)
# 自定义节点模型列表选择
if is_use_modelscope_src; then
invokeai_custom_node_model_list_file="invokeai_custom_node_ms_model.sh"
else
invokeai_custom_node_model_list_file="invokeai_custom_node_hf_model.sh"
fi
term_sd_echo "生成模型选择列表中"
# 查找自定义节点对应模型的编号
for i in ${INVOKEAI_INSTALL_CUSTOM_NODE_LIST}; do
model_list="${model_list} $(cat "${START_PATH}"/term-sd/install/invokeai/${invokeai_custom_node_model_list_file} | grep -w ${i} | awk 'NR==1{if ($NF!="") {print $1 " " $(NF-1) " " $NF} }' | awk '{sub($NF,"OFF")}1')"
done
# 模型选择
INVOKEAI_DOWNLOAD_MODEL_LIST=$(dialog --erase-on-exit --notags \
--title "InvokeAI 安装" \
--backtitle "InvokeAI 自定义节点模型下载选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要下载的 InvokeAI 自定义节点模型" \
$(get_dialog_size_menu) \
"_null_" "=====自定义节点模型选择=====" OFF \
${model_list} \
3>&1 1>&2 2>&3)
# 安装确认
if term_sd_install_confirm "是否安装 InvokeAI 自定义节点 ?"; then
term_sd_echo "生成任务队列"
touch "${START_PATH}/term-sd/task/invokeai_install_custom_node.sh"
# 自定义节点
if [[ ! -z "${INVOKEAI_INSTALL_CUSTOM_NODE_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"下载自定义节点中\"" >> "${START_PATH}/term-sd/task/invokeai_install_custom_node.sh"
for i in ${INVOKEAI_INSTALL_CUSTOM_NODE_LIST}; do
cat "${START_PATH}/term-sd/install/invokeai/invokeai_custom_node.sh" | grep -w ${i} | awk '{sub(" ON "," ") ; sub(" OFF "," ")}1' >> "${START_PATH}/term-sd/task/invokeai_install_custom_node.sh" # 自定义节点
done
fi
# 自定义节点模型
if [[ ! -z "${INVOKEAI_DOWNLOAD_MODEL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"下载模型中\"" >> "${START_PATH}/term-sd/task/invokeai_install_custom_node.sh"
if is_use_modelscope_src; then
echo "__term_sd_task_sys term_sd_tmp_disable_proxy" >> "${START_PATH}/term-sd/task/invokeai_install_custom_node.sh"
for i in ${INVOKEAI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/invokeai/invokeai_custom_node_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/invokeai_install_custom_node.sh" # 自定义节点所需的模型
done
else
for i in ${INVOKEAI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/invokeai/invokeai_custom_node_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/invokeai_install_custom_node.sh" # 自定义节点所需的模型
done
fi
fi
term_sd_echo "任务队列生成完成"
term_sd_echo "开始下载 InvokeAI 自定义节点"
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/invokeai_install_custom_node.sh" | wc -l) + 1 )) # 统计命令行数
for (( cmd_point=1; cmd_point<=cmd_sum; cmd_point++ )); do
term_sd_echo "InvokeAI 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/invokeai_install_custom_node.sh" "${cmd_point}"
done
term_sd_tmp_enable_proxy # 恢复代理
term_sd_echo "InvokeAI 自定义节点下载结束"
rm -f "${START_PATH}/term-sd/task/invokeai_install_custom_node.sh" # 删除任务文件
else
term_sd_echo "取消下载 InvokeAI 自定义节点"
fi
fi
|
2301_81996401/term-sd
|
extra/download-invokeai-extension.sh
|
Shell
|
agpl-3.0
| 4,827
|
#!/bin/bash
# 加载模块
. "${START_PATH}"/term-sd/modules/term_sd_manager.sh
. "${START_PATH}"/term-sd/modules/term_sd_task_manager.sh
. "${START_PATH}"/term-sd/modules/get_modelscope_model.sh
. "${START_PATH}"/term-sd/modules/install_prepare.sh
. "${START_PATH}"/term-sd/modules/term_sd_proxy.sh
. "${START_PATH}"/term-sd/modules/term_sd_try.sh
# ai软件选择
sd_model_download_select() {
local dialog_arg
local file_manager_select
while true; do
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Term-SD" \
--backtitle "Term-SD 模型下载" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择需要下载模型的 AI 软件" \
$(get_dialog_size_menu) \
"1" "> Stable-Diffusion-WebUI" \
"2" "> ComfyUI" \
"3" "> InvokeAI" \
"4" "> Fooocus" \
"5" "> lora-scripts" \
"6" "> kohya_ss" \
"7" "> 退出" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
file_manager_select="stable-diffusion-webui"
;;
2)
file_manager_select="ComfyUI"
;;
3)
file_manager_select="InvokeAI"
;;
4)
file_manager_select="Fooocus"
;;
5)
file_manager_select="lora-scripts"
;;
6)
file_manager_select="kohya_ss"
;;
7)
break
;;
*)
break
;;
esac
if is_sd_folder_exist "${file_manager_select}"; then
model_download_interface "${file_manager_select}"
break
else
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "Term-SD 模型下载" \
--ok-label "确认" \
--msgbox "${file_manager_select} 未安装" \
$(get_dialog_size)
fi
done
}
# 模型选择和下载
model_download_interface() {
local dialog_arg
local cmd_sum
local cmd_point
local install_cmd
local name=$@
download_mirror_select # 下载镜像源选择
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Term-SD" \
--backtitle "${name} 模型下载选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要下载的 ${name} 模型" \
$(get_dialog_size_menu) \
$(cat "${START_PATH}"/term-sd/install/$(get_model_list_file_path ${name} dialog) | awk '{print $1 " " $2 " OFF"}') \
3>&1 1>&2 2>&3)
if term_sd_install_confirm "是否下载 ${name} 模型 ?"; then
term_sd_echo "生成任务队列"
rm -f "${START_PATH}/term-sd/task/model_download.sh" # 删除上次未清除的任务列表
# 代理
if is_use_modelscope_src; then
echo "__term_sd_task_sys term_sd_tmp_disable_proxy" >> "${START_PATH}/term-sd/task/model_download.sh"
fi
# 模型
for i in ${dialog_arg}; do
cat "${START_PATH}"/term-sd/install/"$(get_model_list_file_path ${name})" | grep -w ${i} >> "${START_PATH}/term-sd/task/model_download.sh"
done
term_sd_echo "任务队列生成完成"
term_sd_echo "开始下载 ${name} 模型"
cmd_sum=$(cat "${START_PATH}/term-sd/task/model_download.sh" | wc -l)
for (( cmd_point=1; cmd_point<=cmd_sum; cmd_point++ )); do
term_sd_echo "${name} 模型下载进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/model_download.sh" "${cmd_point}"
done
rm -f "${START_PATH}/term-sd/task/model_download.sh" # 删除任务文件
term_sd_echo "${name} 模型下载结束"
else
term_sd_echo "取消下载模型"
fi
}
# 获取模型列表路径
get_model_list_file_path() {
local sd_name
local download_source_name
local name=$1
local type=$2
case ${name} in
stable-diffusion-webui)
sd_name="sd_webui"
;;
ComfyUI)
sd_name="comfyui"
;;
InvokeAI)
sd_name="invokeai"
;;
Fooocus)
sd_name="fooocus"
;;
lora-scripts)
sd_name="lora_scripts"
;;
kohya_ss)
sd_name="kohya_ss"
;;
esac
if is_use_modelscope_src; then
download_source_name="ms"
else
download_source_name="hf"
fi
if [[ "${type}" == "dialog" ]]; then
echo "${sd_name}/dialog_${sd_name}_${download_source_name}_model.sh"
else
echo "${sd_name}/${sd_name}_${download_source_name}_model.sh"
fi
}
# 检测文件夹存在
is_sd_folder_exist() {
case $@ in
stable-diffusion-webui)
[[ -d "${SD_WEBUI_ROOT_PATH}" ]] && return 0 || return 1
;;
ComfyUI)
[[ -d "${COMFYUI_ROOT_PATH}" ]] && return 0 || return 1
;;
InvokeAI)
[[ -d "${INVOKEAI_ROOT_PATH}" ]] && return 0 || return 1
;;
Fooocus)
[[ -d "${FOOOCUS_ROOT_PATH}" ]] && return 0 || return 1
;;
lora-scripts)
[[ -d "${LORA_SCRIPTS_ROOT_PATH}" ]] && return 0 || return 1
;;
kohya_ss)
[[ -d "${KOHYA_SS_ROOT_PATH}" ]] && return 0 || return 1
;;
esac
}
#############################
sd_model_download_select
|
2301_81996401/term-sd
|
extra/download-model.sh
|
Shell
|
agpl-3.0
| 5,645
|
#!/bin/bash
. "${START_PATH}"/term-sd/modules/install_prepare.sh
. "${START_PATH}"/term-sd/modules/get_modelscope_model.sh
. "${START_PATH}"/term-sd/modules/term_sd_git.sh
. "${START_PATH}"/term-sd/modules/term_sd_task_manager.sh
. "${START_PATH}"/term-sd/modules/term_sd_manager.sh
. "${START_PATH}"/term-sd/modules/term_sd_proxy.sh
. "${START_PATH}"/term-sd/modules/term_sd_try.sh
if [[ ! -d "${SD_WEBUI_ROOT_PATH}" ]]; then
term_sd_echo "未安装 Stable-Diffusion-WebUI"
else
# 删除 SD WebUI 插件安装任务文件
rm -f "${START_PATH}/term-sd/task/sd_webui_install_extension.sh"
download_mirror_select # 下载镜像源选择
# 插件选择
SD_WEBUI_INSTALL_EXTENSION_LIST=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 安装" \
--backtitle "Stable-Diffusion-WebUI 插件安装选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要安装的 Stable-Diffusion-WebUI 插件" \
$(get_dialog_size_menu) \
$(cat "${START_PATH}/term-sd/install/sd_webui/dialog_sd_webui_extension.sh" | awk '{print $1 " " $2 " OFF"}') \
3>&1 1>&2 2>&3)
# 插件模型列表选择
if is_use_modelscope_src; then
sd_webui_extension_model_list_file="sd_webui_extension_ms_model.sh"
else
sd_webui_extension_model_list_file="sd_webui_extension_hf_model.sh"
fi
term_sd_echo "生成模型选择列表中"
# 查找插件对应模型的编号
for i in ${SD_WEBUI_INSTALL_EXTENSION_LIST}; do
sd_webui_extension_model_list="${sd_webui_extension_model_list} $(cat "${START_PATH}"/term-sd/install/sd_webui/${sd_webui_extension_model_list_file} | grep -w ${i} | awk 'NR==1{if ($NF!="") {print $1 " " $(NF-1) " " $NF} }' | awk '{sub($NF,"OFF")}1')"
done
# 模型选择
SD_WEBUI_DOWNLOAD_MODEL_LIST=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 安装" \
--backtitle "Stable-Diffusion-WebUI 插件模型下载选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要下载的 Stable-Diffusion-WebUI 插件模型" \
$(get_dialog_size_menu) \
"_null_" "=====插件模型选择=====" OFF \
${sd_webui_extension_model_list} \
3>&1 1>&2 2>&3)
# 安装确认
if term_sd_install_confirm "是否安装 Stable-Diffusion-WebUI 插件 ?"; then
term_sd_echo "生成任务队列"
touch "${START_PATH}/term-sd/task/sd_webui_install_extension.sh"
# 插件
if [[ ! -z "${SD_WEBUI_INSTALL_EXTENSION_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"下载插件中\"" >> "${START_PATH}/term-sd/task/sd_webui_install_extension.sh"
for i in ${SD_WEBUI_INSTALL_EXTENSION_LIST}; do
cat "${START_PATH}/term-sd/install/sd_webui/sd_webui_extension.sh" | grep -w ${i} | awk '{sub(" ON "," ") ; sub(" OFF "," ")}1' >> "${START_PATH}/term-sd/task/sd_webui_install_extension.sh" # 插件
done
fi
# 插件模型
if [[ ! -z "${SD_WEBUI_DOWNLOAD_MODEL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"下载模型中\"" >> "${START_PATH}/term-sd/task/sd_webui_install_extension.sh"
if is_use_modelscope_src; then
echo "__term_sd_task_sys term_sd_tmp_disable_proxy" >> "${START_PATH}/term-sd/task/sd_webui_install_extension.sh"
for i in ${SD_WEBUI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/sd_webui/sd_webui_extension_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/sd_webui_install_extension.sh" # 插件所需的模型
done
else
for i in ${SD_WEBUI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/sd_webui/sd_webui_extension_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/sd_webui_install_extension.sh" # 插件所需的模型
done
fi
fi
term_sd_echo "任务队列生成完成"
term_sd_echo "开始下载 Stable-Diffusion-WebUI 插件"
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/sd_webui_install_extension.sh" | wc -l) + 1 )) # 统计命令行数
for (( cmd_point=1; cmd_point<=cmd_sum; cmd_point++ )); do
term_sd_echo "Stable-Diffusion-WebUI 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/sd_webui_install_extension.sh" "${cmd_point}"
done
term_sd_tmp_enable_proxy # 恢复代理
term_sd_echo "Stable-Diffusion-WebUI 插件下载结束"
rm -f "${START_PATH}/term-sd/task/sd_webui_install_extension.sh" # 删除任务文件
else
term_sd_echo "取消下载 Stable-Diffusion-WebUI 插件"
fi
fi
|
2301_81996401/term-sd
|
extra/download-sd-webui-extension.sh
|
Shell
|
agpl-3.0
| 4,833
|
#!/bin/bash
# 主界面
term_sd_file_manager() {
local dialog_arg
local file_manager_select
while true; do
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Term-SD" \
--backtitle "Term-SD 备份选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择需要备份的软件\n当前备份文件存储目录: ${START_PATH}/term-sd/backup" \
$(get_dialog_size_menu) \
"0" "> 帮助" \
"1" "> Stable-Diffusion-WebUI 数据管理" \
"2" "> ComfyUI 数据管理" \
"3" "> InvokeAI 数据管理" \
"4" "> Fooocus 数据管理" \
"5" "> lora-scripts 数据管理" \
"6" "> kohya_ss 数据管理" \
"7" "> 退出" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
0)
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "Term-SD 帮助选项" \
--ok-label "确认" \
--msgbox "$(term_sd_file_manager_help)" \
$(get_dialog_size)
continue
;;
1)
file_manager_select="stable-diffusion-webui"
;;
2)
file_manager_select="ComfyUI"
;;
3)
file_manager_select="InvokeAI"
;;
4)
file_manager_select="Fooocus"
;;
5)
file_manager_select="lora-scripts"
;;
6)
file_manager_select="kohya_ss"
;;
7)
break
;;
*)
break
;;
esac
if is_sd_folder_exist "${file_manager_select}"; then
data_backup_manager "${file_manager_select}"
else
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "Term-SD 备份选项" \
--ok-label "确认" \
--msgbox "${file_manager_select} 未安装" \
$(get_dialog_size)
fi
done
}
# 管理界面
data_backup_manager() {
local start_time
local dialog_arg
local name=$@
while true; do
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Term-SD" \
--backtitle "${name} 备份选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择要进行的操作" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 备份 ${name} 数据" \
"2" "> 恢复 ${name} 数据" \
"3" "> 删除 ${name} 数据备份" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
term_sd_echo "是否备份 ${name} 数据 (yes/no) ?"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
y|yes|YES|Y)
start_time=$(date +%s)
term_sd_echo "开始备份 ${name} 数据"
term_sd_data_backup ${name}
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${name} 备份选项" \
--ok-label "确认" \
--msgbox "备份 ${name} 数据完成, $(term_sd_file_operate_time $start_time)" \
$(get_dialog_size)
;;
*)
term_sd_echo "取消操作"
;;
esac
;;
2)
term_sd_echo "是否恢复 ${name} 数据 (yes/no) ?"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
y|yes|YES|Y)
if [ -d "term-sd/backup/${name}" ]; then
start_time=$(date +%s)
term_sd_echo "开始恢复 ${name} 数据"
term_sd_data_restore ${name}
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${name} 备份选项" \
--ok-label "确认" \
--msgbox "恢复 ${name} 数据完成, $(term_sd_file_operate_time ${start_time})" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${name} 备份选项" \
--ok-label "确认" \
--msgbox "${name} 未备份" \
$(get_dialog_size)
fi
;;
*)
term_sd_echo "取消操作"
;;
esac
;;
3)
term_sd_echo "是否删除 ${name} 数据备份 (yes/no) s?"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
y|yes|YES|Y)
if [ -d "term-sd/backup/${name}" ]; then
start_time=$(date +%s)
term_sd_echo "开始删除 ${name} 数据备份"
rm -rf term-sd/backup/${name}
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${name} 备份选项" \
--ok-label "确认" \
--msgbox "删除 ${name} 数据备份完成, $(term_sd_file_operate_time ${start_time})" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${name} 备份选项" \
--ok-label "确认" \
--msgbox "${name} 未备份" \
$(get_dialog_size)
fi
;;
*)
term_sd_echo "取消操作"
;;
esac
;;
*)
break
;;
esac
done
}
# 帮助
term_sd_file_manager_help() {
cat<<EOF
该备份脚本会在 Term-SD 目录生成 "term-sd/backup" 文件夹,用于储存备份数据
以下为脚本备份的数据:
Stable-Diffusion-WebUI
├── cache.json 模型 Hash 缓存
├── config.json WebUI 设置
├── embeddings Embedding 模型目录
├── extensions WebUI 插件目录
├── models 模型路径
├── outputs 图片保存路径
├── params.txt 上次生图参数
├── ui-config.json 界面设置
└── styles.csv 提示词预设
ComfyUI
├── custom_nodes 自定义节点路径
├── models 模型路径
├── output 图片保存路径
├──web
└── extensions 插件路径（少见）
└──user
└──default
└──workflows 工作流保存路径
InvokeAI
└── invokeai 模型，图片，配置文件路径
Fooocus
├── config.txt Fooocus 设置
├── models 模型目录
└── outputs 图片保存路径
lora-scripts
├── config
│ └── autosave 训练参数保存路径
├── logs 日志路径
├── output 模型保存路径
├── sd-models 训练底模路径
└── train 训练集路径
kohya_ss
├── output 模型保存路径
├── models 训练底模路径
└── train 训练集路径
EOF
}
# 检测文件夹存在
is_sd_folder_exist() {
case "$@" in
stable-diffusion-webui)
[ -d "${SD_WEBUI_ROOT_PATH}" ] && return 0 || return 1
;;
ComfyUI)
[ -d "${COMFYUI_ROOT_PATH}" ] && return 0 || return 1
;;
InvokeAI)
[ -d "${INVOKEAI_ROOT_PATH}" ] && return 0 || return 1
;;
Fooocus)
[ -d "${FOOOCUS_ROOT_PATH}" ] && return 0 || return 1
;;
lora-scripts)
[ -d "${LORA_SCRIPTS_ROOT_PATH}" ] && return 0 || return 1
;;
kohya_ss)
[ -d "${KOHYA_SS_ROOT_PATH}" ] && return 0 || return 1
;;
esac
}
# 备份选择
term_sd_data_backup() {
case "$@" in
stable-diffusion-webui)
sd_webui_data_backup
;;
ComfyUI)
comfyui_data_backup
;;
InvokeAI)
invokeai_data_backup
;;
Fooocus)
fooocus_data_backup
;;
lora-scripts)
lora_scripts_data_backup
;;
kohya_ss)
kohya_ss_data_backup
;;
esac
}
# 恢复数据选择
term_sd_data_restore() {
case "$@" in
stable-diffusion-webui)
sd_webui_data_restore
;;
ComfyUI)
comfyui_data_restore
;;
InvokeAI)
invokeai_data_restore
;;
Fooocus)
fooocus_data_restore
;;
lora-scripts)
lora_scripts_data_restore
;;
kohya_ss)
kohya_ss_data_restore
;;
esac
}
# 时间统计
term_sd_file_operate_time() {
local start_time=$@
local end_time=$(date +%s)
local time_span
time_span=$((end_time - start_time))
echo "用时: ${time_span} sec"
}
# SD WebUI
sd_webui_data_backup() {
term_sd_mkdir "${START_PATH}"/term-sd/backup/stable-diffusion-webui
cp -rf "${SD_WEBUI_ROOT_PATH}"/embeddings "${START_PATH}"/term-sd/backup/stable-diffusion-webui/
cp -rf "${SD_WEBUI_ROOT_PATH}"/models "${START_PATH}"/term-sd/backup/stable-diffusion-webui/
cp -rf "${SD_WEBUI_ROOT_PATH}"/outputs "${START_PATH}"/term-sd/backup/stable-diffusion-webui/
cp -rf "${SD_WEBUI_ROOT_PATH}"/extensions "${START_PATH}"/term-sd/backup/stable-diffusion-webui/
cp -f "${SD_WEBUI_ROOT_PATH}"/cache.json "${START_PATH}"/term-sd/backup/stable-diffusion-webui/
cp -f "${SD_WEBUI_ROOT_PATH}"/config.json "${START_PATH}"/term-sd/backup/stable-diffusion-webui/
cp -f "${SD_WEBUI_ROOT_PATH}"/ui-config.json "${START_PATH}"/term-sd/backup/stable-diffusion-webui/
cp -f "${SD_WEBUI_ROOT_PATH}"/params.txt "${START_PATH}"/term-sd/backup/stable-diffusion-webui/
cp -f "${SD_WEBUI_ROOT_PATH}"/styles.csv "${START_PATH}"/term-sd/backup/stable-diffusion-webui/
}
sd_webui_data_restore() {
cp -rf "${START_PATH}"/term-sd/backup/stable-diffusion-webui/embeddings "${SD_WEBUI_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/stable-diffusion-webui/models "${SD_WEBUI_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/stable-diffusion-webui/outputs "${SD_WEBUI_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/stable-diffusion-webui/extensions "${SD_WEBUI_ROOT_PATH}"/
cp -f "${START_PATH}"/term-sd/backup/stable-diffusion-webui/cache.json "${SD_WEBUI_ROOT_PATH}"/
cp -f "${START_PATH}"/term-sd/backup/stable-diffusion-webui/config.json "${SD_WEBUI_ROOT_PATH}"/
cp -f "${START_PATH}"/term-sd/backup/stable-diffusion-webui/ui-config.json "${SD_WEBUI_ROOT_PATH}"/
cp -f "${START_PATH}"/term-sd/backup/stable-diffusion-webui/params.txt "${SD_WEBUI_ROOT_PATH}"/
cp -f "${START_PATH}"/term-sd/backup/stable-diffusion-webui/styles.csv "${SD_WEBUI_ROOT_PATH}"/
}
# ComfyUI
comfyui_data_backup() {
term_sd_mkdir "${START_PATH}"/term-sd/backup/ComfyUI
cp -rf "${COMFYUI_ROOT_PATH}"/custom_nodes "${START_PATH}"/term-sd/backup/ComfyUI/
cp -rf "${COMFYUI_ROOT_PATH}"/models "${START_PATH}"/term-sd/backup/ComfyUI/
cp -rf "${COMFYUI_ROOT_PATH}"/output "${START_PATH}"/term-sd/backup/ComfyUI/
cp -rf "${COMFYUI_ROOT_PATH}"/web/extensions "${START_PATH}"/term-sd/backup/ComfyUI/
cp -rf "${COMFYUI_ROOT_PATH}"/user/default/workflows "${START_PATH}"/term-sd/backup/ComfyUI/
[[ -f "${COMFYUI_ROOT_PATH}/extra_model_paths.yaml" ]] && cp -f "${COMFYUI_ROOT_PATH}"/extra_model_paths.yaml "${START_PATH}"/term-sd/backup/ComfyUI/
rm -rf "${START_PATH}"/term-sd/backup/ComfyUI/web/extensions/core
rm -f "${START_PATH}"/term-sd/backup/ComfyUI/web/extensions/logging.js.example
}
comfyui_data_restore() {
cp -rf "${START_PATH}"/term-sd/backup/ComfyUI/custom_nodes "${COMFYUI_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/ComfyUI/models "${COMFYUI_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/ComfyUI/output "${COMFYUI_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/ComfyUI/web/extensions "${COMFYUI_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/ComfyUI/user/default/workflows "${COMFYUI_ROOT_PATH}"
[ -f "${START_PATH}/term-sd/backup/ComfyUI/extra_model_paths.yaml" ] && cp -f "${START_PATH}"/term-sd/backup/ComfyUI/extra_model_paths.yaml "${COMFYUI_ROOT_PATH}"/
}
# InvokeAI
invokeai_data_backup() {
term_sd_mkdir "${START_PATH}"term-sd/backup/InvokeAI
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/autoimport "${START_PATH}"/term-sd/backup/InvokeAI/
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/configs "${START_PATH}"/term-sd/backup/InvokeAI/
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/databases "${START_PATH}"/term-sd/backup/InvokeAI/
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/nodes "${START_PATH}"/term-sd/backup/InvokeAI/
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/outputs "${START_PATH}"/term-sd/backup/InvokeAI/
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/text-inversion-output "${START_PATH}"/term-sd/backup/InvokeAI/
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/text-inversion-training-data "${START_PATH}"/term-sd/backup/InvokeAI/
cp -f "${INVOKEAI_ROOT_PATH}"/invokeai/invokeai.yaml "${START_PATH}"/term-sd/backup/InvokeAI/
term_sd_mkdir "${START_PATH}"/term-sd/backup/InvokeAI/models
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/models/any "${START_PATH}"/term-sd/backup/InvokeAI/models/
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/models/core "${START_PATH}"/term-sd/backup/InvokeAI/models/
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1 "${START_PATH}"/term-sd/backup/InvokeAI/models/
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2 "${START_PATH}"/term-sd/backup/InvokeAI/models/
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl "${START_PATH}"/term-sd/backup/InvokeAI/models/
cp -rf "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner "${START_PATH}"/term-sd/backup/InvokeAI/models/
}
invokeai_data_restore() {
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/autoimport "${INVOKEAI_ROOT_PATH}"/invokeai/
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/configs "${INVOKEAI_ROOT_PATH}"/invokeai/
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/databases "${INVOKEAI_ROOT_PATH}"/invokeai/
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/nodes "${INVOKEAI_ROOT_PATH}"/invokeai
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/outputs "${INVOKEAI_ROOT_PATH}"/invokeai/
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/text-inversion-output "${INVOKEAI_ROOT_PATH}"/invokeai/
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/text-inversion-training-data "${INVOKEAI_ROOT_PATH}"/invokeai/
cp -f "${START_PATH}"/term-sd/backup/InvokeAI/invokeai.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/
term_sd_mkdir "${INVOKEAI_ROOT_PATH}"/invokeai/models
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/models/any "${INVOKEAI_ROOT_PATH}"/invokeai/models/
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/models/core "${INVOKEAI_ROOT_PATH}"/invokeai/models/
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/models/sd-1 "${INVOKEAI_ROOT_PATH}"/invokeai/models/
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/models/sd-2 "${INVOKEAI_ROOT_PATH}"/invokeai/models/
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/models/sdxl "${INVOKEAI_ROOT_PATH}"/invokeai/models/
cp -rf "${START_PATH}"/term-sd/backup/InvokeAI/models/sdxl-refiner "${INVOKEAI_ROOT_PATH}"/invokeai/models/
}
# Fooocus
fooocus_data_backup() {
term_sd_mkdir "${START_PATH}"term-sd/backup/Fooocus
cp -rf "${FOOOCUS_ROOT_PATH}"/models "${START_PATH}"term-sd/backup/Fooocus/
cp -rf "${FOOOCUS_ROOT_PATH}"/outputs "${START_PATH}"term-sd/backup/Fooocus/
cp -f "${FOOOCUS_ROOT_PATH}"/config.txt "${START_PATH}"term-sd/backup/Fooocus/
}
fooocus_data_restore() {
cp -rf "${START_PATH}"/term-sd/backup/Fooocus/models "${FOOOCUS_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/Fooocus/outputs "${FOOOCUS_ROOT_PATH}"/
cp -f "${START_PATH}"/term-sd/backup/Fooocus/config.txt "${FOOOCUS_ROOT_PATH}"/
}
# lora-scripts
lora_scripts_data_backup() {
term_sd_mkdir "${START_PATH}"term-sd/backup/lora-scripts
cp -rf "${LORA_SCRIPTS_ROOT_PATH}"/config/autosave "${START_PATH}"term-sd/backup/lora-scripts/
cp -rf "${LORA_SCRIPTS_ROOT_PATH}"/logs "${START_PATH}"term-sd/backup/lora-scripts/
cp -rf "${LORA_SCRIPTS_ROOT_PATH}"/output "${START_PATH}"term-sd/backup/lora-scripts/
cp -rf "${LORA_SCRIPTS_ROOT_PATH}"/sd-models "${START_PATH}"term-sd/backup/lora-scripts/
cp -rf "${LORA_SCRIPTS_ROOT_PATH}"/train "${START_PATH}"term-sd/backup/lora-scripts/
}
lora_scripts_data_restore() {
cp -rf "${START_PATH}"/term-sd/backup/lora-scripts/config/autosave "${LORA_SCRIPTS_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/lora-scripts/logs "${LORA_SCRIPTS_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/lora-scripts/output "${LORA_SCRIPTS_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/lora-scripts/sd-models "${LORA_SCRIPTS_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/lora-scripts/train "${LORA_SCRIPTS_ROOT_PATH}"/
}
# kohya_ss
kohya_ss_data_backup() {
term_sd_mkdir "${START_PATH}"term-sd/backup/kohya_ss
cp -rf "${KOHYA_SS_ROOT_PATH}"/output "${START_PATH}"/term-sd/backup/kohya_ss/
cp -rf "${KOHYA_SS_ROOT_PATH}"/train "${START_PATH}"/term-sd/backup/kohya_ss/
cp -rf "${KOHYA_SS_ROOT_PATH}"/models "${START_PATH}"/term-sd/backup/kohya_ss/
}
kohya_ss_data_restore() {
cp -rf "${START_PATH}"/term-sd/backup/kohya_ss/output "${KOHYA_SS_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/kohya_ss/train "${KOHYA_SS_ROOT_PATH}"/
cp -rf "${START_PATH}"/term-sd/backup/kohya_ss/models "${KOHYA_SS_ROOT_PATH}"/
}
#################################################
if [[ -d "${START_PATH}/term-sd/backup" ]]; then
term_sd_echo "备份数据文件夹路径: ${START_PATH}/term-sd/backup"
else
term_sd_echo "创建备份数据文件夹中, 路径: ${START_PATH}/term-sd/backup"
term_sd_mkdir "${START_PATH}/term-sd/backup"
fi
term_sd_file_manager
|
2301_81996401/term-sd
|
extra/file-backup.sh
|
Shell
|
agpl-3.0
| 19,390
|
#!/bin/bash
# 没啥用的脚本
term_sd_echo "当前可用扩展脚本列表"
term_sd_print_line
ls -lrh "${START_PATH}/term-sd/extra" --time-style=+"%Y-%m-%d" | awk 'NR>=2 {print " "$7}' | awk -F '.sh' '{print $1}'
term_sd_print_line
term_sd_echo "提示: 使用 \"--extra\" 启动参数启动扩展脚本选项界面, 或者使用 \"--extra 脚本名\" 直接启动指定的扩展脚本"
|
2301_81996401/term-sd
|
extra/list.sh
|
Shell
|
agpl-3.0
| 392
|
__term_sd_task_sys term_sd_mkdir "${COMFYUI_PARENT_PATH}"
__term_sd_task_sys cd "${COMFYUI_PARENT_PATH}"
__term_sd_task_sys term_sd_tmp_enable_proxy
__term_sd_task_pre_core git_clone_repository https://github.com/comfyanonymous/ComfyUI "${COMFYUI_PARENT_PATH}" "${COMFYUI_FOLDER}"
__term_sd_task_sys term_sd_tmp_disable_proxy # 临时取消代理, 避免一些不必要的网络减速
__term_sd_task_sys is_sd_repo_exist "${COMFYUI_ROOT_PATH}"
__term_sd_task_pre_core create_venv "${COMFYUI_ROOT_PATH}"
__term_sd_task_sys enter_venv "${COMFYUI_ROOT_PATH}"
__term_sd_task_pre_core install_pytorch # 安装 PyTorch
__term_sd_task_pre_core install_python_package -r "${COMFYUI_ROOT_PATH}"/requirements.txt
__term_sd_task_pre_core set_comfyui_normal_config
|
2301_81996401/term-sd
|
install/comfyui/comfyui_core.sh
|
Shell
|
agpl-3.0
| 753
|
__term_sd_task_pre_ext_1 git_clone_repository https://github.com/Fannovel16/comfyui_controlnet_aux "${COMFYUI_ROOT_PATH}"/custom_nodes ON # ComfyUI的ControlNet辅助预处理器
__term_sd_task_pre_ext_2 git_clone_repository https://github.com/Kosinkadink/ComfyUI-AnimateDiff-Evolved "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 视频生成节点
__term_sd_task_pre_ext_3 git_clone_repository https://github.com/cubiq/ComfyUI_IPAdapter_plus "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 添加ip-adapt支持
__term_sd_task_pre_ext_4 git_clone_repository https://github.com/ltdrdata/ComfyUI-Impact-Pack "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 通过检测器、细节器、升频器、管道等方便地增强图像
__term_sd_task_pre_ext_5 git_clone_repository https://github.com/kijai/ComfyUI-Marigold "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 深度图生成节点
__term_sd_task_pre_ext_6 git_clone_repository https://github.com/pythongosssss/ComfyUI-WD14-Tagger "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 图片标签反推
__term_sd_task_pre_ext_7 git_clone_repository https://github.com/huchenlei/ComfyUI-layerdiffusion "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # LayerDiffusion节点
__term_sd_task_pre_ext_8 git_clone_repository https://github.com/huchenlei/ComfyUI_DanTagGen "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 使用Danboou风格对tag进行润色，使出图效果更好，内容更丰富
__term_sd_task_pre_ext_9 git_clone_repository https://github.com/gameltb/Comfyui-StableSR "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 图片放大
__term_sd_task_pre_ext_10 git_clone_repository https://github.com/KohakuBlueleaf/z-tipo-extension "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 使用danbooru-tag和自然语言对提示词进行润色，增强模型的出图效果
__term_sd_task_pre_ext_11 git_clone_repository https://github.com/WASasquatch/was-node-suite-comfyui "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 适用于ComfyUI的广泛节点套件，包含190多个新节点
__term_sd_task_pre_ext_12 git_clone_repository https://github.com/BlenderNeko/ComfyUI_Cutoff "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 解决tag污染
__term_sd_task_pre_ext_13 git_clone_repository https://github.com/BlenderNeko/ComfyUI_TiledKSampler "${COMFYUI_ROOT_PATH}"/custom_nodes ON # ComfyUI的平铺采样器
__term_sd_task_pre_ext_14 git_clone_repository https://github.com/BlenderNeko/ComfyUI_ADV_CLIP_emb "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 高级剪辑文本编码，可让您选择解释提示权重的方式
__term_sd_task_pre_ext_15 git_clone_repository https://github.com/BlenderNeko/ComfyUI_Noise "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 噪声控制
__term_sd_task_pre_ext_16 git_clone_repository https://github.com/Davemane42/ComfyUI_Dave_CustomNode "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 图片区域控制
__term_sd_task_pre_ext_17 git_clone_repository https://github.com/Comfy-Org/ComfyUI-Manager "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 自定义节点管理器
__term_sd_task_pre_ext_18 git_clone_repository https://github.com/Zuellni/ComfyUI-Custom-Nodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # ComfyUI的自定义节点
__term_sd_task_pre_ext_19 git_clone_repository https://github.com/pythongosssss/ComfyUI-Custom-Scripts "${COMFYUI_ROOT_PATH}"/custom_nodes ON # ComfyUI的增强功能
__term_sd_task_pre_ext_20 git_clone_repository https://github.com/xXAdonesXx/NodeGPT "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 使用GPT辅助生图
__term_sd_task_pre_ext_21 git_clone_repository https://github.com/Derfuu/Derfuu_ComfyUI_ModdedNodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 方程式节点
__term_sd_task_pre_ext_22 git_clone_repository https://github.com/lilly1987/ComfyUI_node_Lilly "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 通配符文本工具
__term_sd_task_pre_ext_23 git_clone_repository https://github.com/hnmr293/ComfyUI-nodes-hnmr "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 包含X/Y/Z-plotX/Y/Z，合并，潜在可视化，采样等节点
__term_sd_task_pre_ext_24 git_clone_repository https://github.com/diontimmer/ComfyUI-Vextra-Nodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 包含像素排序，交换颜色模式，拼合颜色等节点
__term_sd_task_pre_ext_25 git_clone_repository https://github.com/omar92/ComfyUI-QualityOfLifeSuit_Omar92 "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 包含GPT辅助标签生成，字符串操作，latentTools等节点
__term_sd_task_pre_ext_26 git_clone_repository https://github.com/Fannovel16/FN16-ComfyUI-nodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # ComfyUI自定义节点集合
__term_sd_task_pre_ext_27 git_clone_repository https://github.com/BadCafeCode/masquerade-nodes-comfyui "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # ComfyUI掩码相关节点
__term_sd_task_pre_ext_28 git_clone_repository https://github.com/EllangoK/ComfyUI-post-processing-nodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # ComfyUI的后处理节点集合，可实现各种酷炫的图像效果
__term_sd_task_pre_ext_29 git_clone_repository https://github.com/LEv145/images-grid-comfy-plugin "${COMFYUI_ROOT_PATH}"/custom_nodes ON # XYZPlot图生成
__term_sd_task_pre_ext_30 git_clone_repository https://github.com/biegert/ComfyUI-CLIPSeg "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 利用CLIPSeg模型根据文本提示为图像修复任务生成蒙版
__term_sd_task_pre_ext_31 git_clone_repository https://github.com/Jcd1230/rembg-comfyui-node "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 背景去除
__term_sd_task_pre_ext_32 git_clone_repository https://github.com/TinyTerra/ComfyUI_tinyterraNodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # ComfyUI的自定义节点
__term_sd_task_pre_ext_33 git_clone_repository https://github.com/guoyk93/yk-node-suite-comfyui "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # ComfyUI的自定义节点
__term_sd_task_pre_ext_34 git_clone_repository https://github.com/comfyanonymous/ComfyUI_experiments "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # ComfyUI的一些实验性自定义节点
__term_sd_task_pre_ext_35 git_clone_repository https://github.com/gamert/ComfyUI_tagger "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 图片tag反推
__term_sd_task_pre_ext_36 git_clone_repository https://github.com/YinBailiang/MergeBlockWeighted_fo_ComfyUI "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 权重合并
__term_sd_task_pre_ext_37 git_clone_repository https://github.com/Kaharos94/ComfyUI-Saveaswebp "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 将生成的图片保存为webp格式
__term_sd_task_pre_ext_38 git_clone_repository https://github.com/trojblue/trNodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 通过蒙版混合两个图像
__term_sd_task_pre_ext_39 git_clone_repository https://github.com/city96/ComfyUI_NetDist "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 在多个本地GPU/联网机器上运行ComfyUI工作流程
__term_sd_task_pre_ext_40 git_clone_repository https://github.com/SLAPaper/ComfyUI-Image-Selector "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 从批处理中选择一个或多个图像
__term_sd_task_pre_ext_41 git_clone_repository https://github.com/strimmlarn/ComfyUI-Strimmlarns-Aesthetic-Score "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 图片美学评分
__term_sd_task_pre_ext_42 git_clone_repository https://github.com/ssitu/ComfyUI_UltimateSDUpscale "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 图片放大
__term_sd_task_pre_ext_43 git_clone_repository https://github.com/space-nuko/ComfyUI-Disco-Diffusion "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # DiscoDiffusion模块
__term_sd_task_pre_ext_44 git_clone_repository https://github.com/Bikecicle/ComfyUI-Waveform-Extensions "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 包括姿势，翻译等节点
__term_sd_task_pre_ext_45 git_clone_repository https://github.com/AlekPet/ComfyUI_Custom_Nodes_AlekPet "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 提示词翻译节点
__term_sd_task_pre_ext_46 git_clone_repository https://github.com/AIGODLIKE/AIGODLIKE-COMFYUI-TRANSLATION "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # ComfyUI的翻译扩展
__term_sd_task_pre_ext_47 git_clone_repository https://github.com/Stability-AI/stability-ComfyUI-nodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # Stability-AI自定义节点支持
__term_sd_task_pre_ext_48 git_clone_repository https://github.com/hustille/ComfyUI_Fooocus_KSampler "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加fooocus噪声生成器支持
__term_sd_task_pre_ext_49 git_clone_repository https://github.com/WASasquatch/FreeU_Advanced "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 生图加速
__term_sd_task_pre_ext_50 git_clone_repository https://github.com/kohya-ss/ControlNet-LLLite-ComfyUI "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加ControlNet-LLLite支持
__term_sd_task_pre_ext_51 git_clone_repository https://github.com/Acly/comfyui-tooling-nodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 使用ComfyUI作为外部工具后端的节点
__term_sd_task_pre_ext_52 git_clone_repository https://github.com/jags111/efficiency-nodes-comfyui "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 自定义节点的集合，可帮助简化工作流程并减少节点总数
__term_sd_task_pre_ext_53 git_clone_repository https://github.com/laksjdjf/cd-tuner_negpip-ComfyUI "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 解决tag的强污染，效果比cutoff好
__term_sd_task_pre_ext_54 git_clone_repository https://github.com/yolain/ComfyUI-Easy-Use "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 自定义节点集合
__term_sd_task_pre_ext_55 git_clone_repository https://github.com/twri/sdxl_prompt_styler "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # SDXL提示词风格预设节点
__term_sd_task_pre_ext_56 git_clone_repository https://github.com/11cafe/comfyui-workspace-manager "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 工作流管理器
__term_sd_task_pre_ext_57 git_clone_repository https://github.com/talesofai/comfyui-browser "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 查看和管理ComfyUI的所有输出文件/工作流，并且添加收藏方便随时调用
__term_sd_task_pre_ext_58 git_clone_repository https://github.com/chrisgoringe/cg-use-everywhere "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 节点整理工具
__term_sd_task_pre_ext_59 git_clone_repository https://github.com/ltdrdata/ComfyUI-Inspire-Pack "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 整合多功能的节点
__term_sd_task_pre_ext_60 git_clone_repository https://github.com/mcmonkeyprojects/sd-dynamic-thresholding "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 解决使用更高的CFGScale而出现颜色问题
__term_sd_task_pre_ext_61 git_clone_repository https://github.com/rgthree/rgthree-comfy "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 节点管道工具
__term_sd_task_pre_ext_62 git_clone_repository https://github.com/Suzie1/ComfyUI_Comfyroll_CustomNodes "${COMFYUI_ROOT_PATH}"/custom_nodes ON # ComfyUI自定义节点合集
__term_sd_task_pre_ext_63 git_clone_repository https://github.com/FizzleDorf/ComfyUI_FizzNodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 视频制作节点
__term_sd_task_pre_ext_64 git_clone_repository https://github.com/Kosinkadink/ComfyUI-Advanced-ControlNet "${COMFYUI_ROOT_PATH}"/custom_nodes ON # Controlnet节点，包含各种Controlnet调节选项
__term_sd_task_pre_ext_65 git_clone_repository https://github.com/WASasquatch/PowerNoiseSuite "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 噪声生成节点
__term_sd_task_pre_ext_66 git_clone_repository https://github.com/crystian/ComfyUI-Crystools "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 资源监视器
__term_sd_task_pre_ext_67 git_clone_repository https://github.com/chflame163/ComfyUI_LayerStyle "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 图层和蒙版合成节点
__term_sd_task_pre_ext_68 git_clone_repository https://github.com/Nuked88/ComfyUI-N-Sidebar "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 节点快捷收藏整理工具
__term_sd_task_pre_ext_69 git_clone_repository https://github.com/brianfitzgerald/style_aligned_comfy "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 使用StyleAligned保持多张图片一致性
__term_sd_task_pre_ext_70 git_clone_repository https://github.com/flowtyone/ComfyUI-Flowty-TripoSR "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加TripoSR支持
__term_sd_task_pre_ext_71 git_clone_repository https://github.com/city96/ComfyUI_ExtraModels "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加DiT，PixArt，HunYuanDiT，MiaoBi模型的支持
__term_sd_task_pre_ext_72 git_clone_repository https://github.com/kijai/ComfyUI-SUPIR "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加DiT，PixArt，T5和一些自定义VAE模型的支持
__term_sd_task_pre_ext_73 git_clone_repository https://github.com/ZHO-ZHO-ZHO/ComfyUI-YoloWorld-EfficientSAM "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 对象检测与分割
__term_sd_task_pre_ext_74 git_clone_repository https://github.com/ZHO-ZHO-ZHO/ComfyUI-PixArt-alpha-Diffusers "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加PixArt-α模型支持
__term_sd_task_pre_ext_75 git_clone_repository https://github.com/ZHO-ZHO-ZHO/ComfyUI-BiRefNet-ZHO "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 对象蒙版生成
__term_sd_task_pre_ext_76 git_clone_repository https://github.com/ZHO-ZHO-ZHO/ComfyUI-DepthFM "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 深度图生成
__term_sd_task_pre_ext_77 git_clone_repository https://github.com/ZHO-ZHO-ZHO/ComfyUI-APISR "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 图像放大
__term_sd_task_pre_ext_78 git_clone_repository https://github.com/ZHO-ZHO-ZHO/ComfyUI-ArtGallery "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 可视化风格提示词预设选择
__term_sd_task_pre_ext_79 git_clone_repository https://github.com/ZHO-ZHO-ZHO/ComfyUI-BRIA_AI-RMBG "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 图片背景移除
__term_sd_task_pre_ext_80 git_clone_repository https://github.com/ZHO-ZHO-ZHO/ComfyUI-I2VGenXL "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加I2VGenXL的支持
__term_sd_task_pre_ext_81 git_clone_repository https://github.com/ZHO-ZHO-ZHO/ComfyUI-SegMoE "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加SegMoE的支持
__term_sd_task_pre_ext_82 git_clone_repository https://github.com/ZHO-ZHO-ZHO/ComfyUI-AnyText "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加AnyText的支持
__term_sd_task_pre_ext_83 git_clone_repository https://github.com/Clybius/ComfyUI-Extra-Samplers "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加额外的采样器
__term_sd_task_pre_ext_84 git_clone_repository https://github.com/blepping/ComfyUI-sonar "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加sonar采样器
__term_sd_task_pre_ext_85 git_clone_repository https://github.com/ssitu/ComfyUI_restart_sampling "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加restart采样器
__term_sd_task_pre_ext_86 git_clone_repository https://github.com/kijai/ComfyUI-Diffusers-X-Adapter "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加x-adapter支持
__term_sd_task_pre_ext_87 git_clone_repository https://github.com/nullquant/ComfyUI-BrushNet "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加brushnet支持，用于精准重绘
__term_sd_task_pre_ext_88 git_clone_repository https://github.com/kijai/ComfyUI-BrushNet-Wrapper "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加brushnet支持，用于精准重绘
__term_sd_task_pre_ext_89 git_clone_repository https://github.com/Koishi-Star/Euler-Smea-Dyn-Sampler "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加Eular-SMEA-Dy采样算法
__term_sd_task_pre_ext_90 git_clone_repository https://github.com/blepping/ComfyUI-bleh "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 改进hypertile和deepshrink节点，提供更好的生成预览算法
__term_sd_task_pre_ext_91 git_clone_repository https://github.com/dfl/comfyui-tcd-scheduler "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加TCD采样器
__term_sd_task_pre_ext_92 git_clone_repository https://github.com/huchenlei/ComfyUI-IC-Light-Native "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加ic-light支持
__term_sd_task_pre_ext_93 git_clone_repository https://github.com/Acly/comfyui-inpaint-nodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加fooocus的重绘模型支持
__term_sd_task_pre_ext_94 git_clone_repository https://github.com/comfyanonymous/ComfyUI_TensorRT "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加TensorRT加速
__term_sd_task_pre_ext_95 git_clone_repository https://github.com/Haoming02/comfyui-diffusion-cg "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 在潜空间张量范围执行颜色分级，改进出图的效果
__term_sd_task_pre_ext_96 git_clone_repository https://github.com/Haoming02/comfyui-floodgate "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 节点控制
__term_sd_task_pre_ext_97 git_clone_repository https://github.com/Haoming02/comfyui-resharpen "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 为主体生成用于修复的蒙版，使背景与主体融合更融洽
__term_sd_task_pre_ext_98 git_clone_repository https://github.com/Haoming02/comfyui-menu-anchor "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 界面按钮位置修改
__term_sd_task_pre_ext_99 git_clone_repository https://github.com/Haoming02/comfyui-tab-handler "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 将tab按键的行为修改成聚焦文本区域
__term_sd_task_pre_ext_100 git_clone_repository https://github.com/Haoming02/comfyui-clear-screen "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 清理控制台输出
__term_sd_task_pre_ext_101 git_clone_repository https://github.com/Haoming02/comfyui-node-beautify "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 节点美化
__term_sd_task_pre_ext_102 git_clone_repository https://github.com/Haoming02/comfyui-prompt-format "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 提示词格式化工具
__term_sd_task_pre_ext_103 git_clone_repository https://github.com/huchenlei/ComfyUI_omost "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加omost模型支持
__term_sd_task_pre_ext_104 git_clone_repository https://github.com/TheMistoAI/ComfyUI-Anyline "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加anyline预处理器
__term_sd_task_pre_ext_105 git_clone_repository https://github.com/shiimizu/ComfyUI-TiledDiffusion "${COMFYUI_ROOT_PATH}"/custom_nodes ON # TiledDiffusion分块放大工具
__term_sd_task_pre_ext_106 git_clone_repository https://github.com/kijai/ComfyUI-DynamiCrafterWrapper "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # ToonCrafter节点
__term_sd_task_pre_ext_107 git_clone_repository https://github.com/thisjam/comfyui-sixgod_prompt "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 提示词辅助工具
__term_sd_task_pre_ext_108 git_clone_repository https://github.com/huchenlei/ComfyUI_densediffusion "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 使用DenseDiffusion进行分区控制
__term_sd_task_pre_ext_109 git_clone_repository https://github.com/huchenlei/omost_region_editor "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # omost区域提示词编辑器
__term_sd_task_pre_ext_110 git_clone_repository https://github.com/huchenlei/ComfyUI-openpose-editor "${COMFYUI_ROOT_PATH}"/custom_nodes ON # openpose编辑器
__term_sd_task_pre_ext_111 git_clone_repository https://github.com/kijai/ComfyUI-IC-Light "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加lc-light支持
__term_sd_task_pre_ext_112 git_clone_repository https://github.com/kijai/ComfyUI-KJNodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 自定义节点集合
__term_sd_task_pre_ext_113 git_clone_repository https://github.com/cubiq/ComfyUI_essentials "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 自定义节点集合
__term_sd_task_pre_ext_114 git_clone_repository https://github.com/licyk/ComfyUI-Restart-Sampler "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 为ComfyUI添加Restart采样算法
__term_sd_task_pre_ext_115 git_clone_repository https://github.com/licyk/ComfyUI-TCD-Sampler "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 为ComfyUI添加TCD采样算法
__term_sd_task_pre_ext_116 git_clone_repository https://github.com/chrisgoringe/cg-noise "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加变异种子支持
__term_sd_task_pre_ext_117 git_clone_repository https://github.com/googincheng/ComfyUX "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 优化ComfyUI界面，使整理节点更方便
__term_sd_task_pre_ext_118 git_clone_repository https://github.com/ZHO-ZHO-ZHO/ComfyUI-UltraEdit-ZHO "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加UltraEdit支持
__term_sd_task_pre_ext_119 git_clone_repository https://github.com/weilin9999/WeiLin-ComfyUI-prompt-all-in-one "${COMFYUI_ROOT_PATH}"/custom_nodes ON # Prompt-all-in-one-app项目的修改版本，能够在ComfyUI中创建节点使用tag功能
__term_sd_task_pre_ext_120 git_clone_repository https://github.com/city96/ComfyUI-GGUF "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 为ComfyUI添加gguf格式模型的支持
__term_sd_task_pre_ext_121 git_clone_repository https://github.com/XLabs-AI/x-flux-comfyui "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加xlabs的controlnet模型支持
__term_sd_task_pre_ext_122 git_clone_repository https://github.com/MakkiShizu/ComfyUI-Prompt-Wildcards "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加提示词通配符支持
__term_sd_task_pre_ext_123 git_clone_repository https://github.com/chrisgoringe/cg-controller "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加类似invokeai的节点整理控制
__term_sd_task_pre_ext_124 git_clone_repository https://github.com/Clybius/ComfyUI-Latent-Modifiers "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 在Latent部分应用滤镜，调整出图效果
__term_sd_task_pre_ext_125 git_clone_repository https://github.com/BennyKok/comfyui-deploy "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 将ComfyUI工作流生成API
__term_sd_task_pre_ext_126 git_clone_repository https://github.com/licyk/ComfyUI-HakuImg "${COMFYUI_ROOT_PATH}"/custom_nodes ON # 图像处理工具
__term_sd_task_pre_ext_127 git_clone_repository https://github.com/Repeerc/ComfyUI-flash-attention-rdna3-win-zluda "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 为Windows下的ZLUDA添加FlashAttension支持
__term_sd_task_pre_ext_128 git_clone_repository https://github.com/AIGODLIKE/ComfyUI-BlenderAI-node "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 为blender添加comfyui支持
__term_sd_task_pre_ext_129 git_clone_repository https://github.com/florestefano1975/comfyui-portrait-master "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 使用滑块调整描述人物的提示词
__term_sd_task_pre_ext_130 git_clone_repository https://github.com/Extraltodeus/sigmas_tools_and_the_golden_scheduler "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 调整调度器
__term_sd_task_pre_ext_131 git_clone_repository https://github.com/ssitu/ComfyUI_fabric "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 基于注意力的参考图像调节
__term_sd_task_pre_ext_132 git_clone_repository https://github.com/Ttl/ComfyUi_NNLatentUpscale "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 使用小型神经网络快速放大潜空间图像
__term_sd_task_pre_ext_133 git_clone_repository https://github.com/badjeff/comfyui_lora_tag_loader "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 使用提示词调用LoRA模型
__term_sd_task_pre_ext_134 git_clone_repository https://github.com/diStyApps/ComfyUI-disty-Flow "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 提供便捷的ComfyUI界面
__term_sd_task_pre_ext_135 git_clone_repository https://github.com/kijai/ComfyUI-FluxTrainer "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 在ComfyUI训练FLUX模型
__term_sd_task_pre_ext_136 git_clone_repository https://github.com/MoonHugo/ComfyUI-BiRefNet-Hugo "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加BiRefNet支持，用于移除背景
__term_sd_task_pre_ext_137 git_clone_repository https://github.com/weilin9999/WeiLin-Comfyui-Tools "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # ComfyUI提示词工具
__term_sd_task_pre_ext_138 git_clone_repository https://github.com/chengzeyi/Comfy-WaveSpeed "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 加速ComfyUI推理速度
__term_sd_task_pre_ext_139 git_clone_repository https://github.com/welltop-cn/ComfyUI-TeaCache "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 使用TeaCache加速ComfyUI推理速度
__term_sd_task_pre_ext_140 git_clone_repository https://github.com/AIGODLIKE/AIGODLIKE-ComfyUI-Studio "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 提供快捷模型管理
__term_sd_task_pre_ext_141 git_clone_repository https://github.com/pydn/ComfyUI-to-Python-Extension "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 将工作流转换为Python库进行调用
__term_sd_task_pre_ext_142 git_clone_repository https://github.com/kijai/ComfyUI-FramePackWrapper "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加FramePack支持
__term_sd_task_pre_ext_143 git_clone_repository https://github.com/tzwm/comfyui-profiler "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 统计各个节点的运行时间
__term_sd_task_pre_ext_144 git_clone_repository https://github.com/KohakuBlueleaf/HDM-ext "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 添加HDM模型加载器
__term_sd_task_pre_ext_145 git_clone_repository https://github.com/QuangLe97/ComfyUI-rgthree-comfy "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 自定义节点集合，并提供进度条显示
__term_sd_task_pre_ext_146 git_clone_repository https://github.com/Firetheft/ComfyUI_Civitai_Gallery "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 将Civitai中的图片参数导入到工作流中
__term_sd_task_pre_ext_147 git_clone_repository https://github.com/ramyma/A8R8_ComfyUI_nodes "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 提供分区绘制
__term_sd_task_pre_ext_148 git_clone_repository https://github.com/laksjdjf/cgem156-ComfyUI "${COMFYUI_ROOT_PATH}"/custom_nodes OFF # 提供分区绘制等节点
|
2301_81996401/term-sd
|
install/comfyui/comfyui_custom_node.sh
|
Shell
|
agpl-3.0
| 25,449
|
__term_sd_task_pre_ext_1 term_sd_echo "下载 ControlNet 模型中" # ControlNet(25.93g) ON
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11e_sd15_ip2p_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11e_sd15_shuffle_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11f1e_sd15_tile_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11f1p_sd15_depth_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_canny_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_inpaint_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_lineart_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_mlsd_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_normalbae_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_openpose_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_scribble_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_seg_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_softedge_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15s2_lineart_anime_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v1p_sd15_brightness.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v1p_sd15_illumination.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v1p_sd15_qrcode_monster.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/sd_control_collection/resolve/main/xinsir-controlnet-union-sdxl-1.0-promax.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/LayerNorm/DensePose-TorchScript-with-hint-image/densepose_r101_fpn_dl.torchscript "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/LayerNorm/DensePose-TorchScript-with-hint-image
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/LayerNorm/DensePose-TorchScript-with-hint-image/densepose_r50_fpn_dl.torchscript "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/LayerNorm/DensePose-TorchScript-with-hint-image
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/LiheYoung/Depth-Anything/checkpoints/depth_anything_vitl14.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/LiheYoung/Depth-Anything/checkpoints
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/LiheYoung/Depth-Anything/checkpoints_metric_depth/depth_anything_metric_depth_indoor.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/LiheYoung/Depth-Anything/checkpoints_metric_depth
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/bdsqlsz/qinglong_controlnet-lllite/Annotators/7_model.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/bdsqlsz/qinglong_controlnet-lllite/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/bdsqlsz/qinglong_controlnet-lllite/Annotators/UNet.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/bdsqlsz/qinglong_controlnet-lllite/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/dhkim2810/MobileSAM/mobile_sam.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/hr16/ControlNet-HandRefiner-pruned/graphormer_hand_state_dict.bin "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/hr16/ControlNet-HandRefiner-pruned/hrnetv2_w64_imagenet_pretrained.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/hr16/DWPose-TorchScript-BatchSize5/dw-ll_ucoco_384_bs5.torchscript.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/hr16/DWPose-TorchScript-BatchSize5/rtmpose-m_ap10k_256_bs5.torchscript.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/hr16/UnJIT-DWPose/dw-ll_ucoco.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/UnJIT-DWPose
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/hr16/UnJIT-DWPose/rtmpose-m_ap10k_256.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/UnJIT-DWPose
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/hr16/yolo-nas-fp16/yolo_nas_l_fp16.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/yolo-nas-fp16
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/hr16/yolo-nas-fp16/yolo_nas_m_fp16.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/yolo-nas-fp16
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/hr16/yolo-nas-fp16/yolo_nas_s_fp16.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/yolo-nas-fp16
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/hr16/yolox-onnx/yolox_l.torchscript.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/yolox-onnx
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/150_16_swin_l_oneformer_coco_100ep.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/250_16_swin_l_oneformer_ade20k_160k.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/ControlNetHED.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/ZoeD_M12_N.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/body_pose_model.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/dpt_hybrid-midas-501f0c75.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/dw-ll_ucoco_384.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/erika.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/facenet.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/hand_pose_model.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/latest_net_G.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/mlsd_large_512_fp32.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/netG.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/res101.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/scannet.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/sk_model.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/sk_model2.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/table5_pidinet.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/upernet_global_small.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/lllyasviel/Annotators/yolox_l.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/skytnt/anime-seg/isnetis.ckpt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/skytnt/anime-seg
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/yzd-v/DWPose/dw-ll_ucoco_384.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/yzd-v/DWPose
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/comfyui_controlnet_aux/yzd-v/DWPose/yolox_l.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/yzd-v/DWPose
__term_sd_task_pre_ext_2 term_sd_echo "下载 Animatediff 模型中" # AnimateDiff(1.67g) OFF
__term_sd_task_pre_ext_2 aria2_download https://huggingface.co/guoyww/animatediff/resolve/main/v3_sd15_mm.ckpt "${COMFYUI_ROOT_PATH}"/models/animatediff_models
__term_sd_task_pre_ext_3 term_sd_echo "下载 IP-Adapter 模型中" # IP-Adapter(9.63g) ON
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter_sd15.pth "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter_sd15_light.pth "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter_sd15_plus.pth "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter_sd15_vit-G.safetensors "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter_sdxl.safetensors "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter-plus_sdxl_vit-h.safetensors "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/clip_vision/clip_g.pth "${COMFYUI_ROOT_PATH}"/models/clip_vision
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/clip_vision/clip_h.pth "${COMFYUI_ROOT_PATH}"/models/clip_vision
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/clip_vision/clip_vitl.pth "${COMFYUI_ROOT_PATH}"/models/clip_vision
__term_sd_task_pre_ext_4 term_sd_echo "下载 ComfyUI-Impact-Pack 模型中" # ComfyUI-Impact-Pack(750m) ON
__term_sd_task_pre_ext_4 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Impact-Pack/face_yolov8m.pt "${COMFYUI_ROOT_PATH}"/models/ultralytics/bbox
__term_sd_task_pre_ext_4 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Impact-Pack/mmdet_anime-face_yolov3.pth "${COMFYUI_ROOT_PATH}"/models/ultralytics/bbox
__term_sd_task_pre_ext_4 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Impact-Pack/sam_vit_b_01ec64.pth "${COMFYUI_ROOT_PATH}"/models/sams
__term_sd_task_pre_ext_4 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Impact-Pack/hand_yolov8s.pt "${COMFYUI_ROOT_PATH}"/models/ultralytics/bbox
__term_sd_task_pre_ext_4 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Impact-Pack/person_yolov8m-seg.pt "${COMFYUI_ROOT_PATH}"/models/ultralytics/segm
__term_sd_task_pre_ext_5 term_sd_echo "下载 ComfyUI-Marigold 模型中" # ComfyUI-Marigold(5.15g) OFF
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/model_index.json "${COMFYUI_ROOT_PATH}"/diffusers
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/scheduler/scheduler_config.json "${COMFYUI_ROOT_PATH}"/diffusers/scheduler
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/text_encoder/config.json "${COMFYUI_ROOT_PATH}"/diffusers/text_encoder
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/text_encoder/model.safetensors "${COMFYUI_ROOT_PATH}"/diffusers/text_encoder
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/tokenizer/merges.txt "${COMFYUI_ROOT_PATH}"/diffusers/tokenizer
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/tokenizer/special_tokens_map.json "${COMFYUI_ROOT_PATH}"/diffusers/tokenizer
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/tokenizer/tokenizer_config.json "${COMFYUI_ROOT_PATH}"/diffusers/tokenizer
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/tokenizer/vocab.json "${COMFYUI_ROOT_PATH}"/diffusers/tokenizer
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/unet/config.json "${COMFYUI_ROOT_PATH}"/diffusers/unet
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/unet/diffusion_pytorch_model.safetensors "${COMFYUI_ROOT_PATH}"/diffusers/unet
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/vae/config.json "${COMFYUI_ROOT_PATH}"/diffusers/vae
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-Marigold/vae/diffusion_pytorch_model.safetensors "${COMFYUI_ROOT_PATH}"/diffusers/vae
__term_sd_task_pre_ext_6 term_sd_echo "下载 ComfyUI-WD14-Tagger 模型中" # ComfyUI-WD14-Tagger(3.09g) ON
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-v1-4-convnext-tagger-v2.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-v1-4-convnext-tagger-v2.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-v1-4-convnext-tagger.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-v1-4-convnext-tagger.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-v1-4-convnextv2-tagger-v2.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-v1-4-convnextv2-tagger-v2.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-v1-4-moat-tagger-v2.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-v1-4-moat-tagger-v2.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-v1-4-vit-tagger-v2.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-v1-4-vit-tagger-v2.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-convnext-tagger-v3.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-convnext-tagger-v3.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-swinv2-tagger-v3.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-swinv2-tagger-v3.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-vit-tagger-v3.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/ComfyUI-WD14-Tagger/wd-vit-tagger-v3.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_7 term_sd_echo "下载 ComfyUI-layerdiffusion 模型" # LayerDiffusion(10.29g) ON
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_bg2ble.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_bgble2fg.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_fg2ble.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_fgble2bg.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_transparent_attn.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_transparent_conv.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/vae_transparent_decoder.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/vae_transparent_encoder.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_8 term_sd_echo "下载 DanTagGen 模型" # DanTagGen(1.53g) OFF
__term_sd_task_pre_ext_8 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/a1111-sd-webui-dtg/ggml-model-Q6_K.gguf "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI_DanTagGen/models
__term_sd_task_pre_ext_8 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/a1111-sd-webui-dtg/ggml-model-Q8_0.gguf "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI_DanTagGen/models
__term_sd_task_pre_ext_8 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/a1111-sd-webui-dtg/ggml-model-f16.gguf "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI_DanTagGen/models
__term_sd_task_pre_ext_9 term_sd_echo "下载 Comfyui-StableSR 模型" # StableSR(422.3m) ON
__term_sd_task_pre_ext_9 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-stablesr/webui_768v_139.ckpt "${COMFYUI_ROOT_PATH}"/models/stablesr
__term_sd_task_pre_ext_10 term_sd_echo "下载 z-tipo-extension 模型" # z-tipo-extension(1.42g) ON
__term_sd_task_pre_ext_10 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/z-tipo-extension/TIPO-500M_epoch5-F16.gguf "${COMFYUI_ROOT_PATH}"/models/kgen
__term_sd_task_pre_ext_10 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/z-tipo-extension/TIPO-200M-40Btok-F16.gguf "${COMFYUI_ROOT_PATH}"/models/kgen
__term_sd_task_pre_ext_10 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/z-tipo-extension/TIPO-200M-ft-F16.gguf "${COMFYUI_ROOT_PATH}"/models/kgen
|
2301_81996401/term-sd
|
install/comfyui/comfyui_custom_node_hf_model.sh
|
Shell
|
agpl-3.0
| 25,971
|
__term_sd_task_pre_ext_1 term_sd_echo "下载 Controlnet 模型中" # ControlNet(25.93g) ON
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11e_sd15_ip2p_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11e_sd15_shuffle_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11f1e_sd15_tile_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11f1p_sd15_depth_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_canny_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_inpaint_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_lineart_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_mlsd_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_normalbae_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_openpose_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_scribble_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_seg_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_softedge_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15s2_lineart_anime_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v1p_sd15_brightness.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v1p_sd15_illumination.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v1p_sd15_qrcode_monster.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/sd_control_collection/master/xinsir-controlnet-union-sdxl-1.0-promax.safetensors "${COMFYUI_ROOT_PATH}"/models/controlnet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/LayerNorm/DensePose-TorchScript-with-hint-image/densepose_r101_fpn_dl.torchscript "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/LayerNorm/DensePose-TorchScript-with-hint-image
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/LayerNorm/DensePose-TorchScript-with-hint-image/densepose_r50_fpn_dl.torchscript "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/LayerNorm/DensePose-TorchScript-with-hint-image
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/LiheYoung/Depth-Anything/checkpoints/depth_anything_vitl14.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/LiheYoung/Depth-Anything/checkpoints
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/LiheYoung/Depth-Anything/checkpoints_metric_depth/depth_anything_metric_depth_indoor.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/LiheYoung/Depth-Anything/checkpoints_metric_depth
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/bdsqlsz/qinglong_controlnet-lllite/Annotators/7_model.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/bdsqlsz/qinglong_controlnet-lllite/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/bdsqlsz/qinglong_controlnet-lllite/Annotators/UNet.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/bdsqlsz/qinglong_controlnet-lllite/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/dhkim2810/MobileSAM/mobile_sam.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/hr16/ControlNet-HandRefiner-pruned/graphormer_hand_state_dict.bin "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/hr16/ControlNet-HandRefiner-pruned/hrnetv2_w64_imagenet_pretrained.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/hr16/DWPose-TorchScript-BatchSize5/dw-ll_ucoco_384_bs5.torchscript.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/hr16/DWPose-TorchScript-BatchSize5/rtmpose-m_ap10k_256_bs5.torchscript.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/hr16/UnJIT-DWPose/dw-ll_ucoco.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/UnJIT-DWPose
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/hr16/UnJIT-DWPose/rtmpose-m_ap10k_256.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/UnJIT-DWPose
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/hr16/yolo-nas-fp16/yolo_nas_l_fp16.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/yolo-nas-fp16
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/hr16/yolo-nas-fp16/yolo_nas_m_fp16.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/yolo-nas-fp16
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/hr16/yolo-nas-fp16/yolo_nas_s_fp16.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/yolo-nas-fp16
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/hr16/yolox-onnx/yolox_l.torchscript.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/hr16/yolox-onnx
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/150_16_swin_l_oneformer_coco_100ep.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/250_16_swin_l_oneformer_ade20k_160k.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/ControlNetHED.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/ZoeD_M12_N.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/body_pose_model.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/dpt_hybrid-midas-501f0c75.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/dw-ll_ucoco_384.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/erika.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/facenet.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/hand_pose_model.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/latest_net_G.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/mlsd_large_512_fp32.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/netG.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/res101.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/scannet.pt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/sk_model.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/sk_model2.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/table5_pidinet.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/upernet_global_small.pth "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/lllyasviel/Annotators/yolox_l.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/lllyasviel/Annotators
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/skytnt/anime-seg/isnetis.ckpt "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/skytnt/anime-seg
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/yzd-v/DWPose/dw-ll_ucoco_384.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/yzd-v/DWPose
__term_sd_task_pre_ext_1 get_modelscope_model licyks/comfyui-extension-models/master/comfyui_controlnet_aux/yzd-v/DWPose/yolox_l.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/comfyui_controlnet_aux/ckpts/yzd-v/DWPose
__term_sd_task_pre_ext_2 term_sd_echo "下载 Animatediff 模型中" # AnimateDiff(1.67g) OFF
__term_sd_task_pre_ext_2 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-animatediff/v3_sd15_mm.ckpt "${COMFYUI_ROOT_PATH}"/models/animatediff_models
__term_sd_task_pre_ext_3 term_sd_echo "下载 IP-Adapter 模型中" # IP-Adapter(9.63g) ON
__term_sd_task_pre_ext_3 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter_sd15.pth "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter_sd15_light.pth "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter_sd15_plus.pth "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter_sd15_vit-G.safetensors "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter_sdxl.safetensors "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter-plus_sdxl_vit-h.safetensors "${COMFYUI_ROOT_PATH}"/models/ipadapter
__term_sd_task_pre_ext_3 get_modelscope_model licyks/controlnet_v1.1_annotator/master/clip_vision/clip_g.pth "${COMFYUI_ROOT_PATH}"/models/clip_vision
__term_sd_task_pre_ext_3 get_modelscope_model licyks/controlnet_v1.1_annotator/master/clip_vision/clip_h.pth "${COMFYUI_ROOT_PATH}"/models/clip_vision
__term_sd_task_pre_ext_3 get_modelscope_model licyks/controlnet_v1.1_annotator/master/clip_vision/clip_vitl.pth "${COMFYUI_ROOT_PATH}"/models/clip_vision
__term_sd_task_pre_ext_4 term_sd_echo "下载 ComfyUI-Impact-Pack 模型中" # ComfyUI-Impact-Pack(750m) ON
__term_sd_task_pre_ext_4 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Impact-Pack/face_yolov8m.pt "${COMFYUI_ROOT_PATH}"/models/ultralytics/bbox
__term_sd_task_pre_ext_4 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Impact-Pack/mmdet_anime-face_yolov3.pth "${COMFYUI_ROOT_PATH}"/models/ultralytics/bbox
__term_sd_task_pre_ext_4 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Impact-Pack/sam_vit_b_01ec64.pth "${COMFYUI_ROOT_PATH}"/models/sams
__term_sd_task_pre_ext_4 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Impact-Pack/hand_yolov8s.pt "${COMFYUI_ROOT_PATH}"/models/ultralytics/bbox
__term_sd_task_pre_ext_4 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Impact-Pack/person_yolov8m-seg.pt "${COMFYUI_ROOT_PATH}"/models/ultralytics/segm
__term_sd_task_pre_ext_5 term_sd_echo "下载 ComfyUI-Marigold 模型中" # ComfyUI-Marigold(5.15g) OFF
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/model_index.json "${COMFYUI_ROOT_PATH}"/diffusers
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/scheduler/scheduler_config.json "${COMFYUI_ROOT_PATH}"/diffusers/scheduler
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/text_encoder/config.json "${COMFYUI_ROOT_PATH}"/diffusers/text_encoder
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/text_encoder/model.safetensors "${COMFYUI_ROOT_PATH}"/diffusers/text_encoder
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/tokenizer/merges.txt "${COMFYUI_ROOT_PATH}"/diffusers/tokenizer
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/tokenizer/special_tokens_map.json "${COMFYUI_ROOT_PATH}"/diffusers/tokenizer
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/tokenizer/tokenizer_config.json "${COMFYUI_ROOT_PATH}"/diffusers/tokenizer
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/tokenizer/vocab.json "${COMFYUI_ROOT_PATH}"/diffusers/tokenizer
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/unet/config.json "${COMFYUI_ROOT_PATH}"/diffusers/unet
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/unet/diffusion_pytorch_model.safetensors "${COMFYUI_ROOT_PATH}"/diffusers/unet
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/vae/config.json "${COMFYUI_ROOT_PATH}"/diffusers/vae
__term_sd_task_pre_ext_5 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-Marigold/vae/diffusion_pytorch_model.safetensors "${COMFYUI_ROOT_PATH}"/diffusers/vae
__term_sd_task_pre_ext_6 term_sd_echo "下载 ComfyUI-WD14-Tagger 模型中" # ComfyUI-WD14-Tagger(3.09g) ON
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-v1-4-convnext-tagger-v2.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-v1-4-convnext-tagger-v2.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-v1-4-convnext-tagger.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-v1-4-convnext-tagger.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-v1-4-convnextv2-tagger-v2.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-v1-4-convnextv2-tagger-v2.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-v1-4-moat-tagger-v2.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-v1-4-moat-tagger-v2.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-v1-4-vit-tagger-v2.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-v1-4-vit-tagger-v2.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-convnext-tagger-v3.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-convnext-tagger-v3.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-swinv2-tagger-v3.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-swinv2-tagger-v3.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-vit-tagger-v3.csv "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/comfyui-extension-models/master/ComfyUI-WD14-Tagger/wd-vit-tagger-v3.onnx "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI-WD14-Tagger/models
__term_sd_task_pre_ext_7 term_sd_echo "下载 ComfyUI-LayerDiffusion 模型" # LayerDiffusion(10.29g) ON
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_bg2ble.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_bgble2fg.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_fg2ble.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_fgble2bg.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_transparent_attn.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_transparent_conv.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/vae_transparent_decoder.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/vae_transparent_encoder.safetensors "${COMFYUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_8 term_sd_echo "下载 DanTagGen 模型" # DanTagGen(1.53g) OFF
__term_sd_task_pre_ext_8 get_modelscope_model licyks/sd-extensions-model/master/a1111-sd-webui-dtg/ggml-model-Q6_K.gguf "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI_DanTagGen/models
__term_sd_task_pre_ext_8 get_modelscope_model licyks/sd-extensions-model/master/a1111-sd-webui-dtg/ggml-model-Q8_0.gguf "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI_DanTagGen/models
__term_sd_task_pre_ext_8 get_modelscope_model licyks/sd-extensions-model/master/a1111-sd-webui-dtg/ggml-model-f16.gguf "${COMFYUI_ROOT_PATH}"/custom_nodes/ComfyUI_DanTagGen/models
__term_sd_task_pre_ext_9 term_sd_echo "下载 Comfyui-StableSR 模型" # StableSR(422.3m) ON
__term_sd_task_pre_ext_9 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-stablesr/webui_768v_139.ckpt "${COMFYUI_ROOT_PATH}"/models/stablesr
__term_sd_task_pre_ext_10 term_sd_echo "下载 z-tipo-extension 模型" # z-tipo-extension(1.02g) ON
__term_sd_task_pre_ext_10 get_modelscope_model licyks/sd-extensions-model/master/z-tipo-extension/TIPO-500M_epoch5-F16.gguf "${COMFYUI_ROOT_PATH}"/models/kgen
__term_sd_task_pre_ext_10 get_modelscope_model licyks/sd-extensions-model/master/z-tipo-extension/TIPO-200M-40Btok-F16.gguf "${COMFYUI_ROOT_PATH}"/models/kgen
__term_sd_task_pre_ext_10 get_modelscope_model licyks/sd-extensions-model/master/z-tipo-extension/TIPO-200M-ft-F16.gguf "${COMFYUI_ROOT_PATH}"/models/kgen
|
2301_81996401/term-sd
|
install/comfyui/comfyui_custom_node_ms_model.sh
|
Shell
|
agpl-3.0
| 23,447
|
__term_sd_task_pre_ext_1 git_clone_repository https://github.com/diffus3/ComfyUI-extensions "${COMFYUI_ROOT_PATH}"/web/extensions OFF # ComfyUI插件扩展
__term_sd_task_pre_ext_2 git_clone_repository https://github.com/rock-land/graphNavigator "${COMFYUI_ROOT_PATH}"/web/extensions OFF # 节点辅助插件
|
2301_81996401/term-sd
|
install/comfyui/comfyui_extension.sh
|
Shell
|
agpl-3.0
| 309
|
__term_sd_task_pre_model_1 # =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/v1-5-pruned-emaonly.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/animefull-final-pruned.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/nai1-artist_all_in_one_merge.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # nai1-artist_all_in_one_merge(2.13g) OFF
__term_sd_task_pre_model_5 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/Counterfeit-V3.0_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Counterfeit-V3.0(4.24g) OFF
__term_sd_task_pre_model_6 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/cetusMix_Whalefall2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # cetusMix_Whalefall2(3.85g) OFF
__term_sd_task_pre_model_7 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/cuteyukimixAdorable_neochapter3.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # cuteyukimixAdorable_neochapter3(2.3g) OFF
__term_sd_task_pre_model_8 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/ekmix-pastel-fp16-no-ema.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # ekmix-pastel(2.13g) OFF
__term_sd_task_pre_model_9 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/ex2K_sse2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # ex2K_sse2(2.38g) OFF
__term_sd_task_pre_model_10 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/kohakuV5_rev2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohakuV5_rev2(2.13g) OFF
__term_sd_task_pre_model_11 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/meinamix_meinaV11.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # meinamix_meinaV11(2.13g) OFF
__term_sd_task_pre_model_12 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/oukaStar_10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # oukaStar_10(5.43g) OFF
__term_sd_task_pre_model_13 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/pastelMixStylizedAnime_pastelMixPrunedFP16.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # pastelMixStylizedAnime(2.13g) OFF
__term_sd_task_pre_model_14 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/rabbit_v6.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # rabbit_v6(1.97g) OFF
__term_sd_task_pre_model_15 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/sweetSugarSyndrome_rev15.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sweetSugarSyndrome_rev15(2.13g) OFF
__term_sd_task_pre_model_16 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/AnythingV5Ink_ink.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # AnythingV5Ink_ink(2.13g) OFF
__term_sd_task_pre_model_17 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/bartstyledbBlueArchiveArtStyleFineTunedModel_v10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # bartstyledbBlueArchiveArtStyle(2.13g) OFF
__term_sd_task_pre_model_18 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/meinapastel_v6Pastel.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # meinapastel_v6(2.13g) OFF
__term_sd_task_pre_model_19 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/qteamixQ_omegaFp16.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # qteamix(2.13g) OFF
__term_sd_task_pre_model_20 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/tmndMix_tmndMixSPRAINBOW.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # tmndMix(2.13g) OFF
__term_sd_task_pre_model_21 # =====SD2.1大模型===== OFF
__term_sd_task_pre_model_22 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/v2-1_768-ema-pruned.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_23 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/wd-1-4-anime_e2.ckpt "${COMFYUI_ROOT_PATH}"/models/checkpoints # wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_24 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/wd-mofu-fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_25 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_26 aria2_download https://huggingface.co/licyk/sd-lora/resolve/main/sdxl/sd_xl_offset_example-lora_1.0.safetensors "${COMFYUI_ROOT_PATH}"/models/loras # sd_xl_offset_example-lora_1.0(49.6m) OFF
__term_sd_task_pre_model_27 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_base_1.0_0.9vae.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_28 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_refiner_1.0_0.9vae.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_29 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_turbo_1.0_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_30 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/cosxl.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # cosxl(6.94g) OFF
__term_sd_task_pre_model_31 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/cosxl_edit.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_32 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.0-base.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_33 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_34 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_35 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_36 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0-opt.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_37 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0-zero.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_38 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/holodayo-xl-2.1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_39 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kivotos-xl-2.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_40 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/clandestine-xl-1.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_41 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/UrangDiffusion-1.1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_42 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/RaeDiffusion-XL-v2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_43 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_anime_V52.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_44 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-delta-rev1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_45 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohakuXLEpsilon_rev1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_46 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-epsilon-rev2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_47 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-epsilon-rev3.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_48 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-zeta.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_49 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/starryXLV52_v52.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_50 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/heartOfAppleXL_v20.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_51 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/heartOfAppleXL_v30.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_52 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/baxlBartstylexlBlueArchiveFlatCelluloid_xlv1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_53 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/baxlBlueArchiveFlatCelluloidStyle_xlv3.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_54 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sanaexlAnimeV10_v10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_55 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sanaexlAnimeV10_v11.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_56 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/SanaeXL-Anime-v1.2-aesthetic.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_57 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/SanaeXL-Anime-v1.3-aesthetic.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_58 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v0.1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_59 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v0.1-GUIDED.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_60 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v1.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_61 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v1.1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_62 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v2.0-stable.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_63 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v2.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_64 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/jruTheJourneyRemains_v25XL.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_65 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_illustriousxl10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_66 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/miaomiaoHarem_v15a.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_67 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/waiNSFWIllustrious_v80.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_68 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/tIllunai3_v4.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_69 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_earlyAccessVersion.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_70 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred05Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_71 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred075.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_72 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred077.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_73 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred10Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_74 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred11Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_75 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPredTestVersion.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_76 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred05Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_77 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred06Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_78 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred065SVersion.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_79 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred075SVersion.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_80 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred09RVersion.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_81 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred10Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_82 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_nbxl12.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_83 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_nbxlVPredV10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_84 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/ponyDiffusionV6XL_v6StartWithThisOne.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_85 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/pdForAnime_v20.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_86 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/tPonynai3_v51WeightOptimized.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_87 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/omegaPonyXLAnime_v20.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_88 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animeIllustDiffusion_v061.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_89 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/artiwaifuDiffusion_v10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_90 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/artiwaifu-diffusion-v2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_91 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/AnythingXL_xl.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_92 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/abyssorangeXLElse_v10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_93 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animaPencilXL_v200.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_94 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/bluePencilXL_v401.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_95 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/nekorayxl_v06W3.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_96 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/CounterfeitXL-V1.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_97 # =====SD3大模型===== OFF
__term_sd_task_pre_model_98 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3_medium.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3_medium(4.34g) OFF
__term_sd_task_pre_model_99 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3_medium_incl_clips.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3_medium_incl_clips(5.97g) OFF
__term_sd_task_pre_model_100 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3_medium_incl_clips_t5xxlfp8.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3_medium_incl_clips_t5xxlfp8(10.87g) OFF
__term_sd_task_pre_model_101 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3.5_large.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3.5_large(16.5g) OFF
__term_sd_task_pre_model_102 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3.5_large_fp8_scaled.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3.5_large_fp8_scaled(14.9g) OFF
__term_sd_task_pre_model_103 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3.5_large_turbo.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3.5_large_turbo(16.5g) OFF
__term_sd_task_pre_model_104 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3.5_medium.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3.5_medium(5.1g) OFF
__term_sd_task_pre_model_105 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3.5_medium_incl_clips_t5xxlfp8scaled.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3.5_medium_incl_clips_t5xxlfp8scaled(11.6g) OFF
__term_sd_task_pre_model_106 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/emi3.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # emi3(16.5g) OFF
__term_sd_task_pre_model_107 # =====SD3文本编码器===== OFF
__term_sd_task_pre_model_108 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/text_encoders/clip_g.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # clip_g(1.39g) OFF
__term_sd_task_pre_model_109 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/text_encoders/clip_l.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # clip_l(246.1m) OFF
__term_sd_task_pre_model_110 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/text_encoders/t5xxl_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_111 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/text_encoders/t5xxl_fp8_e4m3fn.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_112 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/text_encoders/t5xxl_fp8_e4m3fn_scaled.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5xxl_fp8_e4m3fn_scaled(5.16g) OFF
__term_sd_task_pre_model_113 # =====HunyuanDiT===== OFF
__term_sd_task_pre_model_114 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/hunyuan_dit_comfyui/hunyuan_dit_1.2.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # hunyuan_dit_1.2(8.24g) OFF
__term_sd_task_pre_model_115 aria2_download https://huggingface.co/licyk/comfyui-extension-models/resolve/main/hunyuan_dit_comfyui/comfy_freeway_animation_hunyuan_dit_180w.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # comfy_freeway_animation_hunyuan_dit_180w(8.24g) OFF
__term_sd_task_pre_model_116 # =====FLUX模型===== OFF
__term_sd_task_pre_model_117 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev(23.8g) OFF
__term_sd_task_pre_model_118 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-fp8.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # flux1-dev-fp8(17.2g) OFF
__term_sd_task_pre_model_119 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux_dev_fp8_scaled_diffusion_model.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # flux_dev_fp8_scaled_diffusion_model(11.9g) OFF
__term_sd_task_pre_model_120 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-bnb-nf4-v2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # flux1-dev-bnb-nf4-v2(12g) OFF
__term_sd_task_pre_model_121 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-bnb-nf4.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # flux1-dev-bnb-nf4(11.5g) OFF
__term_sd_task_pre_model_122 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q2_K.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q2_K-gguf(4.03g) OFF
__term_sd_task_pre_model_123 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q3_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q3_K_S-gguf(5.23g) OFF
__term_sd_task_pre_model_124 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q4_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q4_0-gguf(6.79g) OFF
__term_sd_task_pre_model_125 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q4_1.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q4_1-gguf(7.53g) OFF
__term_sd_task_pre_model_126 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q4_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q4_K_S-gguf(6.81g) OFF
__term_sd_task_pre_model_127 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q5_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q5_0-gguf(8.27g) OFF
__term_sd_task_pre_model_128 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q5_1.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q5_1-gguf(9.01g) OFF
__term_sd_task_pre_model_129 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q5_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q5_K_S-gguf(8.29g) OFF
__term_sd_task_pre_model_130 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q6_K.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q6_K-gguf(9.86g) OFF
__term_sd_task_pre_model_131 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q8_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_132 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-F16.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_133 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_134 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-fp8.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # flux1-schnell-fp8(17.2g) OFF
__term_sd_task_pre_model_135 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q2_K.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q2_K-gguf(4.01g) OFF
__term_sd_task_pre_model_136 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q3_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q3_K_S-gguf(5.21g) OFF
__term_sd_task_pre_model_137 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q4_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q4_0-gguf(6.77g) OFF
__term_sd_task_pre_model_138 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q4_1.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q4_1-gguf(7.51g) OFF
__term_sd_task_pre_model_139 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q4_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q4_K_S-gguf(6.78g) OFF
__term_sd_task_pre_model_140 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q5_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q5_0-gguf(8.25g) OFF
__term_sd_task_pre_model_141 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q5_1.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q5_1-gguf(8.99g) OFF
__term_sd_task_pre_model_142 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q5_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q5_K_S-gguf(8.26g) OFF
__term_sd_task_pre_model_143 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q6_K.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q6_K-gguf(9.83g) OFF
__term_sd_task_pre_model_144 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q8_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_145 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-F16.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_146 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/ashen0209-flux1-dev2pro.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_147 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/jimmycarter-LibreFLUX.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_148 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/nyanko7-flux-dev-de-distill.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_149 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/shuttle-3-diffusion.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_150 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-krea-dev_fp8_scaled.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-krea-dev_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_151 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-krea-dev.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-krea-dev(23.8g) OFF
__term_sd_task_pre_model_152 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-kontext_fp8_scaled.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-kontext_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_153 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-kontext-dev.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-kontext-dev(23.8g) OFF
__term_sd_task_pre_model_154 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/chroma-unlocked-v50.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # chroma-unlocked-v50(23.8g) OFF
__term_sd_task_pre_model_155 # =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_156 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/clip_l.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # clip_l(246.1m) OFF
__term_sd_task_pre_model_157 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5xxl_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_158 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5xxl_fp8_e4m3fn.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_159 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_L.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q3_K_L-gguf(2.46g) OFF
__term_sd_task_pre_model_160 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_M.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q3_K_M-gguf(2.3g) OFF
__term_sd_task_pre_model_161 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q3_K_S-gguf(2.1g) OFF
__term_sd_task_pre_model_162 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q4_K_M.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q4_K_M-gguf(2.9g) OFF
__term_sd_task_pre_model_163 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q4_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q4_K_S-gguf(2.74g) OFF
__term_sd_task_pre_model_164 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q5_K_M.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q5_K_M-gguf(3.39g) OFF
__term_sd_task_pre_model_165 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q5_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q5_K_S-gguf(3.29g) OFF
__term_sd_task_pre_model_166 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q6_K.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q6_K-gguf(3.91g) OFF
__term_sd_task_pre_model_167 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q8_0.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q8_0-gguf(5.06g) OFF
__term_sd_task_pre_model_168 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-f16.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-f16-gguf(9.53g) OFF
__term_sd_task_pre_model_169 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-f32.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-f32-gguf(19.1g) OFF
__term_sd_task_pre_model_170 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_vae/ae.safetensors "${COMFYUI_ROOT_PATH}"/models/vae # ae(335m) OFF
__term_sd_task_pre_model_171 # =====VAE模型===== OFF
__term_sd_task_pre_model_172 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sd_1.5/vae-ft-ema-560000-ema-pruned.safetensors "${COMFYUI_ROOT_PATH}"/models/vae # vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_173 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sd_1.5/vae-ft-mse-840000-ema-pruned.safetensors "${COMFYUI_ROOT_PATH}"/models/vae # vae-ft-mse-840000-ema-pruned(334.6m) ON
__term_sd_task_pre_model_174 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sdxl_1.0/sdxl_vae.safetensors "${COMFYUI_ROOT_PATH}"/models/vae # sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_175 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sdxl_1.0/sdxl_fp16_fix_vae.safetensors "${COMFYUI_ROOT_PATH}"/models/vae # sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_176 # =====VAE-approx模型===== OFF
__term_sd_task_pre_model_177 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/vae-approx/model.pt "${COMFYUI_ROOT_PATH}"/models/vae_approx # VAE-approx模型 model(0.2m) ON
__term_sd_task_pre_model_178 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/vae-approx/vaeapprox-sdxl.pt "${COMFYUI_ROOT_PATH}"/models/vae_approx # vaeapprox-sdxl(0.2m) ON
__term_sd_task_pre_model_179 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/vae-approx/vaeapprox-sd3.pt "${COMFYUI_ROOT_PATH}"/models/vae_approx # vaeapprox-sd3(0.2m) OFF
__term_sd_task_pre_model_180 # =====放大模型===== OFF
__term_sd_task_pre_model_181 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/Codeformer/codeformer-v0.1.0.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # codeformer-v0.1.0(376.6m) OFF
__term_sd_task_pre_model_182 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_2_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_2_x2(139.7m) OFF
__term_sd_task_pre_model_183 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_2_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_2_x3(140.4m) OFF
__term_sd_task_pre_model_184 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_2_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_2_x4(140.3m) OFF
__term_sd_task_pre_model_185 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_S_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_S_x2(87.7m) OFF
__term_sd_task_pre_model_186 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_S_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_S_x3(88.4m) OFF
__term_sd_task_pre_model_187 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_S_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_S_x4(88.2m) OFF
__term_sd_task_pre_model_188 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_light_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_light_x2(45.7m) OFF
__term_sd_task_pre_model_189 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_light_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_light_x3(45.7m) OFF
__term_sd_task_pre_model_190 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_light_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_light_x4(45.8m) OFF
__term_sd_task_pre_model_191 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_x2(154.1m) OFF
__term_sd_task_pre_model_192 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_x3(154.8m) OFF
__term_sd_task_pre_model_193 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_x4(154.7m) OFF
__term_sd_task_pre_model_194 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/16xPSNR.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 16xPSNR(67.2m) OFF
__term_sd_task_pre_model_195 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x-ITF-SkinDiffDetail-Lite-v1.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x-ITF-SkinDiffDetail-Lite-v1(20.1m) OFF
__term_sd_task_pre_model_196 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x_NMKD-BrightenRedux_200k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x_NMKD-BrightenRedux_200k(66.6m) OFF
__term_sd_task_pre_model_197 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x_NMKD-YandereInpaint_375000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x_NMKD-YandereInpaint_375000_G(66.6m) OFF
__term_sd_task_pre_model_198 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x_NMKDDetoon_97500_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x_NMKDDetoon_97500_G(66.6m) OFF
__term_sd_task_pre_model_199 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x_NoiseToner-Poisson-Detailed_108000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x_NoiseToner-Poisson-Detailed_108000_G(66.6m) OFF
__term_sd_task_pre_model_200 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x_NoiseToner-Uniform-Detailed_100000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x_NoiseToner-Uniform-Detailed_100000_G(66.6m) OFF
__term_sd_task_pre_model_201 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x-UltraSharp.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x-UltraSharp(66.9m) OFF
__term_sd_task_pre_model_202 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4xPSNR.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4xPSNR(66.9m) OFF
__term_sd_task_pre_model_203 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_CountryRoads_377000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_CountryRoads_377000_G(66.9m) OFF
__term_sd_task_pre_model_204 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_Fatality_Comix_260000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_Fatality_Comix_260000_G(66.9m) OFF
__term_sd_task_pre_model_205 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-Siax_200k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-Siax_200k(66.9m) OFF
__term_sd_task_pre_model_206 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-Superscale-Artisoftject_210000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-Superscale-Artisoftject_210000_G(66.9m) OFF
__term_sd_task_pre_model_207 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-Superscale-SP_178000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-Superscale-SP_178000_G(66.9m) ON
__term_sd_task_pre_model_208 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-UltraYandere-Lite_280k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-UltraYandere-Lite_280k(20.1m) OFF
__term_sd_task_pre_model_209 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-UltraYandere_300k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-UltraYandere_300k(66.9m) OFF
__term_sd_task_pre_model_210 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-YandereNeoXL_200k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-YandereNeoXL_200k(66.9m) OFF
__term_sd_task_pre_model_211 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKDSuperscale_Artisoft_120000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKDSuperscale_Artisoft_120000_G(67.1m) OFF
__term_sd_task_pre_model_212 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NickelbackFS_72000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NickelbackFS_72000_G(67.1m) OFF
__term_sd_task_pre_model_213 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_Nickelback_70000G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_Nickelback_70000G(66.9m) OFF
__term_sd_task_pre_model_214 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_RealisticRescaler_100000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_RealisticRescaler_100000_G(134.1m) OFF
__term_sd_task_pre_model_215 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_Valar_v1.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_Valar_v1(67.5m) OFF
__term_sd_task_pre_model_216 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_fatal_Anime_500000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_fatal_Anime_500000_G(66.9m) OFF
__term_sd_task_pre_model_217 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_foolhardy_Remacri.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_foolhardy_Remacri(67m) OFF
__term_sd_task_pre_model_218 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/8xPSNR.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 8xPSNR(67.1m) OFF
__term_sd_task_pre_model_219 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/8x_NMKD-Superscale_150000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 8x_NMKD-Superscale_150000_G(67.1m) OFF
__term_sd_task_pre_model_220 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/8x_NMKD-Typescale_175k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 8x_NMKD-Typescale_175k(67.1m) OFF
__term_sd_task_pre_model_221 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/A_ESRGAN_Single.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # A_ESRGAN_Single(134.1m) OFF
__term_sd_task_pre_model_222 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/BSRGAN.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # BSRGAN(67.1m) OFF
__term_sd_task_pre_model_223 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/BSRGANx2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # BSRGANx2(66.8m) OFF
__term_sd_task_pre_model_224 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/BSRNet.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # BSRNet(67.1m) OFF
__term_sd_task_pre_model_225 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/ESRGAN_4x.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # ESRGAN_4x(66.9m) OFF
__term_sd_task_pre_model_226 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/LADDIER1_282500_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # LADDIER1_282500_G(66.9m) OFF
__term_sd_task_pre_model_227 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Neutral_115000_swaG.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_UniversalUpscalerV2-Neutral_115000_swaG(66.9m) OFF
__term_sd_task_pre_model_228 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Sharp_101000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_UniversalUpscalerV2-Sharp_101000_G(66.9m) OFF
__term_sd_task_pre_model_229 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Sharper_103000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_UniversalUpscalerV2-Sharper_103000_G(66.9m) OFF
__term_sd_task_pre_model_230 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/UniversalUpscaler/Legacy/4x_UniversalUpscaler-Detailed_155000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_UniversalUpscaler-Detailed_155000_G(66.9m) OFF
__term_sd_task_pre_model_231 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/UniversalUpscaler/Legacy/4x_UniversalUpscaler-Soft_190000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_UniversalUpscaler-Soft_190000_G(66.9m) OFF
__term_sd_task_pre_model_232 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/WaifuGAN_v3_30000.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # WaifuGAN_v3_30000(66.9m) OFF
__term_sd_task_pre_model_233 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/lollypop.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # lollypop(66.9m) OFF
__term_sd_task_pre_model_234 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/sudo_rife4_269.662_testV1_scale1.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # sudo_rife4_269.662_testV1_scale1(33.7m) OFF
__term_sd_task_pre_model_235 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/GFPGAN/GFPGANv1.3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # GFPGANv1.3(348.6m) OFF
__term_sd_task_pre_model_236 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/GFPGAN/GFPGANv1.4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # GFPGANv1.4(348.6m) OFF
__term_sd_task_pre_model_237 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/GFPGAN/detection_Resnet50_Final.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # detection_Resnet50_Final(109.5m) OFF
__term_sd_task_pre_model_238 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/GFPGAN/parsing_bisenet.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # parsing_bisenet(12.2m) OFF
__term_sd_task_pre_model_239 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/GFPGAN/parsing_parsenet.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # parsing_parsenet(85.3m) OFF
__term_sd_task_pre_model_240 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/RealESRGAN/RealESRGAN_x4plus.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # RealESRGAN_x4plus(67m) ON
__term_sd_task_pre_model_241 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/RealESRGAN/RealESRGAN_x4plus_anime_6B.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # RealESRGAN_x4plus_anime_6B(17.9m) ON
__term_sd_task_pre_model_242 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DF2K_s64w8_SwinIR-M_x2(67.2m) OFF
__term_sd_task_pre_model_243 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DF2K_s64w8_SwinIR-M_x3(68m) OFF
__term_sd_task_pre_model_244 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DF2K_s64w8_SwinIR-M_x4(67.8m) OFF
__term_sd_task_pre_model_245 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x8.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DF2K_s64w8_SwinIR-M_x8(68.4m) OFF
__term_sd_task_pre_model_246 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x2(59m) OFF
__term_sd_task_pre_model_247 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x3(59.7m) OFF
__term_sd_task_pre_model_248 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x4(59.6m) OFF
__term_sd_task_pre_model_249 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x8.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x8(60.2m) OFF
__term_sd_task_pre_model_250 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/Swin2SR_ClassicalSR_X2_64.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # Swin2SR_ClassicalSR_X2_64(68.7m) OFF
__term_sd_task_pre_model_251 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/Swin2SR_ClassicalSR_X4_64.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # Swin2SR_ClassicalSR_X4_64(69.3m) OFF
__term_sd_task_pre_model_252 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/Swin2SR_CompressedSR_X4_48.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # Swin2SR_CompressedSR_X4_48(61.1m) OFF
__term_sd_task_pre_model_253 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR(68.6m) OFF
__term_sd_task_pre_model_254 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/SwinIR_4x.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # SwinIR_4x(142.4m) OFF
__term_sd_task_pre_model_255 # =====Embedding模型===== OFF
__term_sd_task_pre_model_256 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/EasyNegativeV2.safetensors "${COMFYUI_ROOT_PATH}"/models/embeddings # embeddings模型 EasyNegativeV2(0.1m) ON
__term_sd_task_pre_model_257 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/bad-artist-anime.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # bad-artist-anime(0.1m) ON
__term_sd_task_pre_model_258 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/bad-artist.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # bad-artist(0.1m) ON
__term_sd_task_pre_model_259 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/bad-hands-5.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # bad-hands-5(0.1m) ON
__term_sd_task_pre_model_260 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/bad-image-v2-39000.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # bad-image-v2-39000(0.1m) ON
__term_sd_task_pre_model_261 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/bad_prompt_version2.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # bad_prompt_version2(0.1m) ON
__term_sd_task_pre_model_262 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/ng_deepnegative_v1_75t.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # ng_deepnegative_v1_75t(0.1m) ON
__term_sd_task_pre_model_263 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/verybadimagenegative_v1.3.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # verybadimagenegative_v1.3(0.1m) ON
|
2301_81996401/term-sd
|
install/comfyui/comfyui_hf_model.sh
|
Shell
|
agpl-3.0
| 54,805
|
__term_sd_task_pre_model_1 # =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 get_modelscope_model licyks/sd-model/master/sd_1.5/v1-5-pruned-emaonly.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 get_modelscope_model licyks/sd-model/master/sd_1.5/animefull-final-pruned.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 get_modelscope_model licyks/sd-model/master/sd_1.5/nai1-artist_all_in_one_merge.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # nai1-artist_all_in_one_merge(2.13g) OFF
__term_sd_task_pre_model_5 get_modelscope_model licyks/sd-model/master/sd_1.5/Counterfeit-V3.0_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Counterfeit-V3.0(4.24g) OFF
__term_sd_task_pre_model_6 get_modelscope_model licyks/sd-model/master/sd_1.5/cetusMix_Whalefall2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # cetusMix_Whalefall2(3.85g) OFF
__term_sd_task_pre_model_7 get_modelscope_model licyks/sd-model/master/sd_1.5/cuteyukimixAdorable_neochapter3.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # cuteyukimixAdorable_neochapter3(2.3g) OFF
__term_sd_task_pre_model_8 get_modelscope_model licyks/sd-model/master/sd_1.5/ekmix-pastel-fp16-no-ema.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # ekmix-pastel(2.13g) OFF
__term_sd_task_pre_model_9 get_modelscope_model licyks/sd-model/master/sd_1.5/ex2K_sse2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # ex2K_sse2(2.38g) OFF
__term_sd_task_pre_model_10 get_modelscope_model licyks/sd-model/master/sd_1.5/kohakuV5_rev2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohakuV5_rev2(2.13g) OFF
__term_sd_task_pre_model_11 get_modelscope_model licyks/sd-model/master/sd_1.5/meinamix_meinaV11.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # meinamix_meinaV11(2.13g) OFF
__term_sd_task_pre_model_12 get_modelscope_model licyks/sd-model/master/sd_1.5/oukaStar_10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # oukaStar_10(5.43g) OFF
__term_sd_task_pre_model_13 get_modelscope_model licyks/sd-model/master/sd_1.5/pastelMixStylizedAnime_pastelMixPrunedFP16.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # pastelMixStylizedAnime(2.13g) OFF
__term_sd_task_pre_model_14 get_modelscope_model licyks/sd-model/master/sd_1.5/rabbit_v6.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # rabbit_v6(1.97g) OFF
__term_sd_task_pre_model_15 get_modelscope_model licyks/sd-model/master/sd_1.5/sweetSugarSyndrome_rev15.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sweetSugarSyndrome_rev15(1.97g) OFF
__term_sd_task_pre_model_16 get_modelscope_model licyks/sd-model/master/sd_1.5/AnythingV5Ink_ink.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # AnythingV5Ink_ink(1.97g) OFF
__term_sd_task_pre_model_17 get_modelscope_model licyks/sd-model/master/sd_1.5/bartstyledbBlueArchiveArtStyleFineTunedModel_v10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # bartstyledbBlueArchiveArtStyle(1.97g) OFF
__term_sd_task_pre_model_18 get_modelscope_model licyks/sd-model/master/sd_1.5/meinapastel_v6Pastel.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # meinapastel_v6(1.97g) OFF
__term_sd_task_pre_model_19 get_modelscope_model licyks/sd-model/master/sd_1.5/qteamixQ_omegaFp16.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # qteamix(1.97g) OFF
__term_sd_task_pre_model_20 get_modelscope_model licyks/sd-model/master/sd_1.5/tmndMix_tmndMixSPRAINBOW.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # tmndMix(1.97g) OFF
__term_sd_task_pre_model_21 # =====SD2.1大模型===== OFF
__term_sd_task_pre_model_22 get_modelscope_model licyks/sd-model/master/sd_2.1/v2-1_768-ema-pruned.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_23 get_modelscope_model licyks/sd-model/master/sd_2.1/wd-1-4-anime_e2.ckpt "${COMFYUI_ROOT_PATH}"/models/checkpoints # wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_24 get_modelscope_model licyks/sd-model/master/sd_2.1/wd-mofu-fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_25 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_26 get_modelscope_model licyks/sd-lora/master/sdxl/sd_xl_offset_example-lora_1.0.safetensors "${COMFYUI_ROOT_PATH}"/models/loras # sd_xl_offset_example-lora_1.0(49.6m) OFF
__term_sd_task_pre_model_27 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_base_1.0_0.9vae.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_28 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_refiner_1.0_0.9vae.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_29 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_turbo_1.0_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_30 get_modelscope_model licyks/sd-model/master/sdxl_1.0/cosxl.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # cosxl(6.94g) OFF
__term_sd_task_pre_model_31 get_modelscope_model licyks/sd-model/master/sdxl_1.0/cosxl_edit.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_32 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.0-base.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_33 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_34 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_35 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_36 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0-opt.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_37 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0-zero.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_38 get_modelscope_model licyks/sd-model/master/sdxl_1.0/holodayo-xl-2.1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_39 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kivotos-xl-2.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_40 get_modelscope_model licyks/sd-model/master/sdxl_1.0/clandestine-xl-1.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_41 get_modelscope_model licyks/sd-model/master/sdxl_1.0/UrangDiffusion-1.1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_42 get_modelscope_model licyks/sd-model/master/sdxl_1.0/RaeDiffusion-XL-v2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_43 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_anime_V52.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_44 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-delta-rev1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_45 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohakuXLEpsilon_rev1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_46 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-epsilon-rev2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_47 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-epsilon-rev3.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_48 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-zeta.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_49 get_modelscope_model licyks/sd-model/master/sdxl_1.0/starryXLV52_v52.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_50 get_modelscope_model licyks/sd-model/master/sdxl_1.0/heartOfAppleXL_v20.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_51 get_modelscope_model licyks/sd-model/master/sdxl_1.0/heartOfAppleXL_v30.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_52 get_modelscope_model licyks/sd-model/master/sdxl_1.0/baxlBartstylexlBlueArchiveFlatCelluloid_xlv1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_53 get_modelscope_model licyks/sd-model/master/sdxl_1.0/baxlBlueArchiveFlatCelluloidStyle_xlv3.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_54 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sanaexlAnimeV10_v10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_55 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sanaexlAnimeV10_v11.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_56 get_modelscope_model licyks/sd-model/master/sdxl_1.0/SanaeXL-Anime-v1.2-aesthetic.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_57 get_modelscope_model licyks/sd-model/master/sdxl_1.0/SanaeXL-Anime-v1.3-aesthetic.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_58 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v0.1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_59 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v0.1-GUIDED.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_60 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v1.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_61 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v1.1.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_62 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v2.0-stable.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_63 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v2.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_64 get_modelscope_model licyks/sd-model/master/sdxl_1.0/jruTheJourneyRemains_v25XL.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_65 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_illustriousxl10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_66 get_modelscope_model licyks/sd-model/master/sdxl_1.0/miaomiaoHarem_v15a.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_67 get_modelscope_model licyks/sd-model/master/sdxl_1.0/waiNSFWIllustrious_v80.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_68 get_modelscope_model licyks/sd-model/master/sdxl_1.0/tIllunai3_v4.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_69 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_earlyAccessVersion.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_70 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred05Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_71 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred075.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_72 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred077.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_73 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred10Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_74 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred11Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_75 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPredTestVersion.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_76 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred05Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_77 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred06Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_78 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred065SVersion.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_79 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred075SVersion.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_80 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred09RVersion.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_81 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred10Version.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_82 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_nbxl12.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_83 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_nbxlVPredV10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_84 get_modelscope_model licyks/sd-model/master/sdxl_1.0/ponyDiffusionV6XL_v6StartWithThisOne.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_85 get_modelscope_model licyks/sd-model/master/sdxl_1.0/pdForAnime_v20.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_86 get_modelscope_model licyks/sd-model/master/sdxl_1.0/tPonynai3_v51WeightOptimized.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_87 get_modelscope_model licyks/sd-model/master/sdxl_1.0/omegaPonyXLAnime_v20.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_88 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animeIllustDiffusion_v061.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_89 get_modelscope_model licyks/sd-model/master/sdxl_1.0/artiwaifuDiffusion_v10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_90 get_modelscope_model licyks/sd-model/master/sdxl_1.0/artiwaifu-diffusion-v2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_91 get_modelscope_model licyks/sd-model/master/sdxl_1.0/AnythingXL_xl.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_92 get_modelscope_model licyks/sd-model/master/sdxl_1.0/abyssorangeXLElse_v10.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_93 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animaPencilXL_v200.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_94 get_modelscope_model licyks/sd-model/master/sdxl_1.0/bluePencilXL_v401.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_95 get_modelscope_model licyks/sd-model/master/sdxl_1.0/nekorayxl_v06W3.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_96 get_modelscope_model licyks/sd-model/master/sdxl_1.0/CounterfeitXL-V1.0.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_97 # =====SD3大模型===== OFF
__term_sd_task_pre_model_98 get_modelscope_model licyks/sd-3-model/master/sd3_medium.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3_medium(4.34g) OFF
__term_sd_task_pre_model_99 get_modelscope_model licyks/sd-3-model/master/sd3_medium_incl_clips.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3_medium_incl_clips(5.97g) OFF
__term_sd_task_pre_model_100 get_modelscope_model licyks/sd-3-model/master/sd3_medium_incl_clips_t5xxlfp8.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3_medium_incl_clips_t5xxlfp8(10.87g) OFF
__term_sd_task_pre_model_101 get_modelscope_model licyks/sd-3-model/master/sd3.5_large.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3.5_large(16.5g) OFF
__term_sd_task_pre_model_102 get_modelscope_model licyks/sd-3-model/master/sd3.5_large_fp8_scaled.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3.5_large_fp8_scaled(14.9g) OFF
__term_sd_task_pre_model_103 get_modelscope_model licyks/sd-3-model/master/sd3.5_large_turbo.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3.5_large_turbo(16.5g) OFF
__term_sd_task_pre_model_104 get_modelscope_model licyks/sd-3-model/master/sd3.5_medium.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3.5_medium(5.1g) OFF
__term_sd_task_pre_model_105 get_modelscope_model licyks/sd-3-model/master/sd3.5_medium_incl_clips_t5xxlfp8scaled.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # sd3.5_medium_incl_clips_t5xxlfp8scaled(11.6g) OFF
__term_sd_task_pre_model_106 get_modelscope_model licyks/sd-3-model/master/emi3.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # emi3(16.5g) OFF
__term_sd_task_pre_model_107 # =====SD3文本编码器===== OFF
__term_sd_task_pre_model_108 get_modelscope_model licyks/sd-3-model/master/text_encoders/clip_g.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # clip_g(1.39g) OFF
__term_sd_task_pre_model_109 get_modelscope_model licyks/sd-3-model/master/text_encoders/clip_l.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # clip_l(246.1m) OFF
__term_sd_task_pre_model_110 get_modelscope_model licyks/sd-3-model/master/text_encoders/t5xxl_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_111 get_modelscope_model licyks/sd-3-model/master/text_encoders/t5xxl_fp8_e4m3fn.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_112 get_modelscope_model licyks/sd-3-model/master/text_encoders/t5xxl_fp8_e4m3fn_scaled.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5xxl_fp8_e4m3fn_scaled(5.16g) OFF
__term_sd_task_pre_model_113 # =====HunyuanDiT===== OFF
__term_sd_task_pre_model_114 get_modelscope_model licyks/comfyui-extension-models/master/hunyuan_dit_comfyui/hunyuan_dit_1.2.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # hunyuan_dit_1.2(8.24g) OFF
__term_sd_task_pre_model_115 get_modelscope_model licyks/comfyui-extension-models/master/hunyuan_dit_comfyui/comfy_freeway_animation_hunyuan_dit_180w.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # comfy_freeway_animation_hunyuan_dit_180w(8.24g) OFF
__term_sd_task_pre_model_116 # =====FLUX模型===== OFF
__term_sd_task_pre_model_117 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev(23.8g) OFF
__term_sd_task_pre_model_118 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-fp8.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # flux1-dev-fp8(17.2g) OFF
__term_sd_task_pre_model_119 get_modelscope_model licyks/flux-model/master/flux_1/flux_dev_fp8_scaled_diffusion_model.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # flux_dev_fp8_scaled_diffusion_model(11.9g) OFF
__term_sd_task_pre_model_120 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-bnb-nf4-v2.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # flux1-dev-bnb-nf4-v2(12g) OFF
__term_sd_task_pre_model_121 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-bnb-nf4.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # flux1-dev-bnb-nf4(11.5g) OFF
__term_sd_task_pre_model_122 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q2_K.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q2_K-gguf(4.03g) OFF
__term_sd_task_pre_model_123 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q3_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q3_K_S-gguf(5.23g) OFF
__term_sd_task_pre_model_124 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q4_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q4_0-gguf(6.79g) OFF
__term_sd_task_pre_model_125 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q4_1.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q4_1-gguf(7.53g) OFF
__term_sd_task_pre_model_126 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q4_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q4_K_S-gguf(6.81g) OFF
__term_sd_task_pre_model_127 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q5_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q5_0-gguf(8.27g) OFF
__term_sd_task_pre_model_128 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q5_1.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q5_1-gguf(9.01g) OFF
__term_sd_task_pre_model_129 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q5_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q5_K_S-gguf(8.29g) OFF
__term_sd_task_pre_model_130 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q6_K.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q6_K-gguf(9.86g) OFF
__term_sd_task_pre_model_131 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q8_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_132 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-F16.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_133 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_134 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-fp8.safetensors "${COMFYUI_ROOT_PATH}"/models/checkpoints # flux1-schnell-fp8(17.2g) OFF
__term_sd_task_pre_model_135 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q2_K.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q2_K-gguf(4.01g) OFF
__term_sd_task_pre_model_136 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q3_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q3_K_S-gguf(5.21g) OFF
__term_sd_task_pre_model_137 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q4_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q4_0-gguf(6.77g) OFF
__term_sd_task_pre_model_138 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q4_1.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q4_1-gguf(7.51g) OFF
__term_sd_task_pre_model_139 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q4_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q4_K_S-gguf(6.78g) OFF
__term_sd_task_pre_model_140 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q5_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q5_0-gguf(8.25g) OFF
__term_sd_task_pre_model_141 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q5_1.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q5_1-gguf(8.99g) OFF
__term_sd_task_pre_model_142 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q5_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q5_K_S-gguf(8.26g) OFF
__term_sd_task_pre_model_143 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q6_K.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q6_K-gguf(9.83g) OFF
__term_sd_task_pre_model_144 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q8_0.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_145 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-F16.gguf "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-schnell-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_146 get_modelscope_model licyks/flux-model/master/flux_1/ashen0209-flux1-dev2pro.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_147 get_modelscope_model licyks/flux-model/master/flux_1/jimmycarter-LibreFLUX.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_148 get_modelscope_model licyks/flux-model/master/flux_1/nyanko7-flux-dev-de-distill.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_149 get_modelscope_model licyks/flux-model/master/flux_1/shuttle-3-diffusion.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_150 get_modelscope_model licyks/flux-model/master/flux_1/flux1-krea-dev_fp8_scaled.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-krea-dev_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_151 get_modelscope_model licyks/flux-model/master/flux_1/flux1-krea-dev.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-krea-dev(23.8g) OFF
__term_sd_task_pre_model_152 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-kontext_fp8_scaled.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-dev-kontext_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_153 get_modelscope_model licyks/flux-model/master/flux_1/flux1-kontext-dev.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # flux1-kontext-dev(23.8g) OFF
__term_sd_task_pre_model_154 get_modelscope_model licyks/flux-model/master/flux_1/chroma-unlocked-v50.safetensors "${COMFYUI_ROOT_PATH}"/models/diffusion_models # chroma-unlocked-v50(23.8g) OFF
__term_sd_task_pre_model_155 # =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_156 get_modelscope_model licyks/flux-model/master/flux_text_encoders/clip_l.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # clip_l(246.1m) OFF
__term_sd_task_pre_model_157 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5xxl_fp16.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_158 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5xxl_fp8_e4m3fn.safetensors "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_159 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_L.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q3_K_L-gguf(2.46g) OFF
__term_sd_task_pre_model_160 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_M.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q3_K_M-gguf(2.3g) OFF
__term_sd_task_pre_model_161 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q3_K_S-gguf(2.1g) OFF
__term_sd_task_pre_model_162 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q4_K_M.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q4_K_M-gguf(2.9g) OFF
__term_sd_task_pre_model_163 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q4_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q4_K_S-gguf(2.74g) OFF
__term_sd_task_pre_model_164 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q5_K_M.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q5_K_M-gguf(3.39g) OFF
__term_sd_task_pre_model_165 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q5_K_S.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q5_K_S-gguf(3.29g) OFF
__term_sd_task_pre_model_166 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q6_K.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q6_K-gguf(3.91g) OFF
__term_sd_task_pre_model_167 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q8_0.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-Q8_0-gguf(5.06g) OFF
__term_sd_task_pre_model_168 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-f16.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-f16-gguf(9.53g) OFF
__term_sd_task_pre_model_169 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-f32.gguf "${COMFYUI_ROOT_PATH}"/models/text_encoders # t5-v1_1-xxl-encoder-f32-gguf(19.1g) OFF
__term_sd_task_pre_model_170 get_modelscope_model licyks/flux-model/master/flux_vae/ae.safetensors "${COMFYUI_ROOT_PATH}"/models/vae # ae(335m) OFF
__term_sd_task_pre_model_171 # =====VAE模型===== OFF
__term_sd_task_pre_model_172 get_modelscope_model licyks/sd-vae/master/sd_1.5/vae-ft-ema-560000-ema-pruned.safetensors "${COMFYUI_ROOT_PATH}"/models/vae # vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_173 get_modelscope_model licyks/sd-vae/master/sd_1.5/vae-ft-mse-840000-ema-pruned.safetensors "${COMFYUI_ROOT_PATH}"/models/vae # vae-ft-mse-840000-ema-pruned(334.6m) ON
__term_sd_task_pre_model_174 get_modelscope_model licyks/sd-vae/master/sdxl_1.0/sdxl_vae.safetensors "${COMFYUI_ROOT_PATH}"/models/vae # sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_175 get_modelscope_model licyks/sd-vae/master/sdxl_1.0/sdxl_fp16_fix_vae.safetensors "${COMFYUI_ROOT_PATH}"/models/vae # sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_176 # =====VAE-approx模型===== OFF
__term_sd_task_pre_model_177 get_modelscope_model licyks/sd-vae/master/vae-approx/model.pt "${COMFYUI_ROOT_PATH}"/models/vae_approx # VAE-approx模型 model(0.2m) ON
__term_sd_task_pre_model_178 get_modelscope_model licyks/sd-vae/master/vae-approx/vaeapprox-sdxl.pt "${COMFYUI_ROOT_PATH}"/models/vae_approx # vaeapprox-sdxl(0.2m) ON
__term_sd_task_pre_model_179 get_modelscope_model licyks/sd-vae/master/vae-approx/vaeapprox-sd3.pt "${COMFYUI_ROOT_PATH}"/models/vae_approx # vaeapprox-sd3(0.2m) OFF
__term_sd_task_pre_model_180 # =====放大模型===== OFF
__term_sd_task_pre_model_181 get_modelscope_model licyks/sd-upscaler-models/master/Codeformer/codeformer-v0.1.0.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # codeformer-v0.1.0(376.6m) OFF
__term_sd_task_pre_model_182 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_2_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_2_x2(139.7m) OFF
__term_sd_task_pre_model_183 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_2_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_2_x3(140.4m) OFF
__term_sd_task_pre_model_184 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_2_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_2_x4(140.3m) OFF
__term_sd_task_pre_model_185 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_S_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_S_x2(87.7m) OFF
__term_sd_task_pre_model_186 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_S_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_S_x3(88.4m) OFF
__term_sd_task_pre_model_187 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_S_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_S_x4(88.2m) OFF
__term_sd_task_pre_model_188 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_light_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_light_x2(45.7m) OFF
__term_sd_task_pre_model_189 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_light_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_light_x3(45.7m) OFF
__term_sd_task_pre_model_190 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_light_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_light_x4(45.8m) OFF
__term_sd_task_pre_model_191 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_x2(154.1m) OFF
__term_sd_task_pre_model_192 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_x3(154.8m) OFF
__term_sd_task_pre_model_193 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # DAT_x4(154.7m) OFF
__term_sd_task_pre_model_194 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/16xPSNR.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 16xPSNR(67.2m) OFF
__term_sd_task_pre_model_195 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x-ITF-SkinDiffDetail-Lite-v1.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x-ITF-SkinDiffDetail-Lite-v1(20.1m) OFF
__term_sd_task_pre_model_196 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x_NMKD-BrightenRedux_200k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x_NMKD-BrightenRedux_200k(66.6m) OFF
__term_sd_task_pre_model_197 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x_NMKD-YandereInpaint_375000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x_NMKD-YandereInpaint_375000_G(66.6m) OFF
__term_sd_task_pre_model_198 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x_NMKDDetoon_97500_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x_NMKDDetoon_97500_G(66.6m) OFF
__term_sd_task_pre_model_199 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x_NoiseToner-Poisson-Detailed_108000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x_NoiseToner-Poisson-Detailed_108000_G(66.6m) OFF
__term_sd_task_pre_model_200 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x_NoiseToner-Uniform-Detailed_100000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 1x_NoiseToner-Uniform-Detailed_100000_G(66.6m) OFF
__term_sd_task_pre_model_201 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x-UltraSharp.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x-UltraSharp(66.9m) OFF
__term_sd_task_pre_model_202 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4xPSNR.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4xPSNR(66.9m) OFF
__term_sd_task_pre_model_203 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_CountryRoads_377000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_CountryRoads_377000_G(66.9m) OFF
__term_sd_task_pre_model_204 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_Fatality_Comix_260000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_Fatality_Comix_260000_G(66.9m) OFF
__term_sd_task_pre_model_205 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-Siax_200k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-Siax_200k(66.9m) OFF
__term_sd_task_pre_model_206 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-Superscale-Artisoftject_210000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-Superscale-Artisoftject_210000_G(66.9m) OFF
__term_sd_task_pre_model_207 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-Superscale-SP_178000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-Superscale-SP_178000_G(66.9m) ON
__term_sd_task_pre_model_208 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-UltraYandere-Lite_280k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-UltraYandere-Lite_280k(20.1m) OFF
__term_sd_task_pre_model_209 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-UltraYandere_300k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-UltraYandere_300k(66.9m) OFF
__term_sd_task_pre_model_210 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-YandereNeoXL_200k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKD-YandereNeoXL_200k(66.9m) OFF
__term_sd_task_pre_model_211 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKDSuperscale_Artisoft_120000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NMKDSuperscale_Artisoft_120000_G(67.1m) OFF
__term_sd_task_pre_model_212 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NickelbackFS_72000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_NickelbackFS_72000_G(67.1m) OFF
__term_sd_task_pre_model_213 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_Nickelback_70000G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_Nickelback_70000G(66.9m) OFF
__term_sd_task_pre_model_214 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_RealisticRescaler_100000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_RealisticRescaler_100000_G(134.1m) OFF
__term_sd_task_pre_model_215 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_Valar_v1.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_Valar_v1(67.5m) OFF
__term_sd_task_pre_model_216 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_fatal_Anime_500000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_fatal_Anime_500000_G(66.9m) OFF
__term_sd_task_pre_model_217 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_foolhardy_Remacri.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_foolhardy_Remacri(67m) OFF
__term_sd_task_pre_model_218 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/8xPSNR.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 8xPSNR(67.1m) OFF
__term_sd_task_pre_model_219 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/8x_NMKD-Superscale_150000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 8x_NMKD-Superscale_150000_G(67.1m) OFF
__term_sd_task_pre_model_220 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/8x_NMKD-Typescale_175k.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 8x_NMKD-Typescale_175k(67.1m) OFF
__term_sd_task_pre_model_221 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/A_ESRGAN_Single.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # A_ESRGAN_Single(134.1m) OFF
__term_sd_task_pre_model_222 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/BSRGAN.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # BSRGAN(67.1m) OFF
__term_sd_task_pre_model_223 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/BSRGANx2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # BSRGANx2(66.8m) OFF
__term_sd_task_pre_model_224 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/BSRNet.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # BSRNet(67.1m) OFF
__term_sd_task_pre_model_225 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/ESRGAN_4x.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # ESRGAN_4x(66.9m) OFF
__term_sd_task_pre_model_226 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/LADDIER1_282500_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # LADDIER1_282500_G(66.9m) OFF
__term_sd_task_pre_model_227 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Neutral_115000_swaG.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_UniversalUpscalerV2-Neutral_115000_swaG(66.9m) OFF
__term_sd_task_pre_model_228 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Sharp_101000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_UniversalUpscalerV2-Sharp_101000_G(66.9m) OFF
__term_sd_task_pre_model_229 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Sharper_103000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_UniversalUpscalerV2-Sharper_103000_G(66.9m) OFF
__term_sd_task_pre_model_230 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/UniversalUpscaler/Legacy/4x_UniversalUpscaler-Detailed_155000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_UniversalUpscaler-Detailed_155000_G(66.9m) OFF
__term_sd_task_pre_model_231 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/UniversalUpscaler/Legacy/4x_UniversalUpscaler-Soft_190000_G.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 4x_UniversalUpscaler-Soft_190000_G(66.9m) OFF
__term_sd_task_pre_model_232 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/WaifuGAN_v3_30000.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # WaifuGAN_v3_30000(66.9m) OFF
__term_sd_task_pre_model_233 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/lollypop.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # lollypop(66.9m) OFF
__term_sd_task_pre_model_234 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/sudo_rife4_269.662_testV1_scale1.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # sudo_rife4_269.662_testV1_scale1(33.7m) OFF
__term_sd_task_pre_model_235 get_modelscope_model licyks/sd-upscaler-models/master/GFPGAN/GFPGANv1.3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # GFPGANv1.3(348.6m) OFF
__term_sd_task_pre_model_236 get_modelscope_model licyks/sd-upscaler-models/master/GFPGAN/GFPGANv1.4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # GFPGANv1.4(348.6m) OFF
__term_sd_task_pre_model_237 get_modelscope_model licyks/sd-upscaler-models/master/GFPGAN/detection_Resnet50_Final.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # detection_Resnet50_Final(109.5m) OFF
__term_sd_task_pre_model_238 get_modelscope_model licyks/sd-upscaler-models/master/GFPGAN/parsing_bisenet.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # parsing_bisenet(12.2m) OFF
__term_sd_task_pre_model_239 get_modelscope_model licyks/sd-upscaler-models/master/GFPGAN/parsing_parsenet.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # parsing_parsenet(85.3m) OFF
__term_sd_task_pre_model_240 get_modelscope_model licyks/sd-upscaler-models/master/RealESRGAN/RealESRGAN_x4plus.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # RealESRGAN_x4plus(67m) ON
__term_sd_task_pre_model_241 get_modelscope_model licyks/sd-upscaler-models/master/RealESRGAN/RealESRGAN_x4plus_anime_6B.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # RealESRGAN_x4plus_anime_6B(17.9m) ON
__term_sd_task_pre_model_242 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DF2K_s64w8_SwinIR-M_x2(67.2m) OFF
__term_sd_task_pre_model_243 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DF2K_s64w8_SwinIR-M_x3(68m) OFF
__term_sd_task_pre_model_244 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DF2K_s64w8_SwinIR-M_x4(67.8m) OFF
__term_sd_task_pre_model_245 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x8.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DF2K_s64w8_SwinIR-M_x8(68.4m) OFF
__term_sd_task_pre_model_246 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x2.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x2(59m) OFF
__term_sd_task_pre_model_247 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x3.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x3(59.7m) OFF
__term_sd_task_pre_model_248 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x4.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x4(59.6m) OFF
__term_sd_task_pre_model_249 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x8.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x8(60.2m) OFF
__term_sd_task_pre_model_250 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/Swin2SR_ClassicalSR_X2_64.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # Swin2SR_ClassicalSR_X2_64(68.7m) OFF
__term_sd_task_pre_model_251 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/Swin2SR_ClassicalSR_X4_64.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # Swin2SR_ClassicalSR_X4_64(69.3m) OFF
__term_sd_task_pre_model_252 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/Swin2SR_CompressedSR_X4_48.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # Swin2SR_CompressedSR_X4_48(61.1m) OFF
__term_sd_task_pre_model_253 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR(68.6m) OFF
__term_sd_task_pre_model_254 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/SwinIR_4x.pth "${COMFYUI_ROOT_PATH}"/models/upscale_models # SwinIR_4x(142.4m) OFF
__term_sd_task_pre_model_255 # =====Embedding模型===== OFF
__term_sd_task_pre_model_256 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/EasyNegativeV2.safetensors "${COMFYUI_ROOT_PATH}"/models/embeddings # embeddings模型 EasyNegativeV2(0.1m) ON
__term_sd_task_pre_model_257 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/bad-artist-anime.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # bad-artist-anime(0.1m) ON
__term_sd_task_pre_model_258 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/bad-artist.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # bad-artist(0.1m) ON
__term_sd_task_pre_model_259 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/bad-hands-5.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # bad-hands-5(0.1m) ON
__term_sd_task_pre_model_260 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/bad-image-v2-39000.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # bad-image-v2-39000(0.1m) ON
__term_sd_task_pre_model_261 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/bad_prompt_version2.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # bad_prompt_version2(0.1m) ON
__term_sd_task_pre_model_262 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/ng_deepnegative_v1_75t.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # ng_deepnegative_v1_75t(0.1m) ON
__term_sd_task_pre_model_263 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/verybadimagenegative_v1.3.pt "${COMFYUI_ROOT_PATH}"/models/embeddings # verybadimagenegative_v1.3(0.1m) ON
|
2301_81996401/term-sd
|
install/comfyui/comfyui_ms_model.sh
|
Shell
|
agpl-3.0
| 49,283
|
__term_sd_task_pre_ext_1 comfyui_controlnet_aux ON
__term_sd_task_pre_ext_2 ComfyUI-AnimateDiff-Evolved OFF
__term_sd_task_pre_ext_3 ComfyUI_IPAdapter_plus ON
__term_sd_task_pre_ext_4 ComfyUI-Impact-Pack OFF
__term_sd_task_pre_ext_5 ComfyUI-Marigold ON
__term_sd_task_pre_ext_6 ComfyUI-WD14-Tagger ON
__term_sd_task_pre_ext_7 ComfyUI-layerdiffusion OFF
__term_sd_task_pre_ext_8 ComfyUI_DanTagGen OFF
__term_sd_task_pre_ext_9 Comfyui-StableSR OFF
__term_sd_task_pre_ext_10 z-tipo-extension OFF
__term_sd_task_pre_ext_11 was-node-suite-comfyui OFF
__term_sd_task_pre_ext_12 ComfyUI_Cutoff OFF
__term_sd_task_pre_ext_13 ComfyUI_TiledKSampler ON
__term_sd_task_pre_ext_14 ComfyUI_ADV_CLIP_emb OFF
__term_sd_task_pre_ext_15 ComfyUI_Noise OFF
__term_sd_task_pre_ext_16 ComfyUI_Dave_CustomNode OFF
__term_sd_task_pre_ext_17 ComfyUI-Manager ON
__term_sd_task_pre_ext_18 ComfyUI-Custom-Nodes OFF
__term_sd_task_pre_ext_19 ComfyUI-Custom-Scripts ON
__term_sd_task_pre_ext_20 NodeGPT OFF
__term_sd_task_pre_ext_21 Derfuu_ComfyUI_ModdedNodes OFF
__term_sd_task_pre_ext_22 ComfyUI_node_Lilly OFF
__term_sd_task_pre_ext_23 ComfyUI-nodes-hnmr OFF
__term_sd_task_pre_ext_24 ComfyUI-Vextra-Nodes OFF
__term_sd_task_pre_ext_25 ComfyUI-QualityOfLifeSuit_Omar92 OFF
__term_sd_task_pre_ext_26 FN16-ComfyUI-nodes OFF
__term_sd_task_pre_ext_27 masquerade-nodes-comfyui OFF
__term_sd_task_pre_ext_28 ComfyUI-post-processing-nodes OFF
__term_sd_task_pre_ext_29 images-grid-comfy-plugin ON
__term_sd_task_pre_ext_30 ComfyUI-CLIPSeg OFF
__term_sd_task_pre_ext_31 rembg-comfyui-node OFF
__term_sd_task_pre_ext_32 ComfyUI_tinyterraNodes OFF
__term_sd_task_pre_ext_33 yk-node-suite-comfyui OFF
__term_sd_task_pre_ext_34 ComfyUI_experiments OFF
__term_sd_task_pre_ext_35 ComfyUI_tagger OFF
__term_sd_task_pre_ext_36 MergeBlockWeighted_fo_ComfyUI OFF
__term_sd_task_pre_ext_37 ComfyUI-Saveaswebp OFF
__term_sd_task_pre_ext_38 trNodes OFF
__term_sd_task_pre_ext_39 ComfyUI_NetDist OFF
__term_sd_task_pre_ext_40 ComfyUI-Image-Selector OFF
__term_sd_task_pre_ext_41 ComfyUI-Strimmlarns-Aesthetic-Score OFF
__term_sd_task_pre_ext_42 ComfyUI_UltimateSDUpscale ON
__term_sd_task_pre_ext_43 ComfyUI-Disco-Diffusion OFF
__term_sd_task_pre_ext_44 ComfyUI-Waveform-Extensions OFF
__term_sd_task_pre_ext_45 ComfyUI_Custom_Nodes_AlekPet ON
__term_sd_task_pre_ext_46 AIGODLIKE-COMFYUI-TRANSLATION OFF
__term_sd_task_pre_ext_47 stability-ComfyUI-nodes OFF
__term_sd_task_pre_ext_48 ComfyUI_Fooocus_KSampler OFF
__term_sd_task_pre_ext_49 FreeU_Advanced OFF
__term_sd_task_pre_ext_50 ControlNet-LLLite-ComfyUI OFF
__term_sd_task_pre_ext_51 comfyui-tooling-nodes OFF
__term_sd_task_pre_ext_52 efficiency-nodes-comfyui OFF
__term_sd_task_pre_ext_53 cd-tuner_negpip-ComfyUI OFF
__term_sd_task_pre_ext_54 ComfyUI-Easy-Use ON
__term_sd_task_pre_ext_55 sdxl_prompt_styler OFF
__term_sd_task_pre_ext_56 comfyui-workspace-manager OFF
__term_sd_task_pre_ext_57 comfyui-browser ON
__term_sd_task_pre_ext_58 cg-use-everywhere OFF
__term_sd_task_pre_ext_59 ComfyUI-Inspire-Pack ON
__term_sd_task_pre_ext_60 sd-dynamic-thresholding OFF
__term_sd_task_pre_ext_61 rgthree-comfy ON
__term_sd_task_pre_ext_62 ComfyUI_Comfyroll_CustomNodes ON
__term_sd_task_pre_ext_63 ComfyUI_FizzNodes OFF
__term_sd_task_pre_ext_64 ComfyUI-Advanced-ControlNet ON
__term_sd_task_pre_ext_65 PowerNoiseSuite OFF
__term_sd_task_pre_ext_66 ComfyUI-Crystools ON
__term_sd_task_pre_ext_67 ComfyUI_LayerStyle OFF
__term_sd_task_pre_ext_68 ComfyUI-N-Sidebar OFF
__term_sd_task_pre_ext_69 style_aligned_comfy OFF
__term_sd_task_pre_ext_70 ComfyUI-Flowty-TripoSR OFF
__term_sd_task_pre_ext_71 ComfyUI_ExtraModels OFF
__term_sd_task_pre_ext_72 ComfyUI-SUPIR OFF
__term_sd_task_pre_ext_73 ComfyUI-YoloWorld-EfficientSAM OFF
__term_sd_task_pre_ext_74 ComfyUI-PixArt-alpha-Diffusers OFF
__term_sd_task_pre_ext_75 ComfyUI-BiRefNet-ZHO OFF
__term_sd_task_pre_ext_76 ComfyUI-DepthFM OFF
__term_sd_task_pre_ext_77 ComfyUI-APISR OFF
__term_sd_task_pre_ext_78 ComfyUI-ArtGallery OFF
__term_sd_task_pre_ext_79 ComfyUI-BRIA_AI-RMBG OFF
__term_sd_task_pre_ext_80 ComfyUI-I2VGenXL OFF
__term_sd_task_pre_ext_81 ComfyUI-SegMoE OFF
__term_sd_task_pre_ext_82 ComfyUI-AnyText OFF
__term_sd_task_pre_ext_83 ComfyUI-Extra-Samplers OFF
__term_sd_task_pre_ext_84 ComfyUI-sonar OFF
__term_sd_task_pre_ext_85 ComfyUI_restart_sampling OFF
__term_sd_task_pre_ext_86 ComfyUI-Diffusers-X-Adapter OFF
__term_sd_task_pre_ext_87 ComfyUI-BrushNet OFF
__term_sd_task_pre_ext_88 ComfyUI-BrushNet-Wrapper OFF
__term_sd_task_pre_ext_89 Euler-Smea-Dyn-Sampler OFF
__term_sd_task_pre_ext_90 ComfyUI-bleh OFF
__term_sd_task_pre_ext_91 comfyui-tcd-scheduler OFF
__term_sd_task_pre_ext_92 ComfyUI-IC-Light-Native OFF
__term_sd_task_pre_ext_93 comfyui-inpaint-nodes OFF
__term_sd_task_pre_ext_94 ComfyUI_TensorRT OFF
__term_sd_task_pre_ext_95 comfyui-diffusion-cg OFF
__term_sd_task_pre_ext_96 comfyui-floodgate OFF
__term_sd_task_pre_ext_97 comfyui-resharpen OFF
__term_sd_task_pre_ext_98 comfyui-menu-anchor OFF
__term_sd_task_pre_ext_99 comfyui-tab-handler OFF
__term_sd_task_pre_ext_100 comfyui-clear-screen OFF
__term_sd_task_pre_ext_101 comfyui-node-beautify OFF
__term_sd_task_pre_ext_102 comfyui-prompt-format OFF
__term_sd_task_pre_ext_103 ComfyUI_omost OFF
__term_sd_task_pre_ext_104 ComfyUI-Anyline OFF
__term_sd_task_pre_ext_105 ComfyUI-TiledDiffusion ON
__term_sd_task_pre_ext_106 ComfyUI-DynamiCrafterWrapper OFF
__term_sd_task_pre_ext_107 comfyui-sixgod_prompt OFF
__term_sd_task_pre_ext_108 ComfyUI_densediffusion OFF
__term_sd_task_pre_ext_109 omost_region_editor OFF
__term_sd_task_pre_ext_110 ComfyUI-openpose-editor ON
__term_sd_task_pre_ext_111 ComfyUI-IC-Light OFF
__term_sd_task_pre_ext_112 ComfyUI-KJNodes OFF
__term_sd_task_pre_ext_113 ComfyUI_essentials OFF
__term_sd_task_pre_ext_114 ComfyUI-Restart-Sampler ON
__term_sd_task_pre_ext_115 ComfyUI-TCD-Sampler OFF
__term_sd_task_pre_ext_116 cg-noise OFF
__term_sd_task_pre_ext_117 ComfyUX OFF
__term_sd_task_pre_ext_118 ComfyUI-UltraEdit-ZHO OFF
__term_sd_task_pre_ext_119 WeiLin-ComfyUI-prompt-all-in-one ON
__term_sd_task_pre_ext_120 ComfyUI-GGUF OFF
__term_sd_task_pre_ext_121 x-flux-comfyui OFF
__term_sd_task_pre_ext_122 ComfyUI-Prompt-Wildcards OFF
__term_sd_task_pre_ext_123 cg-controller OFF
__term_sd_task_pre_ext_124 ComfyUI-Latent-Modifiers OFF
__term_sd_task_pre_ext_125 comfyui-deploy OFF
__term_sd_task_pre_ext_126 ComfyUI-HakuImg ON
__term_sd_task_pre_ext_127 ComfyUI-flash-attention-rdna3-win-zluda OFF
__term_sd_task_pre_ext_128 ComfyUI-BlenderAI-node OFF
__term_sd_task_pre_ext_129 comfyui-portrait-master OFF
__term_sd_task_pre_ext_130 sigmas_tools_and_the_golden_scheduler OFF
__term_sd_task_pre_ext_131 ComfyUI_fabric OFF
__term_sd_task_pre_ext_132 ComfyUi_NNLatentUpscale OFF
__term_sd_task_pre_ext_133 comfyui_lora_tag_loader OFF
__term_sd_task_pre_ext_134 ComfyUI-disty-Flow OFF
__term_sd_task_pre_ext_135 ComfyUI-FluxTrainer OFF
__term_sd_task_pre_ext_136 ComfyUI-BiRefNet-Hugo OFF
__term_sd_task_pre_ext_137 WeiLin-Comfyui-Tools OFF
__term_sd_task_pre_ext_138 Comfy-WaveSpeed OFF
__term_sd_task_pre_ext_139 ComfyUI-TeaCache OFF
__term_sd_task_pre_ext_140 AIGODLIKE-ComfyUI-Studio OFF
__term_sd_task_pre_ext_141 ComfyUI-to-Python-Extension OFF
__term_sd_task_pre_ext_142 ComfyUI-FramePackWrapper OFF
__term_sd_task_pre_ext_143 comfyui-profiler OFF
__term_sd_task_pre_ext_144 HDM-ext OFF
__term_sd_task_pre_ext_145 ComfyUI-rgthree-comfy OFF
__term_sd_task_pre_ext_146 ComfyUI_Civitai_Gallery OFF
__term_sd_task_pre_ext_147 A8R8_ComfyUI_nodes OFF
__term_sd_task_pre_ext_148 cgem156-ComfyUI OFF
|
2301_81996401/term-sd
|
install/comfyui/dialog_comfyui_custom_node.sh
|
Shell
|
agpl-3.0
| 7,558
|
__term_sd_task_pre_ext_1 ComfyUI-extensions OFF
__term_sd_task_pre_ext_2 graphNavigator OFF
|
2301_81996401/term-sd
|
install/comfyui/dialog_comfyui_extension.sh
|
Shell
|
agpl-3.0
| 92
|
__term_sd_task_pre_model_1 =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 nai1-artist_all_in_one_merge(2.13g) OFF
__term_sd_task_pre_model_5 Counterfeit-V3.0(4.24g) OFF
__term_sd_task_pre_model_6 cetusMix_Whalefall2(3.85g) OFF
__term_sd_task_pre_model_7 cuteyukimixAdorable_neochapter3(2.3g) OFF
__term_sd_task_pre_model_8 ekmix-pastel(2.13g) OFF
__term_sd_task_pre_model_9 ex2K_sse2(2.38g) OFF
__term_sd_task_pre_model_10 kohakuV5_rev2(2.13g) OFF
__term_sd_task_pre_model_11 meinamix_meinaV11(2.13g) OFF
__term_sd_task_pre_model_12 oukaStar_10(5.43g) OFF
__term_sd_task_pre_model_13 pastelMixStylizedAnime(2.13g) OFF
__term_sd_task_pre_model_14 rabbit_v6(1.97g) OFF
__term_sd_task_pre_model_15 sweetSugarSyndrome_rev15(2.13g) OFF
__term_sd_task_pre_model_16 AnythingV5Ink_ink(2.13g) OFF
__term_sd_task_pre_model_17 bartstyledbBlueArchiveArtStyle(2.13g) OFF
__term_sd_task_pre_model_18 meinapastel_v6(2.13g) OFF
__term_sd_task_pre_model_19 qteamix(2.13g) OFF
__term_sd_task_pre_model_20 tmndMix(2.13g) OFF
__term_sd_task_pre_model_21 =====SD2.1大模型===== OFF
__term_sd_task_pre_model_22 v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_23 wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_24 wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_25 =====SDXL大模型===== OFF
__term_sd_task_pre_model_26 sd_xl_offset_example-lora_1.0(49.6m) OFF
__term_sd_task_pre_model_27 sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_28 sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_29 sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_30 cosxl(6.94g) OFF
__term_sd_task_pre_model_31 cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_32 animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_33 animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_34 animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_35 animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_36 animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_37 animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_38 holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_39 kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_40 clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_41 UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_42 RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_43 sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_44 kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_45 kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_46 kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_47 kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_48 kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_49 starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_50 heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_51 heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_52 baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_53 baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_54 sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_55 sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_56 SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_57 SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_58 Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_59 Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_60 Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_61 Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_62 Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_63 Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_64 jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_65 PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_66 miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_67 waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_68 tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_69 noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_70 noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_71 noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_72 noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_73 noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_74 noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_75 noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_76 noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_77 noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_78 noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_79 noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_80 noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_81 noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_82 PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_83 PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_84 ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_85 pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_86 tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_87 omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_88 animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_89 artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_90 artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_91 AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_92 abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_93 animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_94 bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_95 nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_96 CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_97 =====SD3大模型===== OFF
__term_sd_task_pre_model_98 sd3_medium(4.34g) OFF
__term_sd_task_pre_model_99 sd3_medium_incl_clips(5.97g) OFF
__term_sd_task_pre_model_100 sd3_medium_incl_clips_t5xxlfp8(10.87g) OFF
__term_sd_task_pre_model_101 sd3.5_large(16.5g) OFF
__term_sd_task_pre_model_102 sd3.5_large_fp8_scaled(14.9g) OFF
__term_sd_task_pre_model_103 sd3.5_large_turbo(16.5g) OFF
__term_sd_task_pre_model_104 sd3.5_medium(5.1g) OFF
__term_sd_task_pre_model_105 sd3.5_medium_incl_clips_t5xxlfp8scaled(11.6g) OFF
__term_sd_task_pre_model_106 emi3(16.5g) OFF
__term_sd_task_pre_model_107 =====SD3文本编码器===== OFF
__term_sd_task_pre_model_108 clip_g(1.39g) OFF
__term_sd_task_pre_model_109 clip_l(246.1m) OFF
__term_sd_task_pre_model_110 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_111 t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_112 t5xxl_fp8_e4m3fn_scaled(5.16g) OFF
__term_sd_task_pre_model_113 =====HunyuanDiT===== OFF
__term_sd_task_pre_model_114 hunyuan_dit_1.2(8.24g) OFF
__term_sd_task_pre_model_115 comfy_freeway_animation_hunyuan_dit_180w(8.24g) OFF
__term_sd_task_pre_model_116 =====FLUX模型===== OFF
__term_sd_task_pre_model_117 flux1-dev(23.8g) OFF
__term_sd_task_pre_model_118 flux1-dev-fp8(17.2g) OFF
__term_sd_task_pre_model_119 flux_dev_fp8_scaled_diffusion_model(11.9g) OFF
__term_sd_task_pre_model_120 flux1-dev-bnb-nf4-v2(12g) OFF
__term_sd_task_pre_model_121 flux1-dev-bnb-nf4(11.5g) OFF
__term_sd_task_pre_model_122 flux1-dev-Q2_K-gguf(4.03g) OFF
__term_sd_task_pre_model_123 flux1-dev-Q3_K_S-gguf(5.23g) OFF
__term_sd_task_pre_model_124 flux1-dev-Q4_0-gguf(6.79g) OFF
__term_sd_task_pre_model_125 flux1-dev-Q4_1-gguf(7.53g) OFF
__term_sd_task_pre_model_126 flux1-dev-Q4_K_S-gguf(6.81g) OFF
__term_sd_task_pre_model_127 flux1-dev-Q5_0-gguf(8.27g) OFF
__term_sd_task_pre_model_128 flux1-dev-Q5_1-gguf(9.01g) OFF
__term_sd_task_pre_model_129 flux1-dev-Q5_K_S-gguf(8.29g) OFF
__term_sd_task_pre_model_130 flux1-dev-Q6_K-gguf(9.86g) OFF
__term_sd_task_pre_model_131 flux1-dev-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_132 flux1-dev-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_133 flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_134 flux1-schnell-fp8(17.2g) OFF
__term_sd_task_pre_model_135 flux1-schnell-Q2_K-gguf(4.01g) OFF
__term_sd_task_pre_model_136 flux1-schnell-Q3_K_S-gguf(5.21g) OFF
__term_sd_task_pre_model_137 flux1-schnell-Q4_0-gguf(6.77g) OFF
__term_sd_task_pre_model_138 flux1-schnell-Q4_1-gguf(7.51g) OFF
__term_sd_task_pre_model_139 flux1-schnell-Q4_K_S-gguf(6.78g) OFF
__term_sd_task_pre_model_140 flux1-schnell-Q5_0-gguf(8.25g) OFF
__term_sd_task_pre_model_141 flux1-schnell-Q5_1-gguf(8.99g) OFF
__term_sd_task_pre_model_142 flux1-schnell-Q5_K_S-gguf(8.26g) OFF
__term_sd_task_pre_model_143 flux1-schnell-Q6_K-gguf(9.83g) OFF
__term_sd_task_pre_model_144 flux1-schnell-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_145 flux1-schnell-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_146 ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_147 jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_148 nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_149 shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_150 flux1-krea-dev_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_151 flux1-krea-dev(23.8g) OFF
__term_sd_task_pre_model_152 flux1-dev-kontext_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_153 flux1-kontext-dev(23.8g) OFF
__term_sd_task_pre_model_154 chroma-unlocked-v50(23.8g) OFF
__term_sd_task_pre_model_155 =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_156 clip_l(246.1m) OFF
__term_sd_task_pre_model_157 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_158 t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_159 t5-v1_1-xxl-encoder-Q3_K_L-gguf(2.46g) OFF
__term_sd_task_pre_model_160 t5-v1_1-xxl-encoder-Q3_K_M-gguf(2.3g) OFF
__term_sd_task_pre_model_161 t5-v1_1-xxl-encoder-Q3_K_S-gguf(2.1g) OFF
__term_sd_task_pre_model_162 t5-v1_1-xxl-encoder-Q4_K_M-gguf(2.9g) OFF
__term_sd_task_pre_model_163 t5-v1_1-xxl-encoder-Q4_K_S-gguf(2.74g) OFF
__term_sd_task_pre_model_164 t5-v1_1-xxl-encoder-Q5_K_M-gguf(3.39g) OFF
__term_sd_task_pre_model_165 t5-v1_1-xxl-encoder-Q5_K_S-gguf(3.29g) OFF
__term_sd_task_pre_model_166 t5-v1_1-xxl-encoder-Q6_K-gguf(3.91g) OFF
__term_sd_task_pre_model_167 t5-v1_1-xxl-encoder-Q8_0-gguf(5.06g) OFF
__term_sd_task_pre_model_168 t5-v1_1-xxl-encoder-f16-gguf(9.53g) OFF
__term_sd_task_pre_model_169 t5-v1_1-xxl-encoder-f32-gguf(19.1g) OFF
__term_sd_task_pre_model_170 ae(335m) OFF
__term_sd_task_pre_model_171 =====VAE模型===== OFF
__term_sd_task_pre_model_172 vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_173 vae-ft-mse-840000-ema-pruned(334.6m) ON
__term_sd_task_pre_model_174 sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_175 sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_176 =====VAE-approx模型===== OFF
__term_sd_task_pre_model_177 model(0.2m) ON
__term_sd_task_pre_model_178 vaeapprox-sdxl(0.2m) ON
__term_sd_task_pre_model_179 vaeapprox-sd3(0.2m) OFF
__term_sd_task_pre_model_180 =====放大模型===== OFF
__term_sd_task_pre_model_181 codeformer-v0.1.0(376.6m) OFF
__term_sd_task_pre_model_182 DAT_2_x2(139.7m) OFF
__term_sd_task_pre_model_183 DAT_2_x3(140.4m) OFF
__term_sd_task_pre_model_184 DAT_2_x4(140.3m) OFF
__term_sd_task_pre_model_185 DAT_S_x2(87.7m) OFF
__term_sd_task_pre_model_186 DAT_S_x3(88.4m) OFF
__term_sd_task_pre_model_187 DAT_S_x4(88.2m) OFF
__term_sd_task_pre_model_188 DAT_light_x2(45.7m) OFF
__term_sd_task_pre_model_189 DAT_light_x3(45.7m) OFF
__term_sd_task_pre_model_190 DAT_light_x4(45.8m) OFF
__term_sd_task_pre_model_191 DAT_x2(154.1m) OFF
__term_sd_task_pre_model_192 DAT_x3(154.8m) OFF
__term_sd_task_pre_model_193 DAT_x4(154.7m) OFF
__term_sd_task_pre_model_194 16xPSNR(67.2m) OFF
__term_sd_task_pre_model_195 1x-ITF-SkinDiffDetail-Lite-v1(20.1m) OFF
__term_sd_task_pre_model_196 1x_NMKD-BrightenRedux_200k(66.6m) OFF
__term_sd_task_pre_model_197 1x_NMKD-YandereInpaint_375000_G(66.6m) OFF
__term_sd_task_pre_model_198 1x_NMKDDetoon_97500_G(66.6m) OFF
__term_sd_task_pre_model_199 1x_NoiseToner-Poisson-Detailed_108000_G(66.6m) OFF
__term_sd_task_pre_model_200 1x_NoiseToner-Uniform-Detailed_100000_G(66.6m) OFF
__term_sd_task_pre_model_201 4x-UltraSharp(66.9m) OFF
__term_sd_task_pre_model_202 4xPSNR(66.9m) OFF
__term_sd_task_pre_model_203 4x_CountryRoads_377000_G(66.9m) OFF
__term_sd_task_pre_model_204 4x_Fatality_Comix_260000_G(66.9m) OFF
__term_sd_task_pre_model_205 4x_NMKD-Siax_200k(66.9m) OFF
__term_sd_task_pre_model_206 4x_NMKD-Superscale-Artisoftject_210000_G(66.9m) OFF
__term_sd_task_pre_model_207 4x_NMKD-Superscale-SP_178000_G(66.9m) ON
__term_sd_task_pre_model_208 4x_NMKD-UltraYandere-Lite_280k(20.1m) OFF
__term_sd_task_pre_model_209 4x_NMKD-UltraYandere_300k(66.9m) OFF
__term_sd_task_pre_model_210 4x_NMKD-YandereNeoXL_200k(66.9m) OFF
__term_sd_task_pre_model_211 4x_NMKDSuperscale_Artisoft_120000_G(67.1m) OFF
__term_sd_task_pre_model_212 4x_NickelbackFS_72000_G(67.1m) OFF
__term_sd_task_pre_model_213 4x_Nickelback_70000G(66.9m) OFF
__term_sd_task_pre_model_214 4x_RealisticRescaler_100000_G(134.1m) OFF
__term_sd_task_pre_model_215 4x_Valar_v1(67.5m) OFF
__term_sd_task_pre_model_216 4x_fatal_Anime_500000_G(66.9m) OFF
__term_sd_task_pre_model_217 4x_foolhardy_Remacri(67m) OFF
__term_sd_task_pre_model_218 8xPSNR(67.1m) OFF
__term_sd_task_pre_model_219 8x_NMKD-Superscale_150000_G(67.1m) OFF
__term_sd_task_pre_model_220 8x_NMKD-Typescale_175k(67.1m) OFF
__term_sd_task_pre_model_221 A_ESRGAN_Single(134.1m) OFF
__term_sd_task_pre_model_222 BSRGAN(67.1m) OFF
__term_sd_task_pre_model_223 BSRGANx2(66.8m) OFF
__term_sd_task_pre_model_224 BSRNet(67.1m) OFF
__term_sd_task_pre_model_225 ESRGAN_4x(66.9m) OFF
__term_sd_task_pre_model_226 LADDIER1_282500_G(66.9m) OFF
__term_sd_task_pre_model_227 4x_UniversalUpscalerV2-Neutral_115000_swaG(66.9m) OFF
__term_sd_task_pre_model_228 4x_UniversalUpscalerV2-Sharp_101000_G(66.9m) OFF
__term_sd_task_pre_model_229 4x_UniversalUpscalerV2-Sharper_103000_G(66.9m) OFF
__term_sd_task_pre_model_230 4x_UniversalUpscaler-Detailed_155000_G(66.9m) OFF
__term_sd_task_pre_model_231 4x_UniversalUpscaler-Soft_190000_G(66.9m) OFF
__term_sd_task_pre_model_232 WaifuGAN_v3_30000(66.9m) OFF
__term_sd_task_pre_model_233 lollypop(66.9m) OFF
__term_sd_task_pre_model_234 sudo_rife4_269.662_testV1_scale1(33.7m) OFF
__term_sd_task_pre_model_235 GFPGANv1.3(348.6m) OFF
__term_sd_task_pre_model_236 GFPGANv1.4(348.6m) OFF
__term_sd_task_pre_model_237 detection_Resnet50_Final(109.5m) OFF
__term_sd_task_pre_model_238 parsing_bisenet(12.2m) OFF
__term_sd_task_pre_model_239 parsing_parsenet(85.3m) OFF
__term_sd_task_pre_model_240 RealESRGAN_x4plus(67m) ON
__term_sd_task_pre_model_241 RealESRGAN_x4plus_anime_6B(17.9m) ON
__term_sd_task_pre_model_242 001_classicalSR_DF2K_s64w8_SwinIR-M_x2(67.2m) OFF
__term_sd_task_pre_model_243 001_classicalSR_DF2K_s64w8_SwinIR-M_x3(68m) OFF
__term_sd_task_pre_model_244 001_classicalSR_DF2K_s64w8_SwinIR-M_x4(67.8m) OFF
__term_sd_task_pre_model_245 001_classicalSR_DF2K_s64w8_SwinIR-M_x8(68.4m) OFF
__term_sd_task_pre_model_246 001_classicalSR_DIV2K_s48w8_SwinIR-M_x2(59m) OFF
__term_sd_task_pre_model_247 001_classicalSR_DIV2K_s48w8_SwinIR-M_x3(59.7m) OFF
__term_sd_task_pre_model_248 001_classicalSR_DIV2K_s48w8_SwinIR-M_x4(59.6m) OFF
__term_sd_task_pre_model_249 001_classicalSR_DIV2K_s48w8_SwinIR-M_x8(60.2m) OFF
__term_sd_task_pre_model_250 Swin2SR_ClassicalSR_X2_64(68.7m) OFF
__term_sd_task_pre_model_251 Swin2SR_ClassicalSR_X4_64(69.3m) OFF
__term_sd_task_pre_model_252 Swin2SR_CompressedSR_X4_48(61.1m) OFF
__term_sd_task_pre_model_253 Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR(68.6m) OFF
__term_sd_task_pre_model_254 SwinIR_4x(142.4m) OFF
__term_sd_task_pre_model_255 =====Embedding模型===== OFF
__term_sd_task_pre_model_256 EasyNegativeV2(0.1m) ON
__term_sd_task_pre_model_257 bad-artist-anime(0.1m) ON
__term_sd_task_pre_model_258 bad-artist(0.1m) ON
__term_sd_task_pre_model_259 bad-hands-5(0.1m) ON
__term_sd_task_pre_model_260 bad-image-v2-39000(0.1m) ON
__term_sd_task_pre_model_261 bad_prompt_version2(0.1m) ON
__term_sd_task_pre_model_262 ng_deepnegative_v1_75t(0.1m) ON
__term_sd_task_pre_model_263 verybadimagenegative_v1.3(0.1m) ON
|
2301_81996401/term-sd
|
install/comfyui/dialog_comfyui_hf_model.sh
|
Shell
|
agpl-3.0
| 16,127
|
__term_sd_task_pre_model_1 =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 nai1-artist_all_in_one_merge(2.13g) OFF
__term_sd_task_pre_model_5 Counterfeit-V3.0(4.24g) OFF
__term_sd_task_pre_model_6 cetusMix_Whalefall2(3.85g) OFF
__term_sd_task_pre_model_7 cuteyukimixAdorable_neochapter3(2.3g) OFF
__term_sd_task_pre_model_8 ekmix-pastel(2.13g) OFF
__term_sd_task_pre_model_9 ex2K_sse2(2.38g) OFF
__term_sd_task_pre_model_10 kohakuV5_rev2(2.13g) OFF
__term_sd_task_pre_model_11 meinamix_meinaV11(2.13g) OFF
__term_sd_task_pre_model_12 oukaStar_10(5.43g) OFF
__term_sd_task_pre_model_13 pastelMixStylizedAnime(2.13g) OFF
__term_sd_task_pre_model_14 rabbit_v6(1.97g) OFF
__term_sd_task_pre_model_15 sweetSugarSyndrome_rev15(1.97g) OFF
__term_sd_task_pre_model_16 AnythingV5Ink_ink(1.97g) OFF
__term_sd_task_pre_model_17 bartstyledbBlueArchiveArtStyle(1.97g) OFF
__term_sd_task_pre_model_18 meinapastel_v6(1.97g) OFF
__term_sd_task_pre_model_19 qteamix(1.97g) OFF
__term_sd_task_pre_model_20 tmndMix(1.97g) OFF
__term_sd_task_pre_model_21 =====SD2.1大模型===== OFF
__term_sd_task_pre_model_22 v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_23 wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_24 wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_25 =====SDXL大模型===== OFF
__term_sd_task_pre_model_26 sd_xl_offset_example-lora_1.0(49.6m) OFF
__term_sd_task_pre_model_27 sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_28 sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_29 sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_30 cosxl(6.94g) OFF
__term_sd_task_pre_model_31 cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_32 animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_33 animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_34 animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_35 animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_36 animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_37 animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_38 holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_39 kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_40 clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_41 UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_42 RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_43 sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_44 kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_45 kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_46 kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_47 kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_48 kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_49 starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_50 heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_51 heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_52 baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_53 baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_54 sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_55 sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_56 SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_57 SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_58 Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_59 Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_60 Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_61 Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_62 Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_63 Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_64 jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_65 PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_66 miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_67 waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_68 tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_69 noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_70 noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_71 noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_72 noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_73 noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_74 noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_75 noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_76 noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_77 noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_78 noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_79 noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_80 noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_81 noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_82 PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_83 PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_84 ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_85 pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_86 tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_87 omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_88 animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_89 artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_90 artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_91 AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_92 abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_93 animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_94 bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_95 nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_96 CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_97 =====SD3大模型===== OFF
__term_sd_task_pre_model_98 sd3_medium(4.34g) OFF
__term_sd_task_pre_model_99 sd3_medium_incl_clips(5.97g) OFF
__term_sd_task_pre_model_100 sd3_medium_incl_clips_t5xxlfp8(10.87g) OFF
__term_sd_task_pre_model_101 sd3.5_large(16.5g) OFF
__term_sd_task_pre_model_102 sd3.5_large_fp8_scaled(14.9g) OFF
__term_sd_task_pre_model_103 sd3.5_large_turbo(16.5g) OFF
__term_sd_task_pre_model_104 sd3.5_medium(5.1g) OFF
__term_sd_task_pre_model_105 sd3.5_medium_incl_clips_t5xxlfp8scaled(11.6g) OFF
__term_sd_task_pre_model_106 emi3(16.5g) OFF
__term_sd_task_pre_model_107 =====SD3文本编码器===== OFF
__term_sd_task_pre_model_108 clip_g(1.39g) OFF
__term_sd_task_pre_model_109 clip_l(246.1m) OFF
__term_sd_task_pre_model_110 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_111 t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_112 t5xxl_fp8_e4m3fn_scaled(5.16g) OFF
__term_sd_task_pre_model_113 =====HunyuanDiT===== OFF
__term_sd_task_pre_model_114 hunyuan_dit_1.2(8.24g) OFF
__term_sd_task_pre_model_115 comfy_freeway_animation_hunyuan_dit_180w(8.24g) OFF
__term_sd_task_pre_model_116 =====FLUX模型===== OFF
__term_sd_task_pre_model_117 flux1-dev(23.8g) OFF
__term_sd_task_pre_model_118 flux1-dev-fp8(17.2g) OFF
__term_sd_task_pre_model_119 flux_dev_fp8_scaled_diffusion_model(11.9g) OFF
__term_sd_task_pre_model_120 flux1-dev-bnb-nf4-v2(12g) OFF
__term_sd_task_pre_model_121 flux1-dev-bnb-nf4(11.5g) OFF
__term_sd_task_pre_model_122 flux1-dev-Q2_K-gguf(4.03g) OFF
__term_sd_task_pre_model_123 flux1-dev-Q3_K_S-gguf(5.23g) OFF
__term_sd_task_pre_model_124 flux1-dev-Q4_0-gguf(6.79g) OFF
__term_sd_task_pre_model_125 flux1-dev-Q4_1-gguf(7.53g) OFF
__term_sd_task_pre_model_126 flux1-dev-Q4_K_S-gguf(6.81g) OFF
__term_sd_task_pre_model_127 flux1-dev-Q5_0-gguf(8.27g) OFF
__term_sd_task_pre_model_128 flux1-dev-Q5_1-gguf(9.01g) OFF
__term_sd_task_pre_model_129 flux1-dev-Q5_K_S-gguf(8.29g) OFF
__term_sd_task_pre_model_130 flux1-dev-Q6_K-gguf(9.86g) OFF
__term_sd_task_pre_model_131 flux1-dev-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_132 flux1-dev-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_133 flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_134 flux1-schnell-fp8(17.2g) OFF
__term_sd_task_pre_model_135 flux1-schnell-Q2_K-gguf(4.01g) OFF
__term_sd_task_pre_model_136 flux1-schnell-Q3_K_S-gguf(5.21g) OFF
__term_sd_task_pre_model_137 flux1-schnell-Q4_0-gguf(6.77g) OFF
__term_sd_task_pre_model_138 flux1-schnell-Q4_1-gguf(7.51g) OFF
__term_sd_task_pre_model_139 flux1-schnell-Q4_K_S-gguf(6.78g) OFF
__term_sd_task_pre_model_140 flux1-schnell-Q5_0-gguf(8.25g) OFF
__term_sd_task_pre_model_141 flux1-schnell-Q5_1-gguf(8.99g) OFF
__term_sd_task_pre_model_142 flux1-schnell-Q5_K_S-gguf(8.26g) OFF
__term_sd_task_pre_model_143 flux1-schnell-Q6_K-gguf(9.83g) OFF
__term_sd_task_pre_model_144 flux1-schnell-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_145 flux1-schnell-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_146 ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_147 jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_148 nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_149 shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_150 flux1-krea-dev_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_151 flux1-krea-dev(23.8g) OFF
__term_sd_task_pre_model_152 flux1-dev-kontext_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_153 flux1-kontext-dev(23.8g) OFF
__term_sd_task_pre_model_154 chroma-unlocked-v50(23.8g) OFF
__term_sd_task_pre_model_155 =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_156 clip_l(246.1m) OFF
__term_sd_task_pre_model_157 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_158 t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_159 t5-v1_1-xxl-encoder-Q3_K_L-gguf(2.46g) OFF
__term_sd_task_pre_model_160 t5-v1_1-xxl-encoder-Q3_K_M-gguf(2.3g) OFF
__term_sd_task_pre_model_161 t5-v1_1-xxl-encoder-Q3_K_S-gguf(2.1g) OFF
__term_sd_task_pre_model_162 t5-v1_1-xxl-encoder-Q4_K_M-gguf(2.9g) OFF
__term_sd_task_pre_model_163 t5-v1_1-xxl-encoder-Q4_K_S-gguf(2.74g) OFF
__term_sd_task_pre_model_164 t5-v1_1-xxl-encoder-Q5_K_M-gguf(3.39g) OFF
__term_sd_task_pre_model_165 t5-v1_1-xxl-encoder-Q5_K_S-gguf(3.29g) OFF
__term_sd_task_pre_model_166 t5-v1_1-xxl-encoder-Q6_K-gguf(3.91g) OFF
__term_sd_task_pre_model_167 t5-v1_1-xxl-encoder-Q8_0-gguf(5.06g) OFF
__term_sd_task_pre_model_168 t5-v1_1-xxl-encoder-f16-gguf(9.53g) OFF
__term_sd_task_pre_model_169 t5-v1_1-xxl-encoder-f32-gguf(19.1g) OFF
__term_sd_task_pre_model_170 ae(335m) OFF
__term_sd_task_pre_model_171 =====VAE模型===== OFF
__term_sd_task_pre_model_172 vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_173 vae-ft-mse-840000-ema-pruned(334.6m) ON
__term_sd_task_pre_model_174 sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_175 sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_176 =====VAE-approx模型===== OFF
__term_sd_task_pre_model_177 model(0.2m) ON
__term_sd_task_pre_model_178 vaeapprox-sdxl(0.2m) ON
__term_sd_task_pre_model_179 vaeapprox-sd3(0.2m) OFF
__term_sd_task_pre_model_180 =====放大模型===== OFF
__term_sd_task_pre_model_181 codeformer-v0.1.0(376.6m) OFF
__term_sd_task_pre_model_182 DAT_2_x2(139.7m) OFF
__term_sd_task_pre_model_183 DAT_2_x3(140.4m) OFF
__term_sd_task_pre_model_184 DAT_2_x4(140.3m) OFF
__term_sd_task_pre_model_185 DAT_S_x2(87.7m) OFF
__term_sd_task_pre_model_186 DAT_S_x3(88.4m) OFF
__term_sd_task_pre_model_187 DAT_S_x4(88.2m) OFF
__term_sd_task_pre_model_188 DAT_light_x2(45.7m) OFF
__term_sd_task_pre_model_189 DAT_light_x3(45.7m) OFF
__term_sd_task_pre_model_190 DAT_light_x4(45.8m) OFF
__term_sd_task_pre_model_191 DAT_x2(154.1m) OFF
__term_sd_task_pre_model_192 DAT_x3(154.8m) OFF
__term_sd_task_pre_model_193 DAT_x4(154.7m) OFF
__term_sd_task_pre_model_194 16xPSNR(67.2m) OFF
__term_sd_task_pre_model_195 1x-ITF-SkinDiffDetail-Lite-v1(20.1m) OFF
__term_sd_task_pre_model_196 1x_NMKD-BrightenRedux_200k(66.6m) OFF
__term_sd_task_pre_model_197 1x_NMKD-YandereInpaint_375000_G(66.6m) OFF
__term_sd_task_pre_model_198 1x_NMKDDetoon_97500_G(66.6m) OFF
__term_sd_task_pre_model_199 1x_NoiseToner-Poisson-Detailed_108000_G(66.6m) OFF
__term_sd_task_pre_model_200 1x_NoiseToner-Uniform-Detailed_100000_G(66.6m) OFF
__term_sd_task_pre_model_201 4x-UltraSharp(66.9m) OFF
__term_sd_task_pre_model_202 4xPSNR(66.9m) OFF
__term_sd_task_pre_model_203 4x_CountryRoads_377000_G(66.9m) OFF
__term_sd_task_pre_model_204 4x_Fatality_Comix_260000_G(66.9m) OFF
__term_sd_task_pre_model_205 4x_NMKD-Siax_200k(66.9m) OFF
__term_sd_task_pre_model_206 4x_NMKD-Superscale-Artisoftject_210000_G(66.9m) OFF
__term_sd_task_pre_model_207 4x_NMKD-Superscale-SP_178000_G(66.9m) ON
__term_sd_task_pre_model_208 4x_NMKD-UltraYandere-Lite_280k(20.1m) OFF
__term_sd_task_pre_model_209 4x_NMKD-UltraYandere_300k(66.9m) OFF
__term_sd_task_pre_model_210 4x_NMKD-YandereNeoXL_200k(66.9m) OFF
__term_sd_task_pre_model_211 4x_NMKDSuperscale_Artisoft_120000_G(67.1m) OFF
__term_sd_task_pre_model_212 4x_NickelbackFS_72000_G(67.1m) OFF
__term_sd_task_pre_model_213 4x_Nickelback_70000G(66.9m) OFF
__term_sd_task_pre_model_214 4x_RealisticRescaler_100000_G(134.1m) OFF
__term_sd_task_pre_model_215 4x_Valar_v1(67.5m) OFF
__term_sd_task_pre_model_216 4x_fatal_Anime_500000_G(66.9m) OFF
__term_sd_task_pre_model_217 4x_foolhardy_Remacri(67m) OFF
__term_sd_task_pre_model_218 8xPSNR(67.1m) OFF
__term_sd_task_pre_model_219 8x_NMKD-Superscale_150000_G(67.1m) OFF
__term_sd_task_pre_model_220 8x_NMKD-Typescale_175k(67.1m) OFF
__term_sd_task_pre_model_221 A_ESRGAN_Single(134.1m) OFF
__term_sd_task_pre_model_222 BSRGAN(67.1m) OFF
__term_sd_task_pre_model_223 BSRGANx2(66.8m) OFF
__term_sd_task_pre_model_224 BSRNet(67.1m) OFF
__term_sd_task_pre_model_225 ESRGAN_4x(66.9m) OFF
__term_sd_task_pre_model_226 LADDIER1_282500_G(66.9m) OFF
__term_sd_task_pre_model_227 4x_UniversalUpscalerV2-Neutral_115000_swaG(66.9m) OFF
__term_sd_task_pre_model_228 4x_UniversalUpscalerV2-Sharp_101000_G(66.9m) OFF
__term_sd_task_pre_model_229 4x_UniversalUpscalerV2-Sharper_103000_G(66.9m) OFF
__term_sd_task_pre_model_230 4x_UniversalUpscaler-Detailed_155000_G(66.9m) OFF
__term_sd_task_pre_model_231 4x_UniversalUpscaler-Soft_190000_G(66.9m) OFF
__term_sd_task_pre_model_232 WaifuGAN_v3_30000(66.9m) OFF
__term_sd_task_pre_model_233 lollypop(66.9m) OFF
__term_sd_task_pre_model_234 sudo_rife4_269.662_testV1_scale1(33.7m) OFF
__term_sd_task_pre_model_235 GFPGANv1.3(348.6m) OFF
__term_sd_task_pre_model_236 GFPGANv1.4(348.6m) OFF
__term_sd_task_pre_model_237 detection_Resnet50_Final(109.5m) OFF
__term_sd_task_pre_model_238 parsing_bisenet(12.2m) OFF
__term_sd_task_pre_model_239 parsing_parsenet(85.3m) OFF
__term_sd_task_pre_model_240 RealESRGAN_x4plus(67m) ON
__term_sd_task_pre_model_241 RealESRGAN_x4plus_anime_6B(17.9m) ON
__term_sd_task_pre_model_242 001_classicalSR_DF2K_s64w8_SwinIR-M_x2(67.2m) OFF
__term_sd_task_pre_model_243 001_classicalSR_DF2K_s64w8_SwinIR-M_x3(68m) OFF
__term_sd_task_pre_model_244 001_classicalSR_DF2K_s64w8_SwinIR-M_x4(67.8m) OFF
__term_sd_task_pre_model_245 001_classicalSR_DF2K_s64w8_SwinIR-M_x8(68.4m) OFF
__term_sd_task_pre_model_246 001_classicalSR_DIV2K_s48w8_SwinIR-M_x2(59m) OFF
__term_sd_task_pre_model_247 001_classicalSR_DIV2K_s48w8_SwinIR-M_x3(59.7m) OFF
__term_sd_task_pre_model_248 001_classicalSR_DIV2K_s48w8_SwinIR-M_x4(59.6m) OFF
__term_sd_task_pre_model_249 001_classicalSR_DIV2K_s48w8_SwinIR-M_x8(60.2m) OFF
__term_sd_task_pre_model_250 Swin2SR_ClassicalSR_X2_64(68.7m) OFF
__term_sd_task_pre_model_251 Swin2SR_ClassicalSR_X4_64(69.3m) OFF
__term_sd_task_pre_model_252 Swin2SR_CompressedSR_X4_48(61.1m) OFF
__term_sd_task_pre_model_253 Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR(68.6m) OFF
__term_sd_task_pre_model_254 SwinIR_4x(142.4m) OFF
__term_sd_task_pre_model_255 =====Embedding模型===== OFF
__term_sd_task_pre_model_256 EasyNegativeV2(0.1m) ON
__term_sd_task_pre_model_257 bad-artist-anime(0.1m) ON
__term_sd_task_pre_model_258 bad-artist(0.1m) ON
__term_sd_task_pre_model_259 bad-hands-5(0.1m) ON
__term_sd_task_pre_model_260 bad-image-v2-39000(0.1m) ON
__term_sd_task_pre_model_261 bad_prompt_version2(0.1m) ON
__term_sd_task_pre_model_262 ng_deepnegative_v1_75t(0.1m) ON
__term_sd_task_pre_model_263 verybadimagenegative_v1.3(0.1m) ON
|
2301_81996401/term-sd
|
install/comfyui/dialog_comfyui_ms_model.sh
|
Shell
|
agpl-3.0
| 16,127
|
__term_sd_task_pre_model_1 =====SDXL大模型===== OFF
__term_sd_task_pre_model_2 sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_3 sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_4 sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_5 cosxl(6.94g) OFF
__term_sd_task_pre_model_6 cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_7 animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_8 animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_9 animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_10 animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_11 animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_12 animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_13 holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_14 kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_15 clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_16 UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_17 RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_18 sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_19 kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_20 kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_21 kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_22 kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_23 kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_24 starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_25 heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_26 heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_27 baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_28 baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_29 sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_30 sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_31 SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_32 SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_33 Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_34 Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_35 Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_36 Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_37 Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_38 Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_39 jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_40 PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_41 miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_42 waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_43 tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_44 noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_45 noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_46 noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_47 noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_48 noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_49 noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_50 noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_51 noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_52 noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_53 noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_54 noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_55 noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_56 noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_57 PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_58 PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_59 ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_60 pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_61 tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_62 omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_63 animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_64 artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_65 artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_66 AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_67 abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_68 animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_69 bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_70 nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_71 CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_72 =====其他模型===== OFF
__term_sd_task_pre_model_73 sd_xl_offset_example-lora_1.0(49.6m) ON
__term_sd_task_pre_model_74 inpaint.fooocus(1.32g) OFF
__term_sd_task_pre_model_75 inpaint_v26.fooocus(1.32g) ON
__term_sd_task_pre_model_76 fooocus_inpaint_head(0.05m) ON
__term_sd_task_pre_model_77 fooocus_expansion(351.2m) ON
__term_sd_task_pre_model_78 fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_79 fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_80 fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_81 fooocus_expansion(2.1m) ON
__term_sd_task_pre_model_82 fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_83 fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_84 fooocus_upscaler_s409985e5(33.6m) ON
__term_sd_task_pre_model_85 vaeapp_sd15(0.2m) ON
__term_sd_task_pre_model_86 xl-to-v1_interposer-v3.1(6.5m) OFF
__term_sd_task_pre_model_87 xl-to-v1_interposer-v4.0(5.6m) ON
__term_sd_task_pre_model_88 xlvaeapp(0.2m) ON
__term_sd_task_pre_model_89 sdxl_lcm_lora(393.8m) ON
__term_sd_task_pre_model_90 control-lora-canny-rank128(395.7m) ON
__term_sd_task_pre_model_91 fooocus_ip_negative(0.01m) ON
__term_sd_task_pre_model_92 fooocus_xl_cpds_128(395.7m) ON
__term_sd_task_pre_model_93 ip-adapter-plus_sdxl_vit-h(1.01g) ON
__term_sd_task_pre_model_94 detection_Resnet50_Final(103.5m) ON
__term_sd_task_pre_model_95 ip-adapter-plus-face_sdxl_vit-h(1.01g) ON
__term_sd_task_pre_model_96 parsing_parsenet(85.3m) ON
|
2301_81996401/term-sd
|
install/fooocus/dialog_fooocus_hf_model.sh
|
Shell
|
agpl-3.0
| 5,864
|
__term_sd_task_pre_model_1 =====SDXL大模型===== OFF
__term_sd_task_pre_model_2 sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_3 sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_4 sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_5 cosxl(6.94g) OFF
__term_sd_task_pre_model_6 cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_7 animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_8 animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_9 animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_10 animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_11 animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_12 animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_13 holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_14 kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_15 clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_16 UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_17 RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_18 sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_19 kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_20 kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_21 kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_22 kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_23 kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_24 starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_25 heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_26 heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_27 baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_28 baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_29 sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_30 sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_31 SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_32 SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_33 Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_34 Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_35 Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_36 Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_37 Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_38 Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_39 jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_40 PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_41 miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_42 waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_43 tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_44 noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_45 noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_46 noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_47 noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_48 noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_49 noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_50 noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_51 noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_52 noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_53 noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_54 noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_55 noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_56 noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_57 PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_58 PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_59 ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_60 pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_61 tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_62 omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_63 animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_64 artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_65 artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_66 AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_67 abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_68 animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_69 bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_70 nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_71 CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_72 =====其他模型===== OFF
__term_sd_task_pre_model_73 sd_xl_offset_example-lora_1.0(49.6m) ON
__term_sd_task_pre_model_74 inpaint.fooocus(1.32g) OFF
__term_sd_task_pre_model_75 inpaint_v26.fooocus(1.32g) ON
__term_sd_task_pre_model_76 fooocus_inpaint_head(0.05m) ON
__term_sd_task_pre_model_77 fooocus_expansion(351.2m) ON
__term_sd_task_pre_model_78 fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_79 fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_80 fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_81 fooocus_expansion(2.1m) ON
__term_sd_task_pre_model_82 fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_83 fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_84 fooocus_upscaler_s409985e5(33.6m) ON
__term_sd_task_pre_model_85 vaeapp_sd15(0.2m) ON
__term_sd_task_pre_model_86 xl-to-v1_interposer-v3.1(6.5m) OFF
__term_sd_task_pre_model_87 xl-to-v1_interposer-v4.0(5.6m) ON
__term_sd_task_pre_model_88 xlvaeapp(0.2m) ON
__term_sd_task_pre_model_89 sdxl_lcm_lora(393.8m) ON
__term_sd_task_pre_model_90 control-lora-canny-rank128(395.7m) ON
__term_sd_task_pre_model_91 fooocus_ip_negative(0.01m) ON
__term_sd_task_pre_model_92 fooocus_xl_cpds_128(395.7m) ON
__term_sd_task_pre_model_93 ip-adapter-plus_sdxl_vit-h(1.01g) ON
__term_sd_task_pre_model_94 detection_Resnet50_Final(103.5m) ON
__term_sd_task_pre_model_95 ip-adapter-plus-face_sdxl_vit-h(1.01g) ON
__term_sd_task_pre_model_96 parsing_parsenet(85.3m) ON
|
2301_81996401/term-sd
|
install/fooocus/dialog_fooocus_ms_model.sh
|
Shell
|
agpl-3.0
| 5,864
|
__term_sd_task_sys term_sd_mkdir "${FOOOCUS_PARENT_PATH}"
__term_sd_task_sys cd "${FOOOCUS_PARENT_PATH}"
__term_sd_task_sys term_sd_tmp_enable_proxy
__term_sd_task_pre_core git_clone_repository https://github.com/lllyasviel/Fooocus "${FOOOCUS_PARENT_PATH}" "${FOOOCUS_FOLDER}"
__term_sd_task_sys is_sd_repo_exist "${FOOOCUS_ROOT_PATH}"
__term_sd_task_sys term_sd_tmp_disable_proxy # 临时取消代理, 避免一些不必要的网络减速
__term_sd_task_pre_core create_venv "${FOOOCUS_ROOT_PATH}"
__term_sd_task_sys enter_venv "${FOOOCUS_ROOT_PATH}"
__term_sd_task_pre_core install_pytorch # 安装 PyTorch
__term_sd_task_pre_core install_python_package -r "${FOOOCUS_ROOT_PATH}"/requirements_versions.txt
__term_sd_task_pre_core set_fooocus_preset # 添加 Term-SD 风格的预设
__term_sd_task_pre_core set_fooocus_lang_config # 为 Fooocus 添加翻译文件
|
2301_81996401/term-sd
|
install/fooocus/fooocus_core.sh
|
Shell
|
agpl-3.0
| 865
|
__term_sd_task_pre_model_1 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_2 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_base_1.0_0.9vae.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_3 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_refiner_1.0_0.9vae.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_4 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_turbo_1.0_fp16.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_5 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/cosxl.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # cosxl(6.94g) OFF
__term_sd_task_pre_model_6 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/cosxl_edit.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_7 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.0-base.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_8 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_9 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_10 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_11 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0-opt.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_12 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0-zero.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_13 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/holodayo-xl-2.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_14 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kivotos-xl-2.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_15 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/clandestine-xl-1.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_16 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/UrangDiffusion-1.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_17 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/RaeDiffusion-XL-v2.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_18 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_anime_V52.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_19 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-delta-rev1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_20 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohakuXLEpsilon_rev1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_21 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-epsilon-rev2.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_22 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-epsilon-rev3.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_23 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-zeta.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_24 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/starryXLV52_v52.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_25 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/heartOfAppleXL_v20.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_26 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/heartOfAppleXL_v30.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_27 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/baxlBartstylexlBlueArchiveFlatCelluloid_xlv1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_28 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/baxlBlueArchiveFlatCelluloidStyle_xlv3.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_29 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sanaexlAnimeV10_v10.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_30 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sanaexlAnimeV10_v11.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_31 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/SanaeXL-Anime-v1.2-aesthetic.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_32 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/SanaeXL-Anime-v1.3-aesthetic.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_33 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v0.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_34 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v0.1-GUIDED.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_35 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v1.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_36 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v1.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_37 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v2.0-stable.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_38 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v2.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_39 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/jruTheJourneyRemains_v25XL.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_40 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_illustriousxl10.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_41 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/miaomiaoHarem_v15a.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_42 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/waiNSFWIllustrious_v80.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_43 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/tIllunai3_v4.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_44 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_earlyAccessVersion.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_45 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred05Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_46 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred075.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_47 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred077.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_48 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred10Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_49 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred11Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_50 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPredTestVersion.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_51 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred05Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_52 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred06Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_53 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred065SVersion.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_54 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred075SVersion.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_55 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred09RVersion.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_56 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred10Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_57 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_nbxl12.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_58 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_nbxlVPredV10.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_59 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/ponyDiffusionV6XL_v6StartWithThisOne.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_60 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/pdForAnime_v20.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_61 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/tPonynai3_v51WeightOptimized.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_62 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/omegaPonyXLAnime_v20.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_63 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animeIllustDiffusion_v061.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_64 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/artiwaifuDiffusion_v10.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_65 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/artiwaifu-diffusion-v2.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_66 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/AnythingXL_xl.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_67 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/abyssorangeXLElse_v10.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_68 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animaPencilXL_v200.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_69 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/bluePencilXL_v401.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_70 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/nekorayxl_v06W3.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_71 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/CounterfeitXL-V1.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_72 # =====其他模型===== OFF
__term_sd_task_pre_model_73 aria2_download https://huggingface.co/licyk/sd-lora/resolve/main/sdxl/sd_xl_offset_example-lora_1.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/loras # sd_xl_offset_example-lora_1.0(49.6m) ON
__term_sd_task_pre_model_74 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/inpaint/inpaint.fooocus.patch "${FOOOCUS_ROOT_PATH}"/models/inpaint # inpaint.fooocus(1.32g) OFF
__term_sd_task_pre_model_75 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/inpaint/inpaint_v26.fooocus.patch "${FOOOCUS_ROOT_PATH}"/models/inpaint # inpaint_v26.fooocus(1.32g) ON
__term_sd_task_pre_model_76 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/inpaint/fooocus_inpaint_head.pth "${FOOOCUS_ROOT_PATH}"/models/inpaint # fooocus_inpaint_head(0.05m) ON
__term_sd_task_pre_model_77 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/prompt_expansion/fooocus_expansion/pytorch_model.bin "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(351.2m) ON
__term_sd_task_pre_model_78 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/prompt_expansion/fooocus_expansion/config.json "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_79 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/prompt_expansion/fooocus_expansion/merges.txt "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_80 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/prompt_expansion/fooocus_expansion/special_tokens_map.json "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_81 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/prompt_expansion/fooocus_expansion/tokenizer.json "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(2.1m) ON
__term_sd_task_pre_model_82 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/prompt_expansion/fooocus_expansion/tokenizer_config.json "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_83 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/prompt_expansion/fooocus_expansion/vocab.json "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_84 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/upscale_models/fooocus_upscaler_s409985e5.bin "${FOOOCUS_ROOT_PATH}"/models/upscale_models # fooocus_upscaler_s409985e5(33.6m) ON
__term_sd_task_pre_model_85 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/vae_approx/vaeapp_sd15.pth "${FOOOCUS_ROOT_PATH}"/models/vae_approx # vaeapp_sd15(0.2m) ON
__term_sd_task_pre_model_86 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/vae_approx/xl-to-v1_interposer-v3.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/vae_approx # xl-to-v1_interposer-v3.1(6.5m) OFF
__term_sd_task_pre_model_87 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/vae_approx/xl-to-v1_interposer-v4.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/vae_approx # xl-to-v1_interposer-v4.0(5.6m) ON
__term_sd_task_pre_model_88 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/vae_approx/xlvaeapp.pth "${FOOOCUS_ROOT_PATH}"/models/vae_approx # xlvaeapp(0.2m) ON
__term_sd_task_pre_model_89 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/loras/sdxl_lcm_lora.safetensors "${FOOOCUS_ROOT_PATH}"/models/loras # sdxl_lcm_lora(393.8m) ON
__term_sd_task_pre_model_90 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/controlnet/control-lora-canny-rank128.safetensors "${FOOOCUS_ROOT_PATH}"/models/controlnet # control-lora-canny-rank128(395.7m) ON
__term_sd_task_pre_model_91 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/controlnet/fooocus_ip_negative.safetensors "${FOOOCUS_ROOT_PATH}"/models/controlnet # fooocus_ip_negative(0.01m) ON
__term_sd_task_pre_model_92 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/controlnet/fooocus_xl_cpds_128.safetensors "${FOOOCUS_ROOT_PATH}"/models/controlnet # fooocus_xl_cpds_128(395.7m) ON
__term_sd_task_pre_model_93 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/controlnet/ip-adapter-plus_sdxl_vit-h.bin "${FOOOCUS_ROOT_PATH}"/models/controlnet # ip-adapter-plus_sdxl_vit-h(1.01g) ON
__term_sd_task_pre_model_94 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/controlnet/detection_Resnet50_Final.pth "${FOOOCUS_ROOT_PATH}"/models/controlnet # detection_Resnet50_Final(103.5m) ON
__term_sd_task_pre_model_95 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/controlnet/ip-adapter-plus-face_sdxl_vit-h.bin "${FOOOCUS_ROOT_PATH}"/models/controlnet # ip-adapter-plus-face_sdxl_vit-h(1.01g) ON
__term_sd_task_pre_model_96 aria2_download https://huggingface.co/licyk/fooocus-model/resolve/main/controlnet/parsing_parsenet.pth "${FOOOCUS_ROOT_PATH}"/models/controlnet # parsing_parsenet(85.3m) ON
|
2301_81996401/term-sd
|
install/fooocus/fooocus_hf_model.sh
|
Shell
|
agpl-3.0
| 20,592
|
__term_sd_task_pre_model_1 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_2 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_base_1.0_0.9vae.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_3 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_refiner_1.0_0.9vae.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_4 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_turbo_1.0_fp16.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_5 get_modelscope_model licyks/sd-model/master/sdxl_1.0/cosxl.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # cosxl(6.94g) OFF
__term_sd_task_pre_model_6 get_modelscope_model licyks/sd-model/master/sdxl_1.0/cosxl_edit.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_7 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.0-base.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_8 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_9 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_10 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_11 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0-opt.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_12 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0-zero.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_13 get_modelscope_model licyks/sd-model/master/sdxl_1.0/holodayo-xl-2.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_14 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kivotos-xl-2.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_15 get_modelscope_model licyks/sd-model/master/sdxl_1.0/clandestine-xl-1.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_16 get_modelscope_model licyks/sd-model/master/sdxl_1.0/UrangDiffusion-1.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_17 get_modelscope_model licyks/sd-model/master/sdxl_1.0/RaeDiffusion-XL-v2.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_18 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_anime_V52.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_19 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-delta-rev1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_20 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohakuXLEpsilon_rev1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_21 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-epsilon-rev2.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_22 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-epsilon-rev3.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_23 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-zeta.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_24 get_modelscope_model licyks/sd-model/master/sdxl_1.0/starryXLV52_v52.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_25 get_modelscope_model licyks/sd-model/master/sdxl_1.0/heartOfAppleXL_v20.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_26 get_modelscope_model licyks/sd-model/master/sdxl_1.0/heartOfAppleXL_v30.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_27 get_modelscope_model licyks/sd-model/master/sdxl_1.0/baxlBartstylexlBlueArchiveFlatCelluloid_xlv1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_28 get_modelscope_model licyks/sd-model/master/sdxl_1.0/baxlBlueArchiveFlatCelluloidStyle_xlv3.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_29 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sanaexlAnimeV10_v10.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_30 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sanaexlAnimeV10_v11.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_31 get_modelscope_model licyks/sd-model/master/sdxl_1.0/SanaeXL-Anime-v1.2-aesthetic.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_32 get_modelscope_model licyks/sd-model/master/sdxl_1.0/SanaeXL-Anime-v1.3-aesthetic.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_33 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v0.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_34 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v0.1-GUIDED.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_35 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v1.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_36 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v1.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_37 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v2.0-stable.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_38 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v2.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_39 get_modelscope_model licyks/sd-model/master/sdxl_1.0/jruTheJourneyRemains_v25XL.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_40 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_illustriousxl10.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_41 get_modelscope_model licyks/sd-model/master/sdxl_1.0/miaomiaoHarem_v15a.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_42 get_modelscope_model licyks/sd-model/master/sdxl_1.0/waiNSFWIllustrious_v80.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_43 get_modelscope_model licyks/sd-model/master/sdxl_1.0/tIllunai3_v4.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_44 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_earlyAccessVersion.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_45 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred05Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_46 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred075.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_47 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred077.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_48 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred10Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_49 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred11Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_50 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPredTestVersion.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_51 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred05Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_52 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred06Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_53 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred065SVersion.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_54 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred075SVersion.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_55 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred09RVersion.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_56 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred10Version.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_57 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_nbxl12.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_58 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_nbxlVPredV10.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_59 get_modelscope_model licyks/sd-model/master/sdxl_1.0/ponyDiffusionV6XL_v6StartWithThisOne.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_60 get_modelscope_model licyks/sd-model/master/sdxl_1.0/pdForAnime_v20.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_61 get_modelscope_model licyks/sd-model/master/sdxl_1.0/tPonynai3_v51WeightOptimized.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_62 get_modelscope_model licyks/sd-model/master/sdxl_1.0/omegaPonyXLAnime_v20.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_63 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animeIllustDiffusion_v061.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_64 get_modelscope_model licyks/sd-model/master/sdxl_1.0/artiwaifuDiffusion_v10.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_65 get_modelscope_model licyks/sd-model/master/sdxl_1.0/artiwaifu-diffusion-v2.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_66 get_modelscope_model licyks/sd-model/master/sdxl_1.0/AnythingXL_xl.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_67 get_modelscope_model licyks/sd-model/master/sdxl_1.0/abyssorangeXLElse_v10.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_68 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animaPencilXL_v200.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_69 get_modelscope_model licyks/sd-model/master/sdxl_1.0/bluePencilXL_v401.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_70 get_modelscope_model licyks/sd-model/master/sdxl_1.0/nekorayxl_v06W3.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_71 get_modelscope_model licyks/sd-model/master/sdxl_1.0/CounterfeitXL-V1.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/checkpoints # CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_72 # =====其他模型===== OFF
__term_sd_task_pre_model_73 get_modelscope_model licyks/sd-lora/master/sdxl/sd_xl_offset_example-lora_1.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/loras # sd_xl_offset_example-lora_1.0(49.6m) ON
__term_sd_task_pre_model_74 get_modelscope_model licyks/fooocus-model/master/inpaint/inpaint.fooocus.patch "${FOOOCUS_ROOT_PATH}"/models/inpaint # inpaint.fooocus(1.32g) OFF
__term_sd_task_pre_model_75 get_modelscope_model licyks/fooocus-model/master/inpaint/inpaint_v26.fooocus.patch "${FOOOCUS_ROOT_PATH}"/models/inpaint # inpaint_v26.fooocus(1.32g) ON
__term_sd_task_pre_model_76 get_modelscope_model licyks/fooocus-model/master/inpaint/fooocus_inpaint_head.pth "${FOOOCUS_ROOT_PATH}"/models/inpaint # fooocus_inpaint_head(0.05m) ON
__term_sd_task_pre_model_77 get_modelscope_model licyks/fooocus-model/master/prompt_expansion/fooocus_expansion/pytorch_model.bin "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(351.2m) ON
__term_sd_task_pre_model_78 get_modelscope_model licyks/fooocus-model/master/prompt_expansion/fooocus_expansion/config.json "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_79 get_modelscope_model licyks/fooocus-model/master/prompt_expansion/fooocus_expansion/merges.txt "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_80 get_modelscope_model licyks/fooocus-model/master/prompt_expansion/fooocus_expansion/special_tokens_map.json "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_81 get_modelscope_model licyks/fooocus-model/master/prompt_expansion/fooocus_expansion/tokenizer.json "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(2.1m) ON
__term_sd_task_pre_model_82 get_modelscope_model licyks/fooocus-model/master/prompt_expansion/fooocus_expansion/tokenizer_config.json "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_83 get_modelscope_model licyks/fooocus-model/master/prompt_expansion/fooocus_expansion/vocab.json "${FOOOCUS_ROOT_PATH}"/models/prompt_expansion/fooocus_expansion # fooocus_expansion(0.1m) ON
__term_sd_task_pre_model_84 get_modelscope_model licyks/fooocus-model/master/upscale_models/fooocus_upscaler_s409985e5.bin "${FOOOCUS_ROOT_PATH}"/models/upscale_models # fooocus_upscaler_s409985e5(33.6m) ON
__term_sd_task_pre_model_85 get_modelscope_model licyks/fooocus-model/master/vae_approx/vaeapp_sd15.pth "${FOOOCUS_ROOT_PATH}"/models/vae_approx # vaeapp_sd15(0.2m) ON
__term_sd_task_pre_model_86 get_modelscope_model licyks/fooocus-model/master/vae_approx/xl-to-v1_interposer-v3.1.safetensors "${FOOOCUS_ROOT_PATH}"/models/vae_approx # xl-to-v1_interposer-v3.1(6.5m) OFF
__term_sd_task_pre_model_87 get_modelscope_model licyks/fooocus-model/master/vae_approx/xl-to-v1_interposer-v4.0.safetensors "${FOOOCUS_ROOT_PATH}"/models/vae_approx # xl-to-v1_interposer-v4.0(5.6m) ON
__term_sd_task_pre_model_88 get_modelscope_model licyks/fooocus-model/master/vae_approx/xlvaeapp.pth "${FOOOCUS_ROOT_PATH}"/models/vae_approx # xlvaeapp(0.2m) ON
__term_sd_task_pre_model_89 get_modelscope_model licyks/fooocus-model/master/loras/sdxl_lcm_lora.safetensors "${FOOOCUS_ROOT_PATH}"/models/loras # sdxl_lcm_lora(393.8m) ON
__term_sd_task_pre_model_90 get_modelscope_model licyks/fooocus-model/master/controlnet/control-lora-canny-rank128.safetensors "${FOOOCUS_ROOT_PATH}"/models/controlnet # control-lora-canny-rank128(395.7m) ON
__term_sd_task_pre_model_91 get_modelscope_model licyks/fooocus-model/master/controlnet/fooocus_ip_negative.safetensors "${FOOOCUS_ROOT_PATH}"/models/controlnet # fooocus_ip_negative(0.01m) ON
__term_sd_task_pre_model_92 get_modelscope_model licyks/fooocus-model/master/controlnet/fooocus_xl_cpds_128.safetensors "${FOOOCUS_ROOT_PATH}"/models/controlnet # fooocus_xl_cpds_128(395.7m) ON
__term_sd_task_pre_model_93 get_modelscope_model licyks/fooocus-model/master/controlnet/ip-adapter-plus_sdxl_vit-h.bin "${FOOOCUS_ROOT_PATH}"/models/controlnet # ip-adapter-plus_sdxl_vit-h(1.01g) ON
__term_sd_task_pre_model_94 get_modelscope_model licyks/fooocus-model/master/controlnet/detection_Resnet50_Final.pth "${FOOOCUS_ROOT_PATH}"/models/controlnet # detection_Resnet50_Final(103.5m) ON
__term_sd_task_pre_model_95 get_modelscope_model licyks/fooocus-model/master/controlnet/ip-adapter-plus-face_sdxl_vit-h.bin "${FOOOCUS_ROOT_PATH}"/models/controlnet # ip-adapter-plus-face_sdxl_vit-h(1.01g) ON
__term_sd_task_pre_model_96 get_modelscope_model licyks/fooocus-model/master/controlnet/parsing_parsenet.pth "${FOOOCUS_ROOT_PATH}"/models/controlnet # parsing_parsenet(85.3m) ON
|
2301_81996401/term-sd
|
install/fooocus/fooocus_ms_model.sh
|
Shell
|
agpl-3.0
| 18,524
|
__term_sd_task_pre_ext_1 invoke_tipo ON
__term_sd_task_pre_ext_2 invoke_wd14_tagger ON
__term_sd_task_pre_ext_3 adapters-linked-nodes OFF
__term_sd_task_pre_ext_4 average-images-node OFF
__term_sd_task_pre_ext_5 clean-artifact-after-cut-node OFF
__term_sd_task_pre_ext_6 close-color-mask-node OFF
__term_sd_task_pre_ext_7 clothing-mask-node OFF
__term_sd_task_pre_ext_8 clahe-node OFF
__term_sd_task_pre_ext_9 depth-from-obj-node OFF
__term_sd_task_pre_ext_10 enhance-detail-node OFF
__term_sd_task_pre_ext_11 film-grain-node OFF
__term_sd_task_pre_ext_12 GPT2RandomPromptMaker OFF
__term_sd_task_pre_ext_13 GridToGif.py OFF
__term_sd_task_pre_ext_14 invoke_meshgraphormer OFF
__term_sd_task_pre_ext_15 halftone-node OFF
__term_sd_task_pre_ext_16 composition-nodes OFF
__term_sd_task_pre_ext_17 imagetoasciiimage OFF
__term_sd_task_pre_ext_18 image-picker-node OFF
__term_sd_task_pre_ext_19 image-resize-plus-node OFF
__term_sd_task_pre_ext_20 latent-upscale OFF
__term_sd_task_pre_ext_21 load_video_frame OFF
__term_sd_task_pre_ext_22 mask-operations-node OFF
__term_sd_task_pre_ext_23 metadata-linked-nodes OFF
__term_sd_task_pre_ext_24 Prompt-tools-nodes OFF
__term_sd_task_pre_ext_25 invoke_bria_rmbg ON
__term_sd_task_pre_ext_26 remove-background-node OFF
__term_sd_task_pre_ext_27 XYGrid_nodes ON
|
2301_81996401/term-sd
|
install/invokeai/dialog_invokeai_custom_node.sh
|
Shell
|
agpl-3.0
| 1,303
|
__term_sd_task_pre_model_1 (提示：) OFF
__term_sd_task_pre_model_2 (建议使用InvokeAI自带的模型管理下载和添加模型) OFF
__term_sd_task_pre_model_3 (不推荐使用Term-SD下载InvokeAI的模型) OFF
__term_sd_task_pre_model_4 =====核心模型===== OFF
__term_sd_task_pre_model_5 bert-base-uncased OFF
__term_sd_task_pre_model_6 bert-base-uncased OFF
__term_sd_task_pre_model_7 bert-base-uncased OFF
__term_sd_task_pre_model_8 bert-base-uncased OFF
__term_sd_task_pre_model_9 CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_10 CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_11 CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_12 CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_13 CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_14 clip-vit-large-patch14 OFF
__term_sd_task_pre_model_15 clip-vit-large-patch14 OFF
__term_sd_task_pre_model_16 clip-vit-large-patch14(492.3m) OFF
__term_sd_task_pre_model_17 clip-vit-large-patch14 OFF
__term_sd_task_pre_model_18 clip-vit-large-patch14 OFF
__term_sd_task_pre_model_19 clip-vit-large-patch14 OFF
__term_sd_task_pre_model_20 stable-diffusion-2-clip OFF
__term_sd_task_pre_model_21 stable-diffusion-2-clip(1.36g) OFF
__term_sd_task_pre_model_22 stable-diffusion-2-clip OFF
__term_sd_task_pre_model_23 stable-diffusion-2-clip OFF
__term_sd_task_pre_model_24 stable-diffusion-2-clip OFF
__term_sd_task_pre_model_25 stable-diffusion-2-clip OFF
__term_sd_task_pre_model_26 stable-diffusion-safety-checker OFF
__term_sd_task_pre_model_27 stable-diffusion-safety-checker(1.22g) OFF
__term_sd_task_pre_model_28 stable-diffusion-safety-checker OFF
__term_sd_task_pre_model_29 lama(205.6m) OFF
__term_sd_task_pre_model_30 =====放大模型===== OFF
__term_sd_task_pre_model_31 ESRGAN_SRx4_DF2KOST_official-ff704c30(66.9m) OFF
__term_sd_task_pre_model_32 RealESRGAN_x2plus(67m) OFF
__term_sd_task_pre_model_33 RealESRGAN_x4plus(67m) OFF
__term_sd_task_pre_model_34 RealESRGAN_x4plus_anime_6B(17.9m) OFF
__term_sd_task_pre_model_35 =====配置文件===== OFF
__term_sd_task_pre_model_36 INITIAL_MODELS OFF
__term_sd_task_pre_model_37 models.yaml OFF
__term_sd_task_pre_model_38 models.yaml.example OFF
__term_sd_task_pre_model_39 sd_xl_base.yaml OFF
__term_sd_task_pre_model_40 sd_xl_refiner.yaml OFF
__term_sd_task_pre_model_41 v1-finetune.yaml OFF
__term_sd_task_pre_model_42 v1-finetune_style.yaml OFF
__term_sd_task_pre_model_43 v1-inference-v.yaml OFF
__term_sd_task_pre_model_44 v1-inference.yaml OFF
__term_sd_task_pre_model_45 v1-inpainting-inference.yaml OFF
__term_sd_task_pre_model_46 v1-m1-finetune.yaml OFF
__term_sd_task_pre_model_47 v2-inference-v.yaml OFF
__term_sd_task_pre_model_48 v2-inference.yaml OFF
__term_sd_task_pre_model_49 v2-inpainting-inference-v.yaml OFF
__term_sd_task_pre_model_50 v2-inpainting-inference.yaml OFF
__term_sd_task_pre_model_51 =====基础模型===== OFF
__term_sd_task_pre_model_52 =====SD1.5大模型===== OFF
__term_sd_task_pre_model_53 sd1.5-official OFF
__term_sd_task_pre_model_54 sd1.5-official OFF
__term_sd_task_pre_model_55 sd1.5-official OFF
__term_sd_task_pre_model_56 sd1.5-official OFF
__term_sd_task_pre_model_57 sd1.5-official(246.1m) OFF
__term_sd_task_pre_model_58 sd1.5-official OFF
__term_sd_task_pre_model_59 sd1.5-official OFF
__term_sd_task_pre_model_60 sd1.5-official OFF
__term_sd_task_pre_model_61 sd1.5-official OFF
__term_sd_task_pre_model_62 sd1.5-official OFF
__term_sd_task_pre_model_63 sd1.5-official(1.72g) OFF
__term_sd_task_pre_model_64 sd1.5-official OFF
__term_sd_task_pre_model_65 sd1.5-official(167.3m) OFF
__term_sd_task_pre_model_66 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_67 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_68 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_69 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_70 sd1.5-inpaint-official(246.1m) OFF
__term_sd_task_pre_model_71 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_72 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_73 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_74 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_75 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_76 sd1.5-inpaint-official(1.72g) OFF
__term_sd_task_pre_model_77 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_78 sd1.5-inpaint-official(167.3m) OFF
__term_sd_task_pre_model_79 openjourney OFF
__term_sd_task_pre_model_80 openjourney OFF
__term_sd_task_pre_model_81 openjourney OFF
__term_sd_task_pre_model_82 openjourney OFF
__term_sd_task_pre_model_83 openjourney(246.1m) OFF
__term_sd_task_pre_model_84 openjourney OFF
__term_sd_task_pre_model_85 openjourney OFF
__term_sd_task_pre_model_86 openjourney OFF
__term_sd_task_pre_model_87 openjourney OFF
__term_sd_task_pre_model_88 openjourney OFF
__term_sd_task_pre_model_89 openjourney(1.72g) OFF
__term_sd_task_pre_model_90 openjourney OFF
__term_sd_task_pre_model_91 openjourney(246.1m) OFF
__term_sd_task_pre_model_92 =====SD2.1大模型===== OFF
__term_sd_task_pre_model_93 sd2.1-official OFF
__term_sd_task_pre_model_94 sd2.1-official OFF
__term_sd_task_pre_model_95 sd2.1-official OFF
__term_sd_task_pre_model_96 sd2.1-official OFF
__term_sd_task_pre_model_97 sd2.1-official(680.8m) OFF
__term_sd_task_pre_model_98 sd2.1-official OFF
__term_sd_task_pre_model_99 sd2.1-official OFF
__term_sd_task_pre_model_100 sd2.1-official OFF
__term_sd_task_pre_model_101 sd2.1-official OFF
__term_sd_task_pre_model_102 sd2.1-official OFF
__term_sd_task_pre_model_103 sd2.1-official(1.73g) OFF
__term_sd_task_pre_model_104 sd2.1-official OFF
__term_sd_task_pre_model_105 sd2.1-official(167.3m) OFF
__term_sd_task_pre_model_106 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_107 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_108 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_109 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_110 sd2.1-inpaint-official(680.8m) OFF
__term_sd_task_pre_model_111 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_112 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_113 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_114 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_115 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_116 sd2.1-inpaint-official(1.73g) OFF
__term_sd_task_pre_model_117 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_118 sd2.1-inpaint-official(167.3m) OFF
__term_sd_task_pre_model_119 =====SDXL大模型===== OFF
__term_sd_task_pre_model_120 sdxl OFF
__term_sd_task_pre_model_121 sdxl OFF
__term_sd_task_pre_model_122 sdxl OFF
__term_sd_task_pre_model_123 sdxl(246.1m) OFF
__term_sd_task_pre_model_124 sdxl OFF
__term_sd_task_pre_model_125 sdxl(1.39g) OFF
__term_sd_task_pre_model_126 sdxl OFF
__term_sd_task_pre_model_127 sdxl OFF
__term_sd_task_pre_model_128 sdxl OFF
__term_sd_task_pre_model_129 sdxl OFF
__term_sd_task_pre_model_130 sdxl OFF
__term_sd_task_pre_model_131 sdxl OFF
__term_sd_task_pre_model_132 sdxl OFF
__term_sd_task_pre_model_133 sdxl OFF
__term_sd_task_pre_model_134 sdxl OFF
__term_sd_task_pre_model_135 sdxl(5.14g) OFF
__term_sd_task_pre_model_136 sdxl OFF
__term_sd_task_pre_model_137 sdxl(167.3m) OFF
__term_sd_task_pre_model_138 sdxl-refind OFF
__term_sd_task_pre_model_139 sdxl-refind OFF
__term_sd_task_pre_model_140 sdxl-refind OFF
__term_sd_task_pre_model_141 sdxl-refind(1.39g) OFF
__term_sd_task_pre_model_142 sdxl-refind OFF
__term_sd_task_pre_model_143 sdxl-refind OFF
__term_sd_task_pre_model_144 sdxl-refind OFF
__term_sd_task_pre_model_145 sdxl-refind OFF
__term_sd_task_pre_model_146 sdxl-refind OFF
__term_sd_task_pre_model_147 sdxl-refind(5.14g) OFF
__term_sd_task_pre_model_148 sdxl-refind OFF
__term_sd_task_pre_model_149 sdxl-refind(167.3m) OFF
__term_sd_task_pre_model_150 =====VAE模型===== OFF
__term_sd_task_pre_model_151 sd-vae-ft-mse OFF
__term_sd_task_pre_model_152 sd-vae-ft-mse(334.6m) OFF
__term_sd_task_pre_model_153 sdxl-vae OFF
__term_sd_task_pre_model_154 sdxl-vae(334.6m) OFF
__term_sd_task_pre_model_155 =====Embedding模型===== OFF
__term_sd_task_pre_model_156 EasyNegative(0.1m) OFF
__term_sd_task_pre_model_157 ahx-beta-453407d(0.1m) OFF
__term_sd_task_pre_model_158 =====控制模型===== OFF
__term_sd_task_pre_model_159 =====ControlNet(SD1.5)模型===== OFF
__term_sd_task_pre_model_160 canny OFF
__term_sd_task_pre_model_161 canny(1.45g) OFF
__term_sd_task_pre_model_162 depth OFF
__term_sd_task_pre_model_163 depth(1.45g) OFF
__term_sd_task_pre_model_164 inpaint OFF
__term_sd_task_pre_model_165 inpaint(1.45g) OFF
__term_sd_task_pre_model_166 ip2p OFF
__term_sd_task_pre_model_167 ip2p(1.45g) OFF
__term_sd_task_pre_model_168 lineart OFF
__term_sd_task_pre_model_169 lineart(1.45g) OFF
__term_sd_task_pre_model_170 lineart-anime OFF
__term_sd_task_pre_model_171 lineart-anime(1.45g) OFF
__term_sd_task_pre_model_172 mlsd OFF
__term_sd_task_pre_model_173 mlsd(1.45g) OFF
__term_sd_task_pre_model_174 normal-bae OFF
__term_sd_task_pre_model_175 normal-bae(1.45g) OFF
__term_sd_task_pre_model_176 openpose OFF
__term_sd_task_pre_model_177 openpose(1.45g) OFF
__term_sd_task_pre_model_178 qrcode OFF
__term_sd_task_pre_model_179 qrcode(1.45g) OFF
__term_sd_task_pre_model_180 scribble OFF
__term_sd_task_pre_model_181 scribble(1.45g) OFF
__term_sd_task_pre_model_182 seg OFF
__term_sd_task_pre_model_183 seg(1.45g) OFF
__term_sd_task_pre_model_184 shuffle OFF
__term_sd_task_pre_model_185 shuffle(1.45g) OFF
__term_sd_task_pre_model_186 softedge OFF
__term_sd_task_pre_model_187 softedge(1.45g) OFF
__term_sd_task_pre_model_188 tile OFF
__term_sd_task_pre_model_189 tile(1.45g) OFF
__term_sd_task_pre_model_190 =====T2I-Adapter(SD1.5)模型===== OFF
__term_sd_task_pre_model_191 canny OFF
__term_sd_task_pre_model_192 canny(308m) OFF
__term_sd_task_pre_model_193 depth OFF
__term_sd_task_pre_model_194 depth(308m) OFF
__term_sd_task_pre_model_195 sketch OFF
__term_sd_task_pre_model_196 sketch(308m) OFF
__term_sd_task_pre_model_197 zoedepth OFF
__term_sd_task_pre_model_198 zoedepth(308m) OFF
__term_sd_task_pre_model_199 =====T2I-Adapter(SDXL)模型===== OFF
__term_sd_task_pre_model_200 canny OFF
__term_sd_task_pre_model_201 canny(316m) OFF
__term_sd_task_pre_model_202 lineart OFF
__term_sd_task_pre_model_203 lineart(316m) OFF
__term_sd_task_pre_model_204 sketch OFF
__term_sd_task_pre_model_205 sketch(316m) OFF
__term_sd_task_pre_model_206 zoedepth OFF
__term_sd_task_pre_model_207 zoedepth(316m) OFF
__term_sd_task_pre_model_208 =====IP-Adapter(SD1.5)模型===== OFF
__term_sd_task_pre_model_209 clip_vision OFF
__term_sd_task_pre_model_210 clip_vision(2.53g) OFF
__term_sd_task_pre_model_211 plus-face OFF
__term_sd_task_pre_model_212 plus-face(98.1m) OFF
__term_sd_task_pre_model_213 plus OFF
__term_sd_task_pre_model_214 plus(158m) OFF
__term_sd_task_pre_model_215 normal OFF
__term_sd_task_pre_model_216 normal(44.6m) OFF
__term_sd_task_pre_model_217 =====IP-Adapter(SDXL)模型===== OFF
__term_sd_task_pre_model_218 clip_vision OFF
__term_sd_task_pre_model_219 clip_vision(3.69g) OFF
__term_sd_task_pre_model_220 normal OFF
__term_sd_task_pre_model_221 normal(702.6m) OFF
|
2301_81996401/term-sd
|
install/invokeai/dialog_invokeai_hf_model.sh
|
Shell
|
agpl-3.0
| 11,101
|
__term_sd_task_pre_model_1 (提示：) OFF
__term_sd_task_pre_model_2 (建议使用InvokeAI自带的模型管理下载和添加模型) OFF
__term_sd_task_pre_model_3 (不推荐使用Term-SD下载InvokeAI的模型) OFF
__term_sd_task_pre_model_4 =====核心模型===== OFF
__term_sd_task_pre_model_5 bert-base-uncased OFF
__term_sd_task_pre_model_6 bert-base-uncased OFF
__term_sd_task_pre_model_7 bert-base-uncased OFF
__term_sd_task_pre_model_8 bert-base-uncased OFF
__term_sd_task_pre_model_9 CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_10 CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_11 CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_12 CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_13 CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_14 clip-vit-large-patch14 OFF
__term_sd_task_pre_model_15 clip-vit-large-patch14 OFF
__term_sd_task_pre_model_16 clip-vit-large-patch14(492.3m) OFF
__term_sd_task_pre_model_17 clip-vit-large-patch14 OFF
__term_sd_task_pre_model_18 clip-vit-large-patch14 OFF
__term_sd_task_pre_model_19 clip-vit-large-patch14 OFF
__term_sd_task_pre_model_20 stable-diffusion-2-clip OFF
__term_sd_task_pre_model_21 stable-diffusion-2-clip(1.36g) OFF
__term_sd_task_pre_model_22 stable-diffusion-2-clip OFF
__term_sd_task_pre_model_23 stable-diffusion-2-clip OFF
__term_sd_task_pre_model_24 stable-diffusion-2-clip OFF
__term_sd_task_pre_model_25 stable-diffusion-2-clip OFF
__term_sd_task_pre_model_26 stable-diffusion-safety-checker OFF
__term_sd_task_pre_model_27 stable-diffusion-safety-checker(1.22g) OFF
__term_sd_task_pre_model_28 stable-diffusion-safety-checker OFF
__term_sd_task_pre_model_29 lama(205.6m) OFF
__term_sd_task_pre_model_30 =====放大模型===== OFF
__term_sd_task_pre_model_31 ESRGAN_SRx4_DF2KOST_official-ff704c30(66.9m) OFF
__term_sd_task_pre_model_32 RealESRGAN_x2plus(67m) OFF
__term_sd_task_pre_model_33 RealESRGAN_x4plus(67m) OFF
__term_sd_task_pre_model_34 RealESRGAN_x4plus_anime_6B(17.9m) OFF
__term_sd_task_pre_model_35 =====配置文件===== OFF
__term_sd_task_pre_model_36 INITIAL_MODELS OFF
__term_sd_task_pre_model_37 models.yaml OFF
__term_sd_task_pre_model_38 models.yaml.example OFF
__term_sd_task_pre_model_39 sd_xl_base.yaml OFF
__term_sd_task_pre_model_40 sd_xl_refiner.yaml OFF
__term_sd_task_pre_model_41 v1-finetune.yaml OFF
__term_sd_task_pre_model_42 v1-finetune_style.yaml OFF
__term_sd_task_pre_model_43 v1-inference-v.yaml OFF
__term_sd_task_pre_model_44 v1-inference.yaml OFF
__term_sd_task_pre_model_45 v1-inpainting-inference.yaml OFF
__term_sd_task_pre_model_46 v1-m1-finetune.yaml OFF
__term_sd_task_pre_model_47 v2-inference-v.yaml OFF
__term_sd_task_pre_model_48 v2-inference.yaml OFF
__term_sd_task_pre_model_49 v2-inpainting-inference-v.yaml OFF
__term_sd_task_pre_model_50 v2-inpainting-inference.yaml OFF
__term_sd_task_pre_model_51 =====基础模型===== OFF
__term_sd_task_pre_model_52 =====SD1.5大模型===== OFF
__term_sd_task_pre_model_53 sd1.5-official OFF
__term_sd_task_pre_model_54 sd1.5-official OFF
__term_sd_task_pre_model_55 sd1.5-official OFF
__term_sd_task_pre_model_56 sd1.5-official OFF
__term_sd_task_pre_model_57 sd1.5-official(246.1m) OFF
__term_sd_task_pre_model_58 sd1.5-official OFF
__term_sd_task_pre_model_59 sd1.5-official OFF
__term_sd_task_pre_model_60 sd1.5-official OFF
__term_sd_task_pre_model_61 sd1.5-official OFF
__term_sd_task_pre_model_62 sd1.5-official OFF
__term_sd_task_pre_model_63 sd1.5-official(1.72g) OFF
__term_sd_task_pre_model_64 sd1.5-official OFF
__term_sd_task_pre_model_65 sd1.5-official(167.3m) OFF
__term_sd_task_pre_model_66 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_67 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_68 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_69 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_70 sd1.5-inpaint-official(246.1m) OFF
__term_sd_task_pre_model_71 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_72 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_73 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_74 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_75 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_76 sd1.5-inpaint-official(1.72g) OFF
__term_sd_task_pre_model_77 sd1.5-inpaint-official OFF
__term_sd_task_pre_model_78 sd1.5-inpaint-official(167.3m) OFF
__term_sd_task_pre_model_79 openjourney OFF
__term_sd_task_pre_model_80 openjourney OFF
__term_sd_task_pre_model_81 openjourney OFF
__term_sd_task_pre_model_82 openjourney OFF
__term_sd_task_pre_model_83 openjourney(246.1m) OFF
__term_sd_task_pre_model_84 openjourney OFF
__term_sd_task_pre_model_85 openjourney OFF
__term_sd_task_pre_model_86 openjourney OFF
__term_sd_task_pre_model_87 openjourney OFF
__term_sd_task_pre_model_88 openjourney OFF
__term_sd_task_pre_model_89 openjourney(1.72g) OFF
__term_sd_task_pre_model_90 openjourney OFF
__term_sd_task_pre_model_91 openjourney(246.1m) OFF
__term_sd_task_pre_model_92 =====SD2.1大模型===== OFF
__term_sd_task_pre_model_93 sd2.1-official OFF
__term_sd_task_pre_model_94 sd2.1-official OFF
__term_sd_task_pre_model_95 sd2.1-official OFF
__term_sd_task_pre_model_96 sd2.1-official OFF
__term_sd_task_pre_model_97 sd2.1-official(680.8m) OFF
__term_sd_task_pre_model_98 sd2.1-official OFF
__term_sd_task_pre_model_99 sd2.1-official OFF
__term_sd_task_pre_model_100 sd2.1-official OFF
__term_sd_task_pre_model_101 sd2.1-official OFF
__term_sd_task_pre_model_102 sd2.1-official OFF
__term_sd_task_pre_model_103 sd2.1-official(1.73g) OFF
__term_sd_task_pre_model_104 sd2.1-official OFF
__term_sd_task_pre_model_105 sd2.1-official(167.3m) OFF
__term_sd_task_pre_model_106 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_107 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_108 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_109 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_110 sd2.1-inpaint-official(680.8m) OFF
__term_sd_task_pre_model_111 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_112 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_113 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_114 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_115 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_116 sd2.1-inpaint-official(1.73g) OFF
__term_sd_task_pre_model_117 sd2.1-inpaint-official OFF
__term_sd_task_pre_model_118 sd2.1-inpaint-official(167.3m) OFF
__term_sd_task_pre_model_119 =====SDXL大模型===== OFF
__term_sd_task_pre_model_120 sdxl OFF
__term_sd_task_pre_model_121 sdxl OFF
__term_sd_task_pre_model_122 sdxl OFF
__term_sd_task_pre_model_123 sdxl(246.1m) OFF
__term_sd_task_pre_model_124 sdxl OFF
__term_sd_task_pre_model_125 sdxl(1.39g) OFF
__term_sd_task_pre_model_126 sdxl OFF
__term_sd_task_pre_model_127 sdxl OFF
__term_sd_task_pre_model_128 sdxl OFF
__term_sd_task_pre_model_129 sdxl OFF
__term_sd_task_pre_model_130 sdxl OFF
__term_sd_task_pre_model_131 sdxl OFF
__term_sd_task_pre_model_132 sdxl OFF
__term_sd_task_pre_model_133 sdxl OFF
__term_sd_task_pre_model_134 sdxl OFF
__term_sd_task_pre_model_135 sdxl(5.14g) OFF
__term_sd_task_pre_model_136 sdxl OFF
__term_sd_task_pre_model_137 sdxl(167.3m) OFF
__term_sd_task_pre_model_138 sdxl-refind OFF
__term_sd_task_pre_model_139 sdxl-refind OFF
__term_sd_task_pre_model_140 sdxl-refind OFF
__term_sd_task_pre_model_141 sdxl-refind(1.39g) OFF
__term_sd_task_pre_model_142 sdxl-refind OFF
__term_sd_task_pre_model_143 sdxl-refind OFF
__term_sd_task_pre_model_144 sdxl-refind OFF
__term_sd_task_pre_model_145 sdxl-refind OFF
__term_sd_task_pre_model_146 sdxl-refind OFF
__term_sd_task_pre_model_147 sdxl-refind(5.14g) OFF
__term_sd_task_pre_model_148 sdxl-refind OFF
__term_sd_task_pre_model_149 sdxl-refind(167.3m) OFF
__term_sd_task_pre_model_150 =====VAE模型===== OFF
__term_sd_task_pre_model_151 sd-vae-ft-mse OFF
__term_sd_task_pre_model_152 sd-vae-ft-mse(334.6m) OFF
__term_sd_task_pre_model_153 sdxl-vae OFF
__term_sd_task_pre_model_154 sdxl-vae(334.6m) OFF
__term_sd_task_pre_model_155 =====Embedding模型===== OFF
__term_sd_task_pre_model_156 EasyNegative(0.1m) OFF
__term_sd_task_pre_model_157 ahx-beta-453407d(0.1m) OFF
__term_sd_task_pre_model_158 =====控制模型===== OFF
__term_sd_task_pre_model_159 =====ControlNet(SD1.5)模型===== OFF
__term_sd_task_pre_model_160 canny OFF
__term_sd_task_pre_model_161 canny(1.45g) OFF
__term_sd_task_pre_model_162 depth OFF
__term_sd_task_pre_model_163 depth(1.45g) OFF
__term_sd_task_pre_model_164 inpaint OFF
__term_sd_task_pre_model_165 inpaint(1.45g) OFF
__term_sd_task_pre_model_166 ip2p OFF
__term_sd_task_pre_model_167 ip2p(1.45g) OFF
__term_sd_task_pre_model_168 lineart OFF
__term_sd_task_pre_model_169 lineart(1.45g) OFF
__term_sd_task_pre_model_170 lineart-anime OFF
__term_sd_task_pre_model_171 lineart-anime(1.45g) OFF
__term_sd_task_pre_model_172 mlsd OFF
__term_sd_task_pre_model_173 mlsd(1.45g) OFF
__term_sd_task_pre_model_174 normal-bae OFF
__term_sd_task_pre_model_175 normal-bae(1.45g) OFF
__term_sd_task_pre_model_176 openpose OFF
__term_sd_task_pre_model_177 openpose(1.45g) OFF
__term_sd_task_pre_model_178 qrcode OFF
__term_sd_task_pre_model_179 qrcode(1.45g) OFF
__term_sd_task_pre_model_180 scribble OFF
__term_sd_task_pre_model_181 scribble(1.45g) OFF
__term_sd_task_pre_model_182 seg OFF
__term_sd_task_pre_model_183 seg(1.45g) OFF
__term_sd_task_pre_model_184 shuffle OFF
__term_sd_task_pre_model_185 shuffle(1.45g) OFF
__term_sd_task_pre_model_186 softedge OFF
__term_sd_task_pre_model_187 softedge(1.45g) OFF
__term_sd_task_pre_model_188 tile OFF
__term_sd_task_pre_model_189 tile(1.45g) OFF
__term_sd_task_pre_model_190 =====T2I-Adapter(SD1.5)模型===== OFF
__term_sd_task_pre_model_191 canny OFF
__term_sd_task_pre_model_192 canny(308m) OFF
__term_sd_task_pre_model_193 depth OFF
__term_sd_task_pre_model_194 depth(308m) OFF
__term_sd_task_pre_model_195 sketch OFF
__term_sd_task_pre_model_196 sketch(308m) OFF
__term_sd_task_pre_model_197 zoedepth OFF
__term_sd_task_pre_model_198 zoedepth(308m) OFF
__term_sd_task_pre_model_199 =====T2I-Adapter(SDXL)模型===== OFF
__term_sd_task_pre_model_200 canny OFF
__term_sd_task_pre_model_201 canny(316m) OFF
__term_sd_task_pre_model_202 lineart OFF
__term_sd_task_pre_model_203 lineart(316m) OFF
__term_sd_task_pre_model_204 sketch OFF
__term_sd_task_pre_model_205 sketch(316m) OFF
__term_sd_task_pre_model_206 zoedepth OFF
__term_sd_task_pre_model_207 zoedepth(316m) OFF
__term_sd_task_pre_model_208 =====IP-Adapter(SD1.5)模型===== OFF
__term_sd_task_pre_model_209 clip_vision OFF
__term_sd_task_pre_model_210 clip_vision(2.53g) OFF
__term_sd_task_pre_model_211 plus-face OFF
__term_sd_task_pre_model_212 plus-face(98.1m) OFF
__term_sd_task_pre_model_213 plus OFF
__term_sd_task_pre_model_214 plus(158m) OFF
__term_sd_task_pre_model_215 normal OFF
__term_sd_task_pre_model_216 normal(44.6m) OFF
__term_sd_task_pre_model_217 =====IP-Adapter(SDXL)模型===== OFF
__term_sd_task_pre_model_218 clip_vision OFF
__term_sd_task_pre_model_219 clip_vision(3.69g) OFF
__term_sd_task_pre_model_220 normal OFF
__term_sd_task_pre_model_221 normal(702.6m) OFF
|
2301_81996401/term-sd
|
install/invokeai/dialog_invokeai_ms_model.sh
|
Shell
|
agpl-3.0
| 11,101
|
__term_sd_task_sys term_sd_mkdir "${INVOKEAI_PARENT_PATH}"
__term_sd_task_sys cd "${INVOKEAI_PARENT_PATH}"
__term_sd_task_sys term_sd_tmp_disable_proxy # 临时取消代理, 避免一些不必要的网络减速
__term_sd_task_sys term_sd_mkdir "${INVOKEAI_FOLDER}"
__term_sd_task_sys is_sd_repo_exist "${INVOKEAI_ROOT_PATH}"
__term_sd_task_pre_core create_venv "${INVOKEAI_ROOT_PATH}"
__term_sd_task_sys enter_venv "${INVOKEAI_ROOT_PATH}"
__term_sd_task_pre_core install_invokeai_process "${PYTORCH_TYPE}" # 安装 PyTorch
__term_sd_task_pre_core install_pypatchmatch_for_windows # 下载 PyPatchMatch
|
2301_81996401/term-sd
|
install/invokeai/invokeai_core.sh
|
Shell
|
agpl-3.0
| 602
|
__term_sd_task_pre_ext_1 git_clone_repository https://github.com/licyk/invoke_tipo "${INVOKEAI_ROOT_PATH}"/invokeai/nodes ON # 为InvokeAI添加TIPO节点，优化提示词
__term_sd_task_pre_ext_2 git_clone_repository https://github.com/licyk/invoke_wd14_tagger "${INVOKEAI_ROOT_PATH}"/invokeai/nodes ON # 添加提示词反推节点
__term_sd_task_pre_ext_3 git_clone_repository https://github.com/skunkworxdark/adapters-linked-nodes "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 将多个节点（ControlNet、IP-Adapter、T2I-Adapter节点）链接在一起
__term_sd_task_pre_ext_4 git_clone_repository https://github.com/JPPhoto/average-images-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 将多张图像合并取平均值输出
__term_sd_task_pre_ext_5 git_clone_repository https://github.com/VeyDlin/clean-artifact-after-cut-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 去除移除背景后残留的伪影
__term_sd_task_pre_ext_6 git_clone_repository https://github.com/VeyDlin/close-color-mask-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 关闭颜色蒙版
__term_sd_task_pre_ext_7 git_clone_repository https://github.com/VeyDlin/clothing-mask-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 为人物服装生成蒙版
__term_sd_task_pre_ext_8 git_clone_repository https://github.com/VeyDlin/clahe-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 提高图像的对比度
__term_sd_task_pre_ext_9 git_clone_repository https://github.com/dwringer/depth-from-obj-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 从3D文件渲染深度图
__term_sd_task_pre_ext_10 git_clone_repository https://github.com/skunkworxdark/enhance-detail-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 增强图片细节
__term_sd_task_pre_ext_11 git_clone_repository https://github.com/JPPhoto/film-grain-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 生成胶片质感图片
__term_sd_task_pre_ext_12 git_clone_repository https://github.com/mickr777/GPT2RandomPromptMaker "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 使用GPT-2生成提示词
__term_sd_task_pre_ext_13 git_clone_repository https://github.com/mildmisery/invokeai-GridToGifNode/blob/main/GridToGif.py "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 将多张图片转换为GIF图片
__term_sd_task_pre_ext_14 git_clone_repository https://github.com/blessedcoolant/invoke_meshgraphormer "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 为手部生成深度图和蒙版
__term_sd_task_pre_ext_15 git_clone_repository https://github.com/JPPhoto/halftone-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 生成半色调图
__term_sd_task_pre_ext_16 git_clone_repository https://github.com/dwringer/composition-nodes "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 蒙版节点包
__term_sd_task_pre_ext_17 git_clone_repository https://github.com/mickr777/imagetoasciiimage "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 将输入图像转换为ascii/unicode艺术图像的节点
__term_sd_task_pre_ext_18 git_clone_repository https://github.com/JPPhoto/image-picker-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 从多张图像随机选择一张图像输出
__term_sd_task_pre_ext_19 git_clone_repository https://github.com/VeyDlin/image-resize-plus-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 调整图片大小
__term_sd_task_pre_ext_20 git_clone_repository https://github.com/gogurtenjoyer/latent-upscale "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 潜空间放大节点
__term_sd_task_pre_ext_21 git_clone_repository https://github.com/helix4u/load_video_frame "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 图片转视频
__term_sd_task_pre_ext_22 git_clone_repository https://github.com/VeyDlin/mask-operations-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 蒙版组合
__term_sd_task_pre_ext_23 git_clone_repository https://github.com/skunkworxdark/metadata-linked-nodes "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 元数据转换节点
__term_sd_task_pre_ext_24 git_clone_repository https://github.com/skunkworxdark/Prompt-tools-nodes "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 提示词工具
__term_sd_task_pre_ext_25 git_clone_repository https://github.com/blessedcoolant/invoke_bria_rmbg "${INVOKEAI_ROOT_PATH}"/invokeai/nodes ON # 背景移除
__term_sd_task_pre_ext_26 git_clone_repository https://github.com/VeyDlin/remove-background-node "${INVOKEAI_ROOT_PATH}"/invokeai/nodes OFF # 背景移除
__term_sd_task_pre_ext_27 git_clone_repository https://github.com/skunkworxdark/XYGrid_nodes "${INVOKEAI_ROOT_PATH}"/invokeai/nodes ON # 添加xyz图工具
|
2301_81996401/term-sd
|
install/invokeai/invokeai_custom_node.sh
|
Shell
|
agpl-3.0
| 4,554
|
__term_sd_task_pre_ext_1 term_sd_echo "下载 invoke_tipo 模型" # invoke_tipo(1.42g) ON
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/z-tipo-extension/TIPO-500M_epoch5-F16.gguf "${INVOKEAI_ROOT_PATH}"/invokeai/models/kgen
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/z-tipo-extension/TIPO-200M-40Btok-F16.gguf "${INVOKEAI_ROOT_PATH}"/invokeai/models/kgen
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/z-tipo-extension/TIPO-200M-ft-F16.gguf "${INVOKEAI_ROOT_PATH}"/invokeai/models/kgen
|
2301_81996401/term-sd
|
install/invokeai/invokeai_custom_node_hf_model.sh
|
Shell
|
agpl-3.0
| 656
|
__term_sd_task_pre_ext_1 term_sd_echo "下载 invoke_tipo 模型" # invoke_tipo(1.42g) ON
__term_sd_task_pre_ext_1 get_modelscope_model licyks/sd-extensions-model/master/z-tipo-extension/TIPO-500M_epoch5-F16.gguf "${INVOKEAI_ROOT_PATH}"/invokeai/models/kgen
__term_sd_task_pre_ext_1 get_modelscope_model licyks/sd-extensions-model/master/z-tipo-extension/TIPO-200M-40Btok-F16.gguf "${INVOKEAI_ROOT_PATH}"/invokeai/models/kgen
__term_sd_task_pre_ext_1 get_modelscope_model licyks/sd-extensions-model/master/z-tipo-extension/TIPO-200M-ft-F16.gguf "${INVOKEAI_ROOT_PATH}"/invokeai/models/kgen
|
2301_81996401/term-sd
|
install/invokeai/invokeai_custom_node_ms_model.sh
|
Shell
|
agpl-3.0
| 590
|
__term_sd_task_pre_model_1 # (提示：) OFF
__term_sd_task_pre_model_2 # (建议使用InvokeAI自带的模型管理下载和添加模型) OFF
__term_sd_task_pre_model_3 # (不推荐使用Term-SD下载InvokeAI的模型) OFF
__term_sd_task_pre_model_4 # =====核心模型===== OFF
__term_sd_task_pre_model_5 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/bert-base-uncased/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/bert-base-uncased # bert-base-uncased OFF
__term_sd_task_pre_model_6 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/bert-base-uncased/tokenizer.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/bert-base-uncased # bert-base-uncased OFF
__term_sd_task_pre_model_7 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/bert-base-uncased/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/bert-base-uncased # bert-base-uncased OFF
__term_sd_task_pre_model_8 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/bert-base-uncased/vocab.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/bert-base-uncased # bert-base-uncased OFF
__term_sd_task_pre_model_9 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k # CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_10 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k # CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_11 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k # CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_12 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k # CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_13 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k # CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_14 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/clip-vit-large-patch14/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14 OFF
__term_sd_task_pre_model_15 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/clip-vit-large-patch14/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14 OFF
__term_sd_task_pre_model_16 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/clip-vit-large-patch14/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14(492.3m) OFF
__term_sd_task_pre_model_17 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/clip-vit-large-patch14/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14 OFF
__term_sd_task_pre_model_18 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/clip-vit-large-patch14/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14 OFF
__term_sd_task_pre_model_19 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/clip-vit-large-patch14/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14 OFF
__term_sd_task_pre_model_20 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/stable-diffusion-2-clip/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/text_encoder # stable-diffusion-2-clip OFF
__term_sd_task_pre_model_21 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/stable-diffusion-2-clip/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/text_encoder # stable-diffusion-2-clip(1.36g) OFF
__term_sd_task_pre_model_22 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/stable-diffusion-2-clip/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/tokenizer # stable-diffusion-2-clip OFF
__term_sd_task_pre_model_23 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/stable-diffusion-2-clip/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/tokenizer # stable-diffusion-2-clip OFF
__term_sd_task_pre_model_24 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/stable-diffusion-2-clip/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/tokenizer # stable-diffusion-2-clip OFF
__term_sd_task_pre_model_25 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/stable-diffusion-2-clip/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/tokenizer # stable-diffusion-2-clip OFF
__term_sd_task_pre_model_26 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/stable-diffusion-safety-checker/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-safety-checker # stable-diffusion-safety-checker OFF
__term_sd_task_pre_model_27 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/stable-diffusion-safety-checker/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-safety-checker # stable-diffusion-safety-checker(1.22g) OFF
__term_sd_task_pre_model_28 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/stable-diffusion-safety-checker/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-safety-checker # stable-diffusion-safety-checker OFF
__term_sd_task_pre_model_29 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/misc/lama/lama.pt "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/misc/lama # lama(205.6m) OFF
__term_sd_task_pre_model_30 # =====放大模型===== OFF
__term_sd_task_pre_model_31 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/upscaling/realesrgan/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/upscaling/realesrgan # ESRGAN_SRx4_DF2KOST_official-ff704c30(66.9m) OFF
__term_sd_task_pre_model_32 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/upscaling/realesrgan/RealESRGAN_x2plus.pth "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/upscaling/realesrgan # RealESRGAN_x2plus(67m) OFF
__term_sd_task_pre_model_33 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/upscaling/realesrgan/RealESRGAN_x4plus.pth "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/upscaling/realesrgan # RealESRGAN_x4plus(67m) OFF
__term_sd_task_pre_model_34 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/upscaling/realesrgan/RealESRGAN_x4plus_anime_6B.pth "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/upscaling/realesrgan # RealESRGAN_x4plus_anime_6B(17.9m) OFF
__term_sd_task_pre_model_35 # =====配置文件===== OFF
__term_sd_task_pre_model_36 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/INITIAL_MODELS.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs # INITIAL_MODELS OFF
__term_sd_task_pre_model_37 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/models.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs # models.yaml OFF
__term_sd_task_pre_model_38 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/models.yaml.example "${INVOKEAI_ROOT_PATH}"/invokeai/configs # models.yaml.example OFF
__term_sd_task_pre_model_39 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/sd_xl_base.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # sd_xl_base.yaml OFF
__term_sd_task_pre_model_40 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/sd_xl_refiner.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # sd_xl_refiner.yaml OFF
__term_sd_task_pre_model_41 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/v1-finetune.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-finetune.yaml OFF
__term_sd_task_pre_model_42 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/v1-finetune_style.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-finetune_style.yaml OFF
__term_sd_task_pre_model_43 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/v1-inference-v.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-inference-v.yaml OFF
__term_sd_task_pre_model_44 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/v1-inference.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-inference.yaml OFF
__term_sd_task_pre_model_45 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/v1-inpainting-inference.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-inpainting-inference.yaml OFF
__term_sd_task_pre_model_46 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/v1-m1-finetune.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-m1-finetune.yaml OFF
__term_sd_task_pre_model_47 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/v2-inference-v.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v2-inference-v.yaml OFF
__term_sd_task_pre_model_48 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/v2-inference.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v2-inference.yaml OFF
__term_sd_task_pre_model_49 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/v2-inpainting-inference-v.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v2-inpainting-inference-v.yaml OFF
__term_sd_task_pre_model_50 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/configs/stable-diffusion/v2-inpainting-inference.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v2-inpainting-inference.yaml OFF
__term_sd_task_pre_model_51 # =====基础模型===== OFF
__term_sd_task_pre_model_52 # =====SD1.5大模型===== OFF
__term_sd_task_pre_model_53 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/feature_extractor/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/feature_extractor # sd1.5-official OFF
__term_sd_task_pre_model_54 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5 # sd1.5-official OFF
__term_sd_task_pre_model_55 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/scheduler # sd1.5-official OFF
__term_sd_task_pre_model_56 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/text_encoder # sd1.5-official OFF
__term_sd_task_pre_model_57 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/text_encoder # sd1.5-official(246.1m) OFF
__term_sd_task_pre_model_58 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/tokenizer # sd1.5-official OFF
__term_sd_task_pre_model_59 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/tokenizer # sd1.5-official OFF
__term_sd_task_pre_model_60 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/tokenizer # sd1.5-official OFF
__term_sd_task_pre_model_61 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/tokenizer # sd1.5-official OFF
__term_sd_task_pre_model_62 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/unet # sd1.5-official OFF
__term_sd_task_pre_model_63 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/unet # sd1.5-official(1.72g) OFF
__term_sd_task_pre_model_64 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/vae # sd1.5-official OFF
__term_sd_task_pre_model_65 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/vae # sd1.5-official(167.3m) OFF
__term_sd_task_pre_model_66 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/feature_extractor/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/feature_extractor # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_67 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_68 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/scheduler # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_69 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/text_encoder # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_70 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/text_encoder # sd1.5-inpaint-official(246.1m) OFF
__term_sd_task_pre_model_71 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_72 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_73 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_74 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_75 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/unet # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_76 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/unet # sd1.5-inpaint-official(1.72g) OFF
__term_sd_task_pre_model_77 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/vae # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_78 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/stable-diffusion-v1-5-inpainting/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/vae # sd1.5-inpaint-official(167.3m) OFF
__term_sd_task_pre_model_79 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/feature_extractor/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/feature_extractor # openjourney OFF
__term_sd_task_pre_model_80 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney # openjourney OFF
__term_sd_task_pre_model_81 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/scheduler # openjourney OFF
__term_sd_task_pre_model_82 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/text_encoder # openjourney OFF
__term_sd_task_pre_model_83 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/text_encoder # openjourney(246.1m) OFF
__term_sd_task_pre_model_84 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/tokenizer # openjourney OFF
__term_sd_task_pre_model_85 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/tokenizer # openjourney OFF
__term_sd_task_pre_model_86 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/tokenizer # openjourney OFF
__term_sd_task_pre_model_87 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/tokenizer # openjourney OFF
__term_sd_task_pre_model_88 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/unet # openjourney OFF
__term_sd_task_pre_model_89 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/unet # openjourney(1.72g) OFF
__term_sd_task_pre_model_90 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/vae # openjourney OFF
__term_sd_task_pre_model_91 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/main/openjourney/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/vae # openjourney(246.1m) OFF
__term_sd_task_pre_model_92 # =====SD2.1大模型===== OFF
__term_sd_task_pre_model_93 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/feature_extractor/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/feature_extractor # sd2.1-official OFF
__term_sd_task_pre_model_94 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1 # sd2.1-official OFF
__term_sd_task_pre_model_95 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/scheduler # sd2.1-official OFF
__term_sd_task_pre_model_96 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/text_encoder # sd2.1-official OFF
__term_sd_task_pre_model_97 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/text_encoder # sd2.1-official(680.8m) OFF
__term_sd_task_pre_model_98 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/tokenizer # sd2.1-official OFF
__term_sd_task_pre_model_99 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/tokenizer # sd2.1-official OFF
__term_sd_task_pre_model_100 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/tokenizer # sd2.1-official OFF
__term_sd_task_pre_model_101 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/tokenizer # sd2.1-official OFF
__term_sd_task_pre_model_102 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/unet # sd2.1-official OFF
__term_sd_task_pre_model_103 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/unet # sd2.1-official(1.73g) OFF
__term_sd_task_pre_model_104 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/vae # sd2.1-official OFF
__term_sd_task_pre_model_105 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-1/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/vae # sd2.1-official(167.3m) OFF
__term_sd_task_pre_model_106 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/feature_extractor/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/feature_extractor # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_107 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_108 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/scheduler # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_109 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/text_encoder # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_110 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/text_encoder # sd2.1-inpaint-official(680.8m) OFF
__term_sd_task_pre_model_111 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/tokenizer # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_112 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/tokenizer # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_113 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/tokenizer # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_114 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/tokenizer # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_115 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/unet # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_116 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/unet # sd2.1-inpaint-official(1.73g) OFF
__term_sd_task_pre_model_117 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/vae # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_118 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/main/stable-diffusion-2-inpainting/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/vae # sd2.1-inpaint-official(167.3m) OFF
__term_sd_task_pre_model_119 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_120 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0 # sdxl OFF
__term_sd_task_pre_model_121 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/scheduler # sdxl OFF
__term_sd_task_pre_model_122 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder # sdxl OFF
__term_sd_task_pre_model_123 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder # sdxl(246.1m) OFF
__term_sd_task_pre_model_124 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder_2/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder_2 # sdxl OFF
__term_sd_task_pre_model_125 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder_2/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder_2 # sdxl(1.39g) OFF
__term_sd_task_pre_model_126 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer # sdxl OFF
__term_sd_task_pre_model_127 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer # sdxl OFF
__term_sd_task_pre_model_128 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer # sdxl OFF
__term_sd_task_pre_model_129 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer # sdxl OFF
__term_sd_task_pre_model_130 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2 # sdxl OFF
__term_sd_task_pre_model_131 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2 # sdxl OFF
__term_sd_task_pre_model_132 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2 # sdxl OFF
__term_sd_task_pre_model_133 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2 # sdxl OFF
__term_sd_task_pre_model_134 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/unet # sdxl OFF
__term_sd_task_pre_model_135 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/unet # sdxl(5.14g) OFF
__term_sd_task_pre_model_136 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/vae # sdxl OFF
__term_sd_task_pre_model_137 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/main/stable-diffusion-xl-base-1-0/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/vae # sdxl(167.3m) OFF
__term_sd_task_pre_model_138 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0 # sdxl-refind OFF
__term_sd_task_pre_model_139 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/scheduler # sdxl-refind OFF
__term_sd_task_pre_model_140 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/text_encoder_2/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/text_encoder_2 # sdxl-refind OFF
__term_sd_task_pre_model_141 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/text_encoder_2/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/text_encoder_2 # sdxl-refind(1.39g) OFF
__term_sd_task_pre_model_142 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2 # sdxl-refind OFF
__term_sd_task_pre_model_143 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2 # sdxl-refind OFF
__term_sd_task_pre_model_144 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2 # sdxl-refind OFF
__term_sd_task_pre_model_145 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2 # sdxl-refind OFF
__term_sd_task_pre_model_146 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/unet # sdxl-refind OFF
__term_sd_task_pre_model_147 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/unet # sdxl-refind(5.14g) OFF
__term_sd_task_pre_model_148 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/vae # sdxl-refind OFF
__term_sd_task_pre_model_149 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/vae # sdxl-refind(167.3m) OFF
__term_sd_task_pre_model_150 # =====VAE模型===== OFF
__term_sd_task_pre_model_151 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/sd-vae-ft-mse/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/sd-vae-ft-mse # sd-vae-ft-mse OFF
__term_sd_task_pre_model_152 aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/models/core/convert/sd-vae-ft-mse/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/sd-vae-ft-mse # sd-vae-ft-mse(334.6m) OFF
__term_sd_task_pre_model_153 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/vae/sdxl-1-0-vae-fix/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/vae/sdxl-1-0-vae-fix # sdxl-vae OFF
__term_sd_task_pre_model_154 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/vae/sdxl-1-0-vae-fix/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/vae/sdxl-1-0-vae-fix # sdxl-vae(334.6m) OFF
__term_sd_task_pre_model_155 # =====Embedding模型===== OFF
__term_sd_task_pre_model_156 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/embedding/EasyNegative.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/embedding # EasyNegative(0.1m) OFF
__term_sd_task_pre_model_157 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-2/embedding/ahx-beta-453407d/learned_embeds.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/embedding # ahx-beta-453407d(0.1m) OFF
__term_sd_task_pre_model_158 # =====控制模型===== OFF
__term_sd_task_pre_model_159 # =====ControlNet(SD1.5)模型===== OFF
__term_sd_task_pre_model_160 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/canny/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/canny # canny OFF
__term_sd_task_pre_model_161 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/canny/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/canny # canny(1.45g) OFF
__term_sd_task_pre_model_162 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/depth/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/depth # depth OFF
__term_sd_task_pre_model_163 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/depth/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/depth # depth(1.45g) OFF
__term_sd_task_pre_model_164 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/inpaint/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/inpaint # inpaint OFF
__term_sd_task_pre_model_165 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/inpaint/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/inpaint # inpaint(1.45g) OFF
__term_sd_task_pre_model_166 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/ip2p/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/ip2p # ip2p OFF
__term_sd_task_pre_model_167 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/ip2p/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/ip2p # ip2p(1.45g) OFF
__term_sd_task_pre_model_168 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/lineart/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/lineart # lineart OFF
__term_sd_task_pre_model_169 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/lineart/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/lineart # lineart(1.45g) OFF
__term_sd_task_pre_model_170 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/lineart_anime/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/lineart_anime # lineart-anime OFF
__term_sd_task_pre_model_171 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/lineart_anime/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/lineart_anime # lineart-anime(1.45g) OFF
__term_sd_task_pre_model_172 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/mlsd/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/mlsd # mlsd OFF
__term_sd_task_pre_model_173 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/mlsd/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/mlsd # mlsd(1.45g) OFF
__term_sd_task_pre_model_174 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/normal_bae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/normal_bae # normal-bae OFF
__term_sd_task_pre_model_175 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/normal_bae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/normal_bae # normal-bae(1.45g) OFF
__term_sd_task_pre_model_176 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/openpose/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/openpose # openpose OFF
__term_sd_task_pre_model_177 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/openpose/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/openpose # openpose(1.45g) OFF
__term_sd_task_pre_model_178 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/qrcode_monster/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/qrcode_monster # qrcode OFF
__term_sd_task_pre_model_179 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/qrcode_monster/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/qrcode_monster # qrcode(1.45g) OFF
__term_sd_task_pre_model_180 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/scribble/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/scribble # scribble OFF
__term_sd_task_pre_model_181 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/scribble/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/scribble # scribble(1.45g) OFF
__term_sd_task_pre_model_182 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/seg/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/seg # seg OFF
__term_sd_task_pre_model_183 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/seg/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/seg # seg(1.45g) OFF
__term_sd_task_pre_model_184 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/shuffle/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/shuffle # shuffle OFF
__term_sd_task_pre_model_185 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/shuffle/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/shuffle # shuffle(1.45g) OFF
__term_sd_task_pre_model_186 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/softedge/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/softedge # softedge OFF
__term_sd_task_pre_model_187 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/softedge/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/softedge # softedge(1.45g) OFF
__term_sd_task_pre_model_188 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/tile/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/tile # tile OFF
__term_sd_task_pre_model_189 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/controlnet/tile/diffusion_pytorch_model.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/tile # tile(1.45g) OFF
__term_sd_task_pre_model_190 # =====T2I-Adapter(SD1.5)模型===== OFF
__term_sd_task_pre_model_191 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/t2i_adapter/canny-sd15/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/canny-sd15 # canny OFF
__term_sd_task_pre_model_192 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/t2i_adapter/canny-sd15/diffusion_pytorch_model.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/canny-sd15 # canny(308m) OFF
__term_sd_task_pre_model_193 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/t2i_adapter/depth-sd15/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/depth-sd15 # depth OFF
__term_sd_task_pre_model_194 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/t2i_adapter/depth-sd15/diffusion_pytorch_model.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/depth-sd15 # depth(308m) OFF
__term_sd_task_pre_model_195 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/t2i_adapter/sketch-sd15/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/sketch-sd15 # sketch OFF
__term_sd_task_pre_model_196 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/t2i_adapter/sketch-sd15/diffusion_pytorch_model.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/sketch-sd15 # sketch(308m) OFF
__term_sd_task_pre_model_197 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/t2i_adapter/zoedepth-sd15/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/zoedepth-sd15 # zoedepth OFF
__term_sd_task_pre_model_198 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/t2i_adapter/zoedepth-sd15/diffusion_pytorch_model.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/zoedepth-sd15 # zoedepth(308m) OFF
__term_sd_task_pre_model_199 # =====T2I-Adapter(SDXL)模型===== OFF
__term_sd_task_pre_model_200 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/t2i_adapter/canny-sdxl/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/canny-sdxl # canny OFF
__term_sd_task_pre_model_201 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/t2i_adapter/canny-sdxl/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/canny-sdxl # canny(316m) OFF
__term_sd_task_pre_model_202 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/t2i_adapter/lineart-sdxl/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/lineart-sdxl # lineart OFF
__term_sd_task_pre_model_203 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/t2i_adapter/lineart-sdxl/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/lineart-sdxl # lineart(316m) OFF
__term_sd_task_pre_model_204 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/t2i_adapter/sketch-sdxl/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/sketch-sdxl # sketch OFF
__term_sd_task_pre_model_205 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/t2i_adapter/sketch-sdxl/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/sketch-sdxl # sketch(316m) OFF
__term_sd_task_pre_model_206 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/t2i_adapter/zoedepth-sdxl/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/zoedepth-sdxl # zoedepth OFF
__term_sd_task_pre_model_207 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/t2i_adapter/zoedepth-sdxl/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/zoedepth-sdxl # zoedepth(316m) OFF
__term_sd_task_pre_model_208 # =====IP-Adapter(SD1.5)模型===== OFF
__term_sd_task_pre_model_209 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/any/clip_vision/ip_adapter_sd_image_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/any/clip_vision/ip_adapter_sd_image_encoder # clip_vision OFF
__term_sd_task_pre_model_210 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/any/clip_vision/ip_adapter_sd_image_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/any/clip_vision/ip_adapter_sd_image_encoder # clip_vision(2.53g) OFF
__term_sd_task_pre_model_211 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/ip_adapter/ip_adapter_plus_face_sd15/image_encoder.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_plus_face_sd15 # plus-face OFF
__term_sd_task_pre_model_212 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/ip_adapter/ip_adapter_plus_face_sd15/ip_adapter.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_plus_face_sd15 # plus-face(98.1m) OFF
__term_sd_task_pre_model_213 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/ip_adapter/ip_adapter_plus_sd15/image_encoder.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_plus_sd15 # plus OFF
__term_sd_task_pre_model_214 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/ip_adapter/ip_adapter_plus_sd15/ip_adapter.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_plus_sd15 # plus(158m) OFF
__term_sd_task_pre_model_215 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/ip_adapter/ip_adapter_sd15/image_encoder.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_sd15 # normal OFF
__term_sd_task_pre_model_216 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sd-1/ip_adapter/ip_adapter_sd15/ip_adapter.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_sd15 # normal(44.6m) OFF
__term_sd_task_pre_model_217 # =====IP-Adapter(SDXL)模型===== OFF
__term_sd_task_pre_model_218 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/any/clip_vision/ip_adapter_sdxl_image_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/any/clip_vision/ip_adapter_sdxl_image_encoder # clip_vision OFF
__term_sd_task_pre_model_219 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/any/clip_vision/ip_adapter_sdxl_image_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/any/clip_vision/ip_adapter_sdxl_image_encoder # clip_vision(3.69g) OFF
__term_sd_task_pre_model_220 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/ip_adapter/ip_adapter_sdxl/image_encoder.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/ip_adapter/ip_adapter_sdxl # normal OFF
__term_sd_task_pre_model_221 aria2_download https://huggingface.co/licyk/invokeai-model/resolve/main/sdxl/ip_adapter/ip_adapter_sdxl/ip_adapter.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/ip_adapter/ip_adapter_sdxl # normal(702.6m) OFF
|
2301_81996401/term-sd
|
install/invokeai/invokeai_hf_model.sh
|
Shell
|
agpl-3.0
| 53,855
|
__term_sd_task_pre_model_1 # (提示：) OFF
__term_sd_task_pre_model_2 # (建议使用InvokeAI自带的模型管理下载和添加模型) OFF
__term_sd_task_pre_model_3 # (不推荐使用Term-SD下载InvokeAI的模型) OFF
__term_sd_task_pre_model_4 # =====核心模型===== OFF
__term_sd_task_pre_model_5 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/bert-base-uncased/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/bert-base-uncased # bert-base-uncased OFF
__term_sd_task_pre_model_6 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/bert-base-uncased/tokenizer.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/bert-base-uncased # bert-base-uncased OFF
__term_sd_task_pre_model_7 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/bert-base-uncased/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/bert-base-uncased # bert-base-uncased OFF
__term_sd_task_pre_model_8 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/bert-base-uncased/vocab.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/bert-base-uncased # bert-base-uncased OFF
__term_sd_task_pre_model_9 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k # CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_10 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k # CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_11 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k # CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_12 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k # CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_13 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/CLIP-ViT-bigG-14-laion2B-39B-b160k # CLIP-ViT-bigG-14-laion2B-39B-b160k OFF
__term_sd_task_pre_model_14 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/clip-vit-large-patch14/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14 OFF
__term_sd_task_pre_model_15 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/clip-vit-large-patch14/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14 OFF
__term_sd_task_pre_model_16 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/clip-vit-large-patch14/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14(492.3m) OFF
__term_sd_task_pre_model_17 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/clip-vit-large-patch14/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14 OFF
__term_sd_task_pre_model_18 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/clip-vit-large-patch14/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14 OFF
__term_sd_task_pre_model_19 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/clip-vit-large-patch14/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/clip-vit-large-patch14 # clip-vit-large-patch14 OFF
__term_sd_task_pre_model_20 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/stable-diffusion-2-clip/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/text_encoder # stable-diffusion-2-clip OFF
__term_sd_task_pre_model_21 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/stable-diffusion-2-clip/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/text_encoder # stable-diffusion-2-clip(1.36g) OFF
__term_sd_task_pre_model_22 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/stable-diffusion-2-clip/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/tokenizer # stable-diffusion-2-clip OFF
__term_sd_task_pre_model_23 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/stable-diffusion-2-clip/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/tokenizer # stable-diffusion-2-clip OFF
__term_sd_task_pre_model_24 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/stable-diffusion-2-clip/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/tokenizer # stable-diffusion-2-clip OFF
__term_sd_task_pre_model_25 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/stable-diffusion-2-clip/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-2-clip/tokenizer # stable-diffusion-2-clip OFF
__term_sd_task_pre_model_26 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/stable-diffusion-safety-checker/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-safety-checker # stable-diffusion-safety-checker OFF
__term_sd_task_pre_model_27 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/stable-diffusion-safety-checker/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-safety-checker # stable-diffusion-safety-checker(1.22g) OFF
__term_sd_task_pre_model_28 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/stable-diffusion-safety-checker/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/stable-diffusion-safety-checker # stable-diffusion-safety-checker OFF
__term_sd_task_pre_model_29 get_modelscope_model licyks/invokeai-core-model/master/models/core/misc/lama/lama.pt "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/misc/lama # lama(205.6m) OFF
__term_sd_task_pre_model_30 # =====放大模型===== OFF
__term_sd_task_pre_model_31 get_modelscope_model licyks/invokeai-core-model/master/models/core/upscaling/realesrgan/ESRGAN_SRx4_DF2KOST_official-ff704c30.pth "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/upscaling/realesrgan # ESRGAN_SRx4_DF2KOST_official-ff704c30(66.9m) OFF
__term_sd_task_pre_model_32 get_modelscope_model licyks/invokeai-core-model/master/models/core/upscaling/realesrgan/RealESRGAN_x2plus.pth "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/upscaling/realesrgan # RealESRGAN_x2plus(67m) OFF
__term_sd_task_pre_model_33 get_modelscope_model licyks/invokeai-core-model/master/models/core/upscaling/realesrgan/RealESRGAN_x4plus.pth "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/upscaling/realesrgan # RealESRGAN_x4plus(67m) OFF
__term_sd_task_pre_model_34 get_modelscope_model licyks/invokeai-core-model/master/models/core/upscaling/realesrgan/RealESRGAN_x4plus_anime_6B.pth "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/upscaling/realesrgan # RealESRGAN_x4plus_anime_6B(17.9m) OFF
__term_sd_task_pre_model_35 # =====配置文件===== OFF
__term_sd_task_pre_model_36 get_modelscope_model licyks/invokeai-core-model/master/configs/INITIAL_MODELS.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs # INITIAL_MODELS OFF
__term_sd_task_pre_model_37 get_modelscope_model licyks/invokeai-core-model/master/configs/models.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs # models.yaml OFF
__term_sd_task_pre_model_38 get_modelscope_model licyks/invokeai-core-model/master/configs/models.yaml.example "${INVOKEAI_ROOT_PATH}"/invokeai/configs # models.yaml.example OFF
__term_sd_task_pre_model_39 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/sd_xl_base.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # sd_xl_base.yaml OFF
__term_sd_task_pre_model_40 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/sd_xl_refiner.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # sd_xl_refiner.yaml OFF
__term_sd_task_pre_model_41 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/v1-finetune.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-finetune.yaml OFF
__term_sd_task_pre_model_42 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/v1-finetune_style.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-finetune_style.yaml OFF
__term_sd_task_pre_model_43 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/v1-inference-v.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-inference-v.yaml OFF
__term_sd_task_pre_model_44 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/v1-inference.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-inference.yaml OFF
__term_sd_task_pre_model_45 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/v1-inpainting-inference.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-inpainting-inference.yaml OFF
__term_sd_task_pre_model_46 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/v1-m1-finetune.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v1-m1-finetune.yaml OFF
__term_sd_task_pre_model_47 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/v2-inference-v.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v2-inference-v.yaml OFF
__term_sd_task_pre_model_48 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/v2-inference.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v2-inference.yaml OFF
__term_sd_task_pre_model_49 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/v2-inpainting-inference-v.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v2-inpainting-inference-v.yaml OFF
__term_sd_task_pre_model_50 get_modelscope_model licyks/invokeai-core-model/master/configs/stable-diffusion/v2-inpainting-inference.yaml "${INVOKEAI_ROOT_PATH}"/invokeai/configs/stable-diffusion # v2-inpainting-inference.yaml OFF
__term_sd_task_pre_model_51 # =====基础模型===== OFF
__term_sd_task_pre_model_52 # =====SD1.5大模型===== OFF
__term_sd_task_pre_model_53 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/feature_extractor/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/feature_extractor # sd1.5-official OFF
__term_sd_task_pre_model_54 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5 # sd1.5-official OFF
__term_sd_task_pre_model_55 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/scheduler # sd1.5-official OFF
__term_sd_task_pre_model_56 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/text_encoder # sd1.5-official OFF
__term_sd_task_pre_model_57 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/text_encoder # sd1.5-official(246.1m) OFF
__term_sd_task_pre_model_58 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/tokenizer # sd1.5-official OFF
__term_sd_task_pre_model_59 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/tokenizer # sd1.5-official OFF
__term_sd_task_pre_model_60 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/tokenizer # sd1.5-official OFF
__term_sd_task_pre_model_61 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/tokenizer # sd1.5-official OFF
__term_sd_task_pre_model_62 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/unet # sd1.5-official OFF
__term_sd_task_pre_model_63 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/unet # sd1.5-official(1.72g) OFF
__term_sd_task_pre_model_64 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/vae # sd1.5-official OFF
__term_sd_task_pre_model_65 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5/vae # sd1.5-official(167.3m) OFF
__term_sd_task_pre_model_66 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/feature_extractor/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/feature_extractor # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_67 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_68 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/scheduler # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_69 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/text_encoder # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_70 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/text_encoder # sd1.5-inpaint-official(246.1m) OFF
__term_sd_task_pre_model_71 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_72 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_73 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_74 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/tokenizer # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_75 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/unet # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_76 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/unet # sd1.5-inpaint-official(1.72g) OFF
__term_sd_task_pre_model_77 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/vae # sd1.5-inpaint-official OFF
__term_sd_task_pre_model_78 get_modelscope_model licyks/invokeai-model/master/sd-1/main/stable-diffusion-v1-5-inpainting/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/stable-diffusion-v1-5-inpainting/vae # sd1.5-inpaint-official(167.3m) OFF
__term_sd_task_pre_model_79 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/feature_extractor/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/feature_extractor # openjourney OFF
__term_sd_task_pre_model_80 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney # openjourney OFF
__term_sd_task_pre_model_81 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/scheduler # openjourney OFF
__term_sd_task_pre_model_82 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/text_encoder # openjourney OFF
__term_sd_task_pre_model_83 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/text_encoder # openjourney(246.1m) OFF
__term_sd_task_pre_model_84 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/tokenizer # openjourney OFF
__term_sd_task_pre_model_85 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/tokenizer # openjourney OFF
__term_sd_task_pre_model_86 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/tokenizer # openjourney OFF
__term_sd_task_pre_model_87 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/tokenizer # openjourney OFF
__term_sd_task_pre_model_88 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/unet # openjourney OFF
__term_sd_task_pre_model_89 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/unet # openjourney(1.72g) OFF
__term_sd_task_pre_model_90 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/vae # openjourney OFF
__term_sd_task_pre_model_91 get_modelscope_model licyks/invokeai-model/master/sd-1/main/openjourney/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/main/openjourney/vae # openjourney(246.1m) OFF
__term_sd_task_pre_model_92 # =====SD2.1大模型===== OFF
__term_sd_task_pre_model_93 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/feature_extractor/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/feature_extractor # sd2.1-official OFF
__term_sd_task_pre_model_94 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1 # sd2.1-official OFF
__term_sd_task_pre_model_95 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/scheduler # sd2.1-official OFF
__term_sd_task_pre_model_96 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/text_encoder # sd2.1-official OFF
__term_sd_task_pre_model_97 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/text_encoder # sd2.1-official(680.8m) OFF
__term_sd_task_pre_model_98 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/tokenizer # sd2.1-official OFF
__term_sd_task_pre_model_99 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/tokenizer # sd2.1-official OFF
__term_sd_task_pre_model_100 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/tokenizer # sd2.1-official OFF
__term_sd_task_pre_model_101 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/tokenizer # sd2.1-official OFF
__term_sd_task_pre_model_102 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/unet # sd2.1-official OFF
__term_sd_task_pre_model_103 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/unet # sd2.1-official(1.73g) OFF
__term_sd_task_pre_model_104 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/vae # sd2.1-official OFF
__term_sd_task_pre_model_105 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-1/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-1/vae # sd2.1-official(167.3m) OFF
__term_sd_task_pre_model_106 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/feature_extractor/preprocessor_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/feature_extractor # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_107 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_108 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/scheduler # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_109 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/text_encoder # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_110 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/text_encoder # sd2.1-inpaint-official(680.8m) OFF
__term_sd_task_pre_model_111 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/tokenizer # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_112 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/tokenizer # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_113 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/tokenizer # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_114 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/tokenizer # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_115 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/unet # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_116 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/unet # sd2.1-inpaint-official(1.73g) OFF
__term_sd_task_pre_model_117 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/vae # sd2.1-inpaint-official OFF
__term_sd_task_pre_model_118 get_modelscope_model licyks/invokeai-model/master/sd-2/main/stable-diffusion-2-inpainting/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/main/stable-diffusion-2-inpainting/vae # sd2.1-inpaint-official(167.3m) OFF
__term_sd_task_pre_model_119 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_120 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0 # sdxl OFF
__term_sd_task_pre_model_121 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/scheduler # sdxl OFF
__term_sd_task_pre_model_122 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder # sdxl OFF
__term_sd_task_pre_model_123 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder # sdxl(246.1m) OFF
__term_sd_task_pre_model_124 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder_2/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder_2 # sdxl OFF
__term_sd_task_pre_model_125 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder_2/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/text_encoder_2 # sdxl(1.39g) OFF
__term_sd_task_pre_model_126 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer # sdxl OFF
__term_sd_task_pre_model_127 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer # sdxl OFF
__term_sd_task_pre_model_128 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer # sdxl OFF
__term_sd_task_pre_model_129 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer # sdxl OFF
__term_sd_task_pre_model_130 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2 # sdxl OFF
__term_sd_task_pre_model_131 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2 # sdxl OFF
__term_sd_task_pre_model_132 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2 # sdxl OFF
__term_sd_task_pre_model_133 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/tokenizer_2 # sdxl OFF
__term_sd_task_pre_model_134 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/unet # sdxl OFF
__term_sd_task_pre_model_135 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/unet # sdxl(5.14g) OFF
__term_sd_task_pre_model_136 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/vae # sdxl OFF
__term_sd_task_pre_model_137 get_modelscope_model licyks/invokeai-model/master/sdxl/main/stable-diffusion-xl-base-1-0/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/main/stable-diffusion-xl-base-1-0/vae # sdxl(167.3m) OFF
__term_sd_task_pre_model_138 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/model_index.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0 # sdxl-refind OFF
__term_sd_task_pre_model_139 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/scheduler/scheduler_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/scheduler # sdxl-refind OFF
__term_sd_task_pre_model_140 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/text_encoder_2/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/text_encoder_2 # sdxl-refind OFF
__term_sd_task_pre_model_141 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/text_encoder_2/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/text_encoder_2 # sdxl-refind(1.39g) OFF
__term_sd_task_pre_model_142 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2/merges.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2 # sdxl-refind OFF
__term_sd_task_pre_model_143 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2/special_tokens_map.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2 # sdxl-refind OFF
__term_sd_task_pre_model_144 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2/tokenizer_config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2 # sdxl-refind OFF
__term_sd_task_pre_model_145 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2/vocab.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/tokenizer_2 # sdxl-refind OFF
__term_sd_task_pre_model_146 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/unet/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/unet # sdxl-refind OFF
__term_sd_task_pre_model_147 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/unet/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/unet # sdxl-refind(5.14g) OFF
__term_sd_task_pre_model_148 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/vae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/vae # sdxl-refind OFF
__term_sd_task_pre_model_149 get_modelscope_model licyks/invokeai-model/master/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/vae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl-refiner/main/stable-diffusion-xl-refiner-1-0/vae # sdxl-refind(167.3m) OFF
__term_sd_task_pre_model_150 # =====VAE模型===== OFF
__term_sd_task_pre_model_151 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/sd-vae-ft-mse/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/sd-vae-ft-mse # sd-vae-ft-mse OFF
__term_sd_task_pre_model_152 get_modelscope_model licyks/invokeai-core-model/master/models/core/convert/sd-vae-ft-mse/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/core/convert/sd-vae-ft-mse # sd-vae-ft-mse(334.6m) OFF
__term_sd_task_pre_model_153 get_modelscope_model licyks/invokeai-model/master/sdxl/vae/sdxl-1-0-vae-fix/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/vae/sdxl-1-0-vae-fix # sdxl-vae OFF
__term_sd_task_pre_model_154 get_modelscope_model licyks/invokeai-model/master/sdxl/vae/sdxl-1-0-vae-fix/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/vae/sdxl-1-0-vae-fix # sdxl-vae(334.6m) OFF
__term_sd_task_pre_model_155 # =====Embedding模型===== OFF
__term_sd_task_pre_model_156 get_modelscope_model licyks/invokeai-model/master/sd-1/embedding/EasyNegative.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/embedding # EasyNegative(0.1m) OFF
__term_sd_task_pre_model_157 get_modelscope_model licyks/invokeai-model/master/sd-2/embedding/ahx-beta-453407d/learned_embeds.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-2/embedding # ahx-beta-453407d(0.1m) OFF
__term_sd_task_pre_model_158 # =====控制模型===== OFF
__term_sd_task_pre_model_159 # =====ControlNet(SD1.5)模型===== OFF
__term_sd_task_pre_model_160 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/canny/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/canny # canny OFF
__term_sd_task_pre_model_161 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/canny/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/canny # canny(1.45g) OFF
__term_sd_task_pre_model_162 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/depth/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/depth # depth OFF
__term_sd_task_pre_model_163 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/depth/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/depth # depth(1.45g) OFF
__term_sd_task_pre_model_164 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/inpaint/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/inpaint # inpaint OFF
__term_sd_task_pre_model_165 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/inpaint/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/inpaint # inpaint(1.45g) OFF
__term_sd_task_pre_model_166 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/ip2p/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/ip2p # ip2p OFF
__term_sd_task_pre_model_167 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/ip2p/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/ip2p # ip2p(1.45g) OFF
__term_sd_task_pre_model_168 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/lineart/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/lineart # lineart OFF
__term_sd_task_pre_model_169 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/lineart/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/lineart # lineart(1.45g) OFF
__term_sd_task_pre_model_170 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/lineart_anime/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/lineart_anime # lineart-anime OFF
__term_sd_task_pre_model_171 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/lineart_anime/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/lineart_anime # lineart-anime(1.45g) OFF
__term_sd_task_pre_model_172 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/mlsd/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/mlsd # mlsd OFF
__term_sd_task_pre_model_173 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/mlsd/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/mlsd # mlsd(1.45g) OFF
__term_sd_task_pre_model_174 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/normal_bae/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/normal_bae # normal-bae OFF
__term_sd_task_pre_model_175 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/normal_bae/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/normal_bae # normal-bae(1.45g) OFF
__term_sd_task_pre_model_176 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/openpose/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/openpose # openpose OFF
__term_sd_task_pre_model_177 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/openpose/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/openpose # openpose(1.45g) OFF
__term_sd_task_pre_model_178 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/qrcode_monster/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/qrcode_monster # qrcode OFF
__term_sd_task_pre_model_179 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/qrcode_monster/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/qrcode_monster # qrcode(1.45g) OFF
__term_sd_task_pre_model_180 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/scribble/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/scribble # scribble OFF
__term_sd_task_pre_model_181 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/scribble/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/scribble # scribble(1.45g) OFF
__term_sd_task_pre_model_182 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/seg/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/seg # seg OFF
__term_sd_task_pre_model_183 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/seg/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/seg # seg(1.45g) OFF
__term_sd_task_pre_model_184 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/shuffle/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/shuffle # shuffle OFF
__term_sd_task_pre_model_185 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/shuffle/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/shuffle # shuffle(1.45g) OFF
__term_sd_task_pre_model_186 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/softedge/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/softedge # softedge OFF
__term_sd_task_pre_model_187 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/softedge/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/softedge # softedge(1.45g) OFF
__term_sd_task_pre_model_188 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/tile/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/tile # tile OFF
__term_sd_task_pre_model_189 get_modelscope_model licyks/invokeai-model/master/sd-1/controlnet/tile/diffusion_pytorch_model.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/controlnet/tile # tile(1.45g) OFF
__term_sd_task_pre_model_190 # =====T2I-Adapter(SD1.5)模型===== OFF
__term_sd_task_pre_model_191 get_modelscope_model licyks/invokeai-model/master/sd-1/t2i_adapter/canny-sd15/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/canny-sd15 # canny OFF
__term_sd_task_pre_model_192 get_modelscope_model licyks/invokeai-model/master/sd-1/t2i_adapter/canny-sd15/diffusion_pytorch_model.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/canny-sd15 # canny(308m) OFF
__term_sd_task_pre_model_193 get_modelscope_model licyks/invokeai-model/master/sd-1/t2i_adapter/depth-sd15/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/depth-sd15 # depth OFF
__term_sd_task_pre_model_194 get_modelscope_model licyks/invokeai-model/master/sd-1/t2i_adapter/depth-sd15/diffusion_pytorch_model.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/depth-sd15 # depth(308m) OFF
__term_sd_task_pre_model_195 get_modelscope_model licyks/invokeai-model/master/sd-1/t2i_adapter/sketch-sd15/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/sketch-sd15 # sketch OFF
__term_sd_task_pre_model_196 get_modelscope_model licyks/invokeai-model/master/sd-1/t2i_adapter/sketch-sd15/diffusion_pytorch_model.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/sketch-sd15 # sketch(308m) OFF
__term_sd_task_pre_model_197 get_modelscope_model licyks/invokeai-model/master/sd-1/t2i_adapter/zoedepth-sd15/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/zoedepth-sd15 # zoedepth OFF
__term_sd_task_pre_model_198 get_modelscope_model licyks/invokeai-model/master/sd-1/t2i_adapter/zoedepth-sd15/diffusion_pytorch_model.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/t2i_adapter/zoedepth-sd15 # zoedepth(308m) OFF
__term_sd_task_pre_model_199 # =====T2I-Adapter(SDXL)模型===== OFF
__term_sd_task_pre_model_200 get_modelscope_model licyks/invokeai-model/master/sdxl/t2i_adapter/canny-sdxl/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/canny-sdxl # canny OFF
__term_sd_task_pre_model_201 get_modelscope_model licyks/invokeai-model/master/sdxl/t2i_adapter/canny-sdxl/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/canny-sdxl # canny(316m) OFF
__term_sd_task_pre_model_202 get_modelscope_model licyks/invokeai-model/master/sdxl/t2i_adapter/lineart-sdxl/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/lineart-sdxl # lineart OFF
__term_sd_task_pre_model_203 get_modelscope_model licyks/invokeai-model/master/sdxl/t2i_adapter/lineart-sdxl/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/lineart-sdxl # lineart(316m) OFF
__term_sd_task_pre_model_204 get_modelscope_model licyks/invokeai-model/master/sdxl/t2i_adapter/sketch-sdxl/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/sketch-sdxl # sketch OFF
__term_sd_task_pre_model_205 get_modelscope_model licyks/invokeai-model/master/sdxl/t2i_adapter/sketch-sdxl/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/sketch-sdxl # sketch(316m) OFF
__term_sd_task_pre_model_206 get_modelscope_model licyks/invokeai-model/master/sdxl/t2i_adapter/zoedepth-sdxl/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/zoedepth-sdxl # zoedepth OFF
__term_sd_task_pre_model_207 get_modelscope_model licyks/invokeai-model/master/sdxl/t2i_adapter/zoedepth-sdxl/diffusion_pytorch_model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/t2i_adapter/zoedepth-sdxl # zoedepth(316m) OFF
__term_sd_task_pre_model_208 # =====IP-Adapter(SD1.5)模型===== OFF
__term_sd_task_pre_model_209 get_modelscope_model licyks/invokeai-model/master/any/clip_vision/ip_adapter_sd_image_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/any/clip_vision/ip_adapter_sd_image_encoder # clip_vision OFF
__term_sd_task_pre_model_210 get_modelscope_model licyks/invokeai-model/master/any/clip_vision/ip_adapter_sd_image_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/any/clip_vision/ip_adapter_sd_image_encoder # clip_vision(2.53g) OFF
__term_sd_task_pre_model_211 get_modelscope_model licyks/invokeai-model/master/sd-1/ip_adapter/ip_adapter_plus_face_sd15/image_encoder.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_plus_face_sd15 # plus-face OFF
__term_sd_task_pre_model_212 get_modelscope_model licyks/invokeai-model/master/sd-1/ip_adapter/ip_adapter_plus_face_sd15/ip_adapter.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_plus_face_sd15 # plus-face(98.1m) OFF
__term_sd_task_pre_model_213 get_modelscope_model licyks/invokeai-model/master/sd-1/ip_adapter/ip_adapter_plus_sd15/image_encoder.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_plus_sd15 # plus OFF
__term_sd_task_pre_model_214 get_modelscope_model licyks/invokeai-model/master/sd-1/ip_adapter/ip_adapter_plus_sd15/ip_adapter.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_plus_sd15 # plus(158m) OFF
__term_sd_task_pre_model_215 get_modelscope_model licyks/invokeai-model/master/sd-1/ip_adapter/ip_adapter_sd15/image_encoder.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_sd15 # normal OFF
__term_sd_task_pre_model_216 get_modelscope_model licyks/invokeai-model/master/sd-1/ip_adapter/ip_adapter_sd15/ip_adapter.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sd-1/ip_adapter/ip_adapter_sd15 # normal(44.6m) OFF
__term_sd_task_pre_model_217 # =====IP-Adapter(SDXL)模型===== OFF
__term_sd_task_pre_model_218 get_modelscope_model licyks/invokeai-model/master/any/clip_vision/ip_adapter_sdxl_image_encoder/config.json "${INVOKEAI_ROOT_PATH}"/invokeai/models/any/clip_vision/ip_adapter_sdxl_image_encoder # clip_vision OFF
__term_sd_task_pre_model_219 get_modelscope_model licyks/invokeai-model/master/any/clip_vision/ip_adapter_sdxl_image_encoder/model.safetensors "${INVOKEAI_ROOT_PATH}"/invokeai/models/any/clip_vision/ip_adapter_sdxl_image_encoder # clip_vision(3.69g) OFF
__term_sd_task_pre_model_220 get_modelscope_model licyks/invokeai-model/master/sdxl/ip_adapter/ip_adapter_sdxl/image_encoder.txt "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/ip_adapter/ip_adapter_sdxl # normal OFF
__term_sd_task_pre_model_221 get_modelscope_model licyks/invokeai-model/master/sdxl/ip_adapter/ip_adapter_sdxl/ip_adapter.bin "${INVOKEAI_ROOT_PATH}"/invokeai/models/sdxl/ip_adapter/ip_adapter_sdxl # normal(702.6m) OFF
|
2301_81996401/term-sd
|
install/invokeai/invokeai_ms_model.sh
|
Shell
|
agpl-3.0
| 49,389
|
__term_sd_task_pre_model_1 =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 =====SD2.1大模型===== OFF
__term_sd_task_pre_model_5 v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_6 wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_7 wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_8 =====SDXL大模型===== OFF
__term_sd_task_pre_model_9 sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_10 sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_11 sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_12 animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_13 animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_14 animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_15 animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_16 animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_17 animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_18 holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_19 kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_20 clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_21 UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_22 RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_23 sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_24 kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_25 kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_26 kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_27 kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_28 kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_29 starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_30 heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_31 heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_32 baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_33 baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_34 sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_35 sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_36 SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_37 SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_38 Illustrious-XL-v0.1(6.94g) ON
__term_sd_task_pre_model_39 Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_40 Illustrious-XL-v1.0(6.94g) OFF
__term_sd_task_pre_model_41 Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_42 Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_43 Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_44 jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_45 PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_46 miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_47 waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_48 tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_49 noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_50 noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_51 noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_52 noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_53 noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_54 noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_55 noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_56 noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_57 noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_58 noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_59 noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_60 noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_61 noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_62 PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_63 PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_64 ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_65 pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_66 tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_67 omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_68 animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_69 artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_70 artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_71 =====VAE模型===== OFF
__term_sd_task_pre_model_72 vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_73 vae-ft-mse-840000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_74 sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_75 sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_76 =====FLUX模型===== OFF
__term_sd_task_pre_model_77 flux1-dev(23.8g) OFF
__term_sd_task_pre_model_78 flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_79 ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_80 jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_81 nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_82 shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_83 =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_84 clip_l(246.1m) OFF
__term_sd_task_pre_model_85 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_86 ae(335m) OFF
|
2301_81996401/term-sd
|
install/kohya_ss/dialog_kohya_ss_hf_model.sh
|
Shell
|
agpl-3.0
| 5,284
|
__term_sd_task_pre_model_1 =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 =====SD2.1大模型===== OFF
__term_sd_task_pre_model_5 v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_6 wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_7 wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_8 =====SDXL大模型===== OFF
__term_sd_task_pre_model_9 sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_10 sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_11 sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_12 animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_13 animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_14 animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_15 animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_16 animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_17 animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_18 holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_19 kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_20 clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_21 UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_22 RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_23 sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_24 kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_25 kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_26 kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_27 kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_28 kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_29 starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_30 heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_31 heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_32 baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_33 baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_34 sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_35 sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_36 SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_37 SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_38 Illustrious-XL-v0.1(6.94g) ON
__term_sd_task_pre_model_39 Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_40 Illustrious-XL-v1.0(6.94g) OFF
__term_sd_task_pre_model_41 Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_42 Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_43 Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_44 jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_45 PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_46 miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_47 waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_48 tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_49 noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_50 noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_51 noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_52 noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_53 noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_54 noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_55 noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_56 noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_57 noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_58 noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_59 noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_60 noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_61 noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_62 PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_63 PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_64 ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_65 pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_66 tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_67 omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_68 animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_69 artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_70 artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_71 =====VAE模型===== OFF
__term_sd_task_pre_model_72 vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_73 vae-ft-mse-840000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_74 sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_75 sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_76 =====FLUX模型===== OFF
__term_sd_task_pre_model_77 flux1-dev(23.8g) OFF
__term_sd_task_pre_model_78 flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_79 ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_80 jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_81 nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_82 shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_83 =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_84 clip_l(246.1m) OFF
__term_sd_task_pre_model_85 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_86 ae(335m) OFF
|
2301_81996401/term-sd
|
install/kohya_ss/dialog_kohya_ss_ms_model.sh
|
Shell
|
agpl-3.0
| 5,284
|
__term_sd_task_sys term_sd_mkdir "${KOHYA_SS_PARENT_PATH}"
__term_sd_task_sys cd "${KOHYA_SS_PARENT_PATH}"
__term_sd_task_sys term_sd_tmp_enable_proxy
__term_sd_task_pre_core git_clone_repository --disable-submod https://github.com/bmaltais/kohya_ss "${KOHYA_SS_PARENT_PATH}" "${KOHYA_SS_FOLDER}"
__term_sd_task_pre_core git_clone_repository --disable-submod https://github.com/kohya-ss/sd-scripts "${KOHYA_SS_ROOT_PATH}" sd-scripts # kohya_ss 后端
__term_sd_task_sys cd "${KOHYA_SS_ROOT_PATH}"
__term_sd_task_pre_core git_init_submodule "${KOHYA_SS_ROOT_PATH}" # 初始化 Git 子模块
__term_sd_task_sys is_sd_repo_exist "${KOHYA_SS_ROOT_PATH}"
__term_sd_task_sys term_sd_tmp_disable_proxy # 临时取消代理, 避免一些不必要的网络减速
__term_sd_task_pre_core create_venv "${KOHYA_SS_ROOT_PATH}"
__term_sd_task_sys enter_venv "${KOHYA_SS_ROOT_PATH}"
__term_sd_task_pre_core term_sd_mkdir "${KOHYA_SS_ROOT_PATH}"/output
__term_sd_task_pre_core term_sd_mkdir "${KOHYA_SS_ROOT_PATH}"/train
__term_sd_task_pre_core install_pytorch # 安装 PyTorch
__term_sd_task_pre_core install_python_package -r "${KOHYA_SS_ROOT_PATH}"/requirements.txt
__term_sd_task_pre_core install_python_package bitsandbytes -U
__term_sd_task_sys cd ..
|
2301_81996401/term-sd
|
install/kohya_ss/kohya_ss_core.sh
|
Shell
|
agpl-3.0
| 1,241
|
__term_sd_task_pre_model_1 # =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/v1-5-pruned-emaonly.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/animefull-final-pruned.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 # =====SD2.1大模型===== OFF
__term_sd_task_pre_model_5 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/v2-1_768-ema-pruned.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_6 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/wd-1-4-anime_e2.ckpt "${KOHYA_SS_ROOT_PATH}"/models/ # wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_7 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/wd-mofu-fp16.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_8 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_9 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_base_1.0_0.9vae.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_10 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_refiner_1.0_0.9vae.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_11 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_turbo_1.0_fp16.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_12 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.0-base.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_13 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_14 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_15 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_16 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0-opt.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_17 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0-zero.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_18 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/holodayo-xl-2.1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_19 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kivotos-xl-2.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_20 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/clandestine-xl-1.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_21 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/UrangDiffusion-1.1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_22 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/RaeDiffusion-XL-v2.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_23 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_anime_V52.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_24 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-delta-rev1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_25 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohakuXLEpsilon_rev1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_26 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-epsilon-rev2.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_27 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-epsilon-rev3.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_28 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-zeta.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_29 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/starryXLV52_v52.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_30 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/heartOfAppleXL_v20.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_31 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/heartOfAppleXL_v30.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_32 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/baxlBartstylexlBlueArchiveFlatCelluloid_xlv1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_33 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/baxlBlueArchiveFlatCelluloidStyle_xlv3.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_34 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sanaexlAnimeV10_v10.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_35 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sanaexlAnimeV10_v11.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_36 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/SanaeXL-Anime-v1.2-aesthetic.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_37 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/SanaeXL-Anime-v1.3-aesthetic.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_38 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v0.1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v0.1(6.94g) ON
__term_sd_task_pre_model_39 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v0.1-GUIDED.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_40 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v1.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v1.0(6.94g) OFF
__term_sd_task_pre_model_41 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v1.1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_42 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v2.0-stable.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_43 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v2.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_44 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/jruTheJourneyRemains_v25XL.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_45 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_illustriousxl10.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_46 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/miaomiaoHarem_v15a.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_47 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/waiNSFWIllustrious_v80.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_48 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/tIllunai3_v4.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_49 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_earlyAccessVersion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_50 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred05Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_51 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred075.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_52 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred077.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_53 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred10Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_54 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred11Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_55 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPredTestVersion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_56 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred05Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_57 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred06Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_58 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred065SVersion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_59 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred075SVersion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_60 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred09RVersion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_61 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred10Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_62 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_nbxl12.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_63 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_nbxlVPredV10.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_64 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/ponyDiffusionV6XL_v6StartWithThisOne.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_65 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/pdForAnime_v20.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_66 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/tPonynai3_v51WeightOptimized.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_67 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/omegaPonyXLAnime_v20.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_68 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animeIllustDiffusion_v061.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_69 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/artiwaifuDiffusion_v10.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_70 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/artiwaifu-diffusion-v2.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_71 # =====VAE模型===== OFF
__term_sd_task_pre_model_72 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sd_1.5/vae-ft-ema-560000-ema-pruned.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_73 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sd_1.5/vae-ft-mse-840000-ema-pruned.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # vae-ft-mse-840000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_74 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sdxl_1.0/sdxl_fp16_fix_vae.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_75 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sdxl_1.0/sdxl_vae.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_76 # =====FLUX模型===== OFF
__term_sd_task_pre_model_77 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # flux1-dev(23.8g) OFF
__term_sd_task_pre_model_78 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_79 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/ashen0209-flux1-dev2pro.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_80 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/jimmycarter-LibreFLUX.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_81 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/nyanko7-flux-dev-de-distill.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_82 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/shuttle-3-diffusion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_83 # =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_84 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/clip_l.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # clip_l(246.1m) OFF
__term_sd_task_pre_model_85 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5xxl_fp16.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_86 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_vae/ae.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # ae(335m) OFF
|
2301_81996401/term-sd
|
install/kohya_ss/kohya_ss_hf_model.sh
|
Shell
|
agpl-3.0
| 16,811
|
__term_sd_task_pre_model_1 # =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 get_modelscope_model licyks/sd-model/master/sd_1.5/v1-5-pruned-emaonly.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 get_modelscope_model licyks/sd-model/master/sd_1.5/animefull-final-pruned.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 # =====SD2.1大模型===== OFF
__term_sd_task_pre_model_5 get_modelscope_model licyks/sd-model/master/sd_2.1/v2-1_768-ema-pruned.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_6 get_modelscope_model licyks/sd-model/master/sd_2.1/wd-1-4-anime_e2.ckpt "${KOHYA_SS_ROOT_PATH}"/models/ # wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_7 get_modelscope_model licyks/sd-model/master/sd_2.1/wd-mofu-fp16.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_8 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_9 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_base_1.0_0.9vae.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_10 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_refiner_1.0_0.9vae.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_11 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_turbo_1.0_fp16.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_12 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.0-base.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_13 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_14 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_15 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_16 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0-opt.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_17 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0-zero.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_18 get_modelscope_model licyks/sd-model/master/sdxl_1.0/holodayo-xl-2.1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_19 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kivotos-xl-2.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_20 get_modelscope_model licyks/sd-model/master/sdxl_1.0/clandestine-xl-1.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_21 get_modelscope_model licyks/sd-model/master/sdxl_1.0/UrangDiffusion-1.1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_22 get_modelscope_model licyks/sd-model/master/sdxl_1.0/RaeDiffusion-XL-v2.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_23 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_anime_V52.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_24 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-delta-rev1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_25 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohakuXLEpsilon_rev1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_26 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-epsilon-rev2.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_27 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-epsilon-rev3.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_28 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-zeta.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_29 get_modelscope_model licyks/sd-model/master/sdxl_1.0/starryXLV52_v52.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_30 get_modelscope_model licyks/sd-model/master/sdxl_1.0/heartOfAppleXL_v20.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_31 get_modelscope_model licyks/sd-model/master/sdxl_1.0/heartOfAppleXL_v30.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_32 get_modelscope_model licyks/sd-model/master/sdxl_1.0/baxlBartstylexlBlueArchiveFlatCelluloid_xlv1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_33 get_modelscope_model licyks/sd-model/master/sdxl_1.0/baxlBlueArchiveFlatCelluloidStyle_xlv3.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_34 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sanaexlAnimeV10_v10.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_35 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sanaexlAnimeV10_v11.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_36 get_modelscope_model licyks/sd-model/master/sdxl_1.0/SanaeXL-Anime-v1.2-aesthetic.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_37 get_modelscope_model licyks/sd-model/master/sdxl_1.0/SanaeXL-Anime-v1.3-aesthetic.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_38 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v0.1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v0.1(6.94g) ON
__term_sd_task_pre_model_39 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v0.1-GUIDED.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_40 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v1.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v1.0(6.94g) OFF
__term_sd_task_pre_model_41 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v1.1.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_42 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v2.0-stable.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_43 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v2.0.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_44 get_modelscope_model licyks/sd-model/master/sdxl_1.0/jruTheJourneyRemains_v25XL.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_45 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_illustriousxl10.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_46 get_modelscope_model licyks/sd-model/master/sdxl_1.0/miaomiaoHarem_v15a.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_47 get_modelscope_model licyks/sd-model/master/sdxl_1.0/waiNSFWIllustrious_v80.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_48 get_modelscope_model licyks/sd-model/master/sdxl_1.0/tIllunai3_v4.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_49 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_earlyAccessVersion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_50 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred05Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_51 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred075.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_52 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred077.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_53 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred10Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_54 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred11Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_55 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPredTestVersion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_56 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred05Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_57 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred06Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_58 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred065SVersion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_59 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred075SVersion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_60 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred09RVersion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_61 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred10Version.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_62 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_nbxl12.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_63 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_nbxlVPredV10.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_64 get_modelscope_model licyks/sd-model/master/sdxl_1.0/ponyDiffusionV6XL_v6StartWithThisOne.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_65 get_modelscope_model licyks/sd-model/master/sdxl_1.0/pdForAnime_v20.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_66 get_modelscope_model licyks/sd-model/master/sdxl_1.0/tPonynai3_v51WeightOptimized.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_67 get_modelscope_model licyks/sd-model/master/sdxl_1.0/omegaPonyXLAnime_v20.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_68 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animeIllustDiffusion_v061.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_69 get_modelscope_model licyks/sd-model/master/sdxl_1.0/artiwaifuDiffusion_v10.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_70 get_modelscope_model licyks/sd-model/master/sdxl_1.0/artiwaifu-diffusion-v2.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_71 # =====VAE模型===== OFF
__term_sd_task_pre_model_72 get_modelscope_model licyks/sd-vae/master/sd_1.5/vae-ft-ema-560000-ema-pruned.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_73 get_modelscope_model licyks/sd-vae/master/sd_1.5/vae-ft-mse-840000-ema-pruned.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # vae-ft-mse-840000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_74 get_modelscope_model licyks/sd-vae/master/sdxl_1.0/sdxl_fp16_fix_vae.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_75 get_modelscope_model licyks/sd-vae/master/sdxl_1.0/sdxl_vae.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_76 # =====FLUX模型===== OFF
__term_sd_task_pre_model_77 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # flux1-dev(23.8g) OFF
__term_sd_task_pre_model_78 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_79 get_modelscope_model licyks/flux-model/master/flux_1/ashen0209-flux1-dev2pro.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_80 get_modelscope_model licyks/flux-model/master/flux_1/jimmycarter-LibreFLUX.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_81 get_modelscope_model licyks/flux-model/master/flux_1/nyanko7-flux-dev-de-distill.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_82 get_modelscope_model licyks/flux-model/master/flux_1/shuttle-3-diffusion.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_83 # =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_84 get_modelscope_model licyks/flux-model/master/flux_text_encoders/clip_l.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # clip_l(246.1m) OFF
__term_sd_task_pre_model_85 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5xxl_fp16.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_86 get_modelscope_model licyks/flux-model/master/flux_vae/ae.safetensors "${KOHYA_SS_ROOT_PATH}"/models/ # ae(335m) OFF
|
2301_81996401/term-sd
|
install/kohya_ss/kohya_ss_ms_model.sh
|
Shell
|
agpl-3.0
| 15,051
|
__term_sd_task_pre_model_1 =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 =====SD2.1大模型===== OFF
__term_sd_task_pre_model_5 v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_6 wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_7 wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_8 =====SDXL大模型===== OFF
__term_sd_task_pre_model_9 sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_10 sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_11 sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_12 animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_13 animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_14 animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_15 animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_16 animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_17 animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_18 holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_19 kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_20 clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_21 UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_22 RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_23 sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_24 kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_25 kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_26 kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_27 kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_28 kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_29 starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_30 heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_31 heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_32 baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_33 baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_34 sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_35 sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_36 SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_37 SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_38 Illustrious-XL-v0.1(6.94g) ON
__term_sd_task_pre_model_39 Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_40 Illustrious-XL-v1.0(6.94g) OFF
__term_sd_task_pre_model_41 Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_42 Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_43 Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_44 jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_45 PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_46 miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_47 waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_48 tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_49 noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_50 noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_51 noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_52 noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_53 noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_54 noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_55 noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_56 noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_57 noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_58 noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_59 noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_60 noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_61 noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_62 PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_63 PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_64 ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_65 pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_66 tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_67 omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_68 animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_69 artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_70 artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_71 =====VAE模型===== OFF
__term_sd_task_pre_model_72 vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_73 vae-ft-mse-840000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_74 sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_75 sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_76 =====FLUX模型===== OFF
__term_sd_task_pre_model_77 flux1-dev(23.8g) OFF
__term_sd_task_pre_model_78 flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_79 ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_80 jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_81 nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_82 shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_83 =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_84 clip_l(246.1m) OFF
__term_sd_task_pre_model_85 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_86 ae(335m) OFF
|
2301_81996401/term-sd
|
install/lora_scripts/dialog_lora_scripts_hf_model.sh
|
Shell
|
agpl-3.0
| 5,284
|
__term_sd_task_pre_model_1 =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 =====SD2.1大模型===== OFF
__term_sd_task_pre_model_5 v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_6 wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_7 wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_8 =====SDXL大模型===== OFF
__term_sd_task_pre_model_9 sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_10 sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_11 sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_12 animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_13 animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_14 animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_15 animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_16 animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_17 animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_18 holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_19 kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_20 clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_21 UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_22 RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_23 sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_24 kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_25 kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_26 kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_27 kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_28 kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_29 starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_30 heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_31 heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_32 baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_33 baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_34 sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_35 sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_36 SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_37 SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_38 Illustrious-XL-v0.1(6.94g) ON
__term_sd_task_pre_model_39 Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_40 Illustrious-XL-v1.0(6.94g) OFF
__term_sd_task_pre_model_41 Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_42 Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_43 Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_44 jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_45 PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_46 miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_47 waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_48 tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_49 noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_50 noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_51 noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_52 noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_53 noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_54 noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_55 noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_56 noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_57 noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_58 noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_59 noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_60 noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_61 noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_62 PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_63 PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_64 ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_65 pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_66 tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_67 omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_68 animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_69 artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_70 artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_71 =====VAE模型===== OFF
__term_sd_task_pre_model_72 vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_73 vae-ft-mse-840000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_74 sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_75 sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_76 =====FLUX模型===== OFF
__term_sd_task_pre_model_77 flux1-dev(23.8g) OFF
__term_sd_task_pre_model_78 flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_79 ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_80 jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_81 nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_82 shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_83 =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_84 clip_l(246.1m) OFF
__term_sd_task_pre_model_85 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_86 ae(335m) OFF
|
2301_81996401/term-sd
|
install/lora_scripts/dialog_lora_scripts_ms_model.sh
|
Shell
|
agpl-3.0
| 5,284
|
__term_sd_task_sys term_sd_mkdir "${LORA_SCRIPTS_PARENT_PATH}"
__term_sd_task_sys cd "${LORA_SCRIPTS_PARENT_PATH}"
__term_sd_task_sys term_sd_tmp_enable_proxy
__term_sd_task_pre_core git_clone_repository --disable-submod https://github.com/Akegarasu/lora-scripts "${LORA_SCRIPTS_PARENT_PATH}" "${LORA_SCRIPTS_FOLDER}"
__term_sd_task_sys is_sd_repo_exist "${LORA_SCRIPTS_ROOT_PATH}"
__term_sd_task_pre_core git_clone_repository --disable-submod https://github.com/hanamizuki-ai/lora-gui-dist "${LORA_SCRIPTS_ROOT_PATH}" frontend # lora-scripts 前端
__term_sd_task_pre_core git_clone_repository --disable-submod https://github.com/Akegarasu/dataset-tag-editor "${LORA_SCRIPTS_ROOT_PATH}"/mikazuki dataset-tag-editor # 标签编辑器
__term_sd_task_sys term_sd_tmp_disable_proxy # 临时取消代理, 避免一些不必要的网络减速
__term_sd_task_sys cd "${LORA_SCRIPTS_ROOT_PATH}"
__term_sd_task_pre_core git_init_submodule "${LORA_SCRIPTS_ROOT_PATH}" # 初始化 Git 子模块
__term_sd_task_pre_core create_venv "${LORA_SCRIPTS_ROOT_PATH}"
__term_sd_task_sys enter_venv "${LORA_SCRIPTS_ROOT_PATH}"
__term_sd_task_pre_core install_pytorch # 安装 PyTorch
__term_sd_task_pre_core install_python_package -r "${LORA_SCRIPTS_ROOT_PATH}"/requirements.txt # lora-scripts 依赖
__term_sd_task_sys cd ..
|
2301_81996401/term-sd
|
install/lora_scripts/lora_scripts_core.sh
|
Shell
|
agpl-3.0
| 1,306
|
__term_sd_task_pre_model_1 # =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/v1-5-pruned-emaonly.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/animefull-final-pruned.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 # =====SD2.1大模型===== OFF
__term_sd_task_pre_model_5 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/v2-1_768-ema-pruned.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_6 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/wd-1-4-anime_e2.ckpt "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_7 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/wd-mofu-fp16.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_8 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_9 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_base_1.0_0.9vae.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_10 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_refiner_1.0_0.9vae.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_11 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_turbo_1.0_fp16.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_12 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.0-base.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_13 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_14 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_15 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_16 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0-opt.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_17 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0-zero.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_18 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/holodayo-xl-2.1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_19 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kivotos-xl-2.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_20 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/clandestine-xl-1.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_21 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/UrangDiffusion-1.1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_22 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/RaeDiffusion-XL-v2.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_23 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_anime_V52.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_24 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-delta-rev1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_25 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohakuXLEpsilon_rev1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_26 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-epsilon-rev2.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_27 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-epsilon-rev3.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_28 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-zeta.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_29 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/starryXLV52_v52.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_30 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/heartOfAppleXL_v20.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_31 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/heartOfAppleXL_v30.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_32 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/baxlBartstylexlBlueArchiveFlatCelluloid_xlv1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_33 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/baxlBlueArchiveFlatCelluloidStyle_xlv3.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_34 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sanaexlAnimeV10_v10.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_35 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sanaexlAnimeV10_v11.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_36 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/SanaeXL-Anime-v1.2-aesthetic.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_37 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/SanaeXL-Anime-v1.3-aesthetic.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_38 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v0.1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v0.1(6.94g) ON
__term_sd_task_pre_model_39 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v0.1-GUIDED.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_40 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v1.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v1.0(6.94g) OFF
__term_sd_task_pre_model_41 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v1.1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_42 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v2.0-stable.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_43 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v2.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_44 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/jruTheJourneyRemains_v25XL.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_45 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_illustriousxl10.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_46 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/miaomiaoHarem_v15a.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_47 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/waiNSFWIllustrious_v80.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_48 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/tIllunai3_v4.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_49 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_earlyAccessVersion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_50 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred05Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_51 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred075.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_52 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred077.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_53 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred10Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_54 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred11Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_55 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPredTestVersion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_56 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred05Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_57 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred06Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_58 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred065SVersion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_59 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred075SVersion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_60 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred09RVersion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_61 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred10Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_62 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_nbxl12.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_63 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_nbxlVPredV10.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_64 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/ponyDiffusionV6XL_v6StartWithThisOne.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_65 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/pdForAnime_v20.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_66 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/tPonynai3_v51WeightOptimized.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_67 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/omegaPonyXLAnime_v20.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_68 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animeIllustDiffusion_v061.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_69 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/artiwaifuDiffusion_v10.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_70 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/artiwaifu-diffusion-v2.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_71 # =====VAE模型===== OFF
__term_sd_task_pre_model_72 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sd_1.5/vae-ft-ema-560000-ema-pruned.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_73 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sd_1.5/vae-ft-mse-840000-ema-pruned.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # vae-ft-mse-840000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_74 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sdxl_1.0/sdxl_fp16_fix_vae.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_75 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sdxl_1.0/sdxl_vae.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_76 # =====FLUX模型===== OFF
__term_sd_task_pre_model_77 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # flux1-dev(23.8g) OFF
__term_sd_task_pre_model_78 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_79 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/ashen0209-flux1-dev2pro.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_80 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/jimmycarter-LibreFLUX.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_81 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/nyanko7-flux-dev-de-distill.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_82 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/shuttle-3-diffusion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_83 # =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_84 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/clip_l.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # clip_l(246.1m) OFF
__term_sd_task_pre_model_85 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5xxl_fp16.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_86 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_vae/ae.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # ae(335m) OFF
|
2301_81996401/term-sd
|
install/lora_scripts/lora_scripts_hf_model.sh
|
Shell
|
agpl-3.0
| 17,371
|
__term_sd_task_pre_model_1 # =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 get_modelscope_model licyks/sd-model/master/sd_1.5/v1-5-pruned-emaonly.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 get_modelscope_model licyks/sd-model/master/sd_1.5/animefull-final-pruned.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 # =====SD2.1大模型===== OFF
__term_sd_task_pre_model_5 get_modelscope_model licyks/sd-model/master/sd_2.1/v2-1_768-ema-pruned.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_6 get_modelscope_model licyks/sd-model/master/sd_2.1/wd-1-4-anime_e2.ckpt "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_7 get_modelscope_model licyks/sd-model/master/sd_2.1/wd-mofu-fp16.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_8 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_9 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_base_1.0_0.9vae.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_10 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_refiner_1.0_0.9vae.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_11 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_turbo_1.0_fp16.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_12 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.0-base.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_13 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_14 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_15 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_16 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0-opt.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_17 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0-zero.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_18 get_modelscope_model licyks/sd-model/master/sdxl_1.0/holodayo-xl-2.1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_19 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kivotos-xl-2.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_20 get_modelscope_model licyks/sd-model/master/sdxl_1.0/clandestine-xl-1.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_21 get_modelscope_model licyks/sd-model/master/sdxl_1.0/UrangDiffusion-1.1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_22 get_modelscope_model licyks/sd-model/master/sdxl_1.0/RaeDiffusion-XL-v2.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_23 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_anime_V52.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_24 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-delta-rev1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_25 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohakuXLEpsilon_rev1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_26 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-epsilon-rev2.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_27 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-epsilon-rev3.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_28 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-zeta.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_29 get_modelscope_model licyks/sd-model/master/sdxl_1.0/starryXLV52_v52.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_30 get_modelscope_model licyks/sd-model/master/sdxl_1.0/heartOfAppleXL_v20.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_31 get_modelscope_model licyks/sd-model/master/sdxl_1.0/heartOfAppleXL_v30.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_32 get_modelscope_model licyks/sd-model/master/sdxl_1.0/baxlBartstylexlBlueArchiveFlatCelluloid_xlv1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_33 get_modelscope_model licyks/sd-model/master/sdxl_1.0/baxlBlueArchiveFlatCelluloidStyle_xlv3.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_34 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sanaexlAnimeV10_v10.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_35 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sanaexlAnimeV10_v11.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_36 get_modelscope_model licyks/sd-model/master/sdxl_1.0/SanaeXL-Anime-v1.2-aesthetic.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_37 get_modelscope_model licyks/sd-model/master/sdxl_1.0/SanaeXL-Anime-v1.3-aesthetic.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_38 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v0.1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v0.1(6.94g) ON
__term_sd_task_pre_model_39 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v0.1-GUIDED.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_40 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v1.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v1.0(6.94g) OFF
__term_sd_task_pre_model_41 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v1.1.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_42 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v2.0-stable.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_43 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v2.0.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_44 get_modelscope_model licyks/sd-model/master/sdxl_1.0/jruTheJourneyRemains_v25XL.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_45 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_illustriousxl10.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_46 get_modelscope_model licyks/sd-model/master/sdxl_1.0/miaomiaoHarem_v15a.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_47 get_modelscope_model licyks/sd-model/master/sdxl_1.0/waiNSFWIllustrious_v80.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_48 get_modelscope_model licyks/sd-model/master/sdxl_1.0/tIllunai3_v4.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_49 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_earlyAccessVersion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_50 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred05Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_51 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred075.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_52 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred077.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_53 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred10Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_54 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred11Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_55 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPredTestVersion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_56 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred05Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_57 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred06Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_58 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred065SVersion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_59 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred075SVersion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_60 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred09RVersion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_61 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred10Version.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_62 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_nbxl12.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_63 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_nbxlVPredV10.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_64 get_modelscope_model licyks/sd-model/master/sdxl_1.0/ponyDiffusionV6XL_v6StartWithThisOne.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_65 get_modelscope_model licyks/sd-model/master/sdxl_1.0/pdForAnime_v20.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_66 get_modelscope_model licyks/sd-model/master/sdxl_1.0/tPonynai3_v51WeightOptimized.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_67 get_modelscope_model licyks/sd-model/master/sdxl_1.0/omegaPonyXLAnime_v20.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_68 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animeIllustDiffusion_v061.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_69 get_modelscope_model licyks/sd-model/master/sdxl_1.0/artiwaifuDiffusion_v10.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_70 get_modelscope_model licyks/sd-model/master/sdxl_1.0/artiwaifu-diffusion-v2.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_71 # =====VAE模型===== OFF
__term_sd_task_pre_model_72 get_modelscope_model licyks/sd-vae/master/sd_1.5/vae-ft-ema-560000-ema-pruned.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_73 get_modelscope_model licyks/sd-vae/master/sd_1.5/vae-ft-mse-840000-ema-pruned.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # vae-ft-mse-840000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_74 get_modelscope_model licyks/sd-vae/master/sdxl_1.0/sdxl_fp16_fix_vae.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_75 get_modelscope_model licyks/sd-vae/master/sdxl_1.0/sdxl_vae.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_76 # =====FLUX模型===== OFF
__term_sd_task_pre_model_77 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # flux1-dev(23.8g) OFF
__term_sd_task_pre_model_78 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_79 get_modelscope_model licyks/flux-model/master/flux_1/ashen0209-flux1-dev2pro.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_80 get_modelscope_model licyks/flux-model/master/flux_1/jimmycarter-LibreFLUX.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_81 get_modelscope_model licyks/flux-model/master/flux_1/nyanko7-flux-dev-de-distill.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_82 get_modelscope_model licyks/flux-model/master/flux_1/shuttle-3-diffusion.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_83 # =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_84 get_modelscope_model licyks/flux-model/master/flux_text_encoders/clip_l.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # clip_l(246.1m) OFF
__term_sd_task_pre_model_85 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5xxl_fp16.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_86 get_modelscope_model licyks/flux-model/master/flux_vae/ae.safetensors "${LORA_SCRIPTS_ROOT_PATH}"/sd-models/ # ae(335m) OFF
|
2301_81996401/term-sd
|
install/lora_scripts/lora_scripts_ms_model.sh
|
Shell
|
agpl-3.0
| 15,611
|
__term_sd_task_pre_ext_1 sd-webui-controlnet ON
__term_sd_task_pre_ext_2 sd-webui-animatediff OFF
__term_sd_task_pre_ext_3 adetailer ON
__term_sd_task_pre_ext_4 sd-webui-IS-NET-pro OFF
__term_sd_task_pre_ext_5 sd-webui-segment-anything ON
__term_sd_task_pre_ext_6 sd-webui-inpaint-anything OFF
__term_sd_task_pre_ext_7 sd-forge-layerdiffuse OFF
__term_sd_task_pre_ext_8 z-a1111-sd-webui-dtg OFF
__term_sd_task_pre_ext_9 sd-webui-stablesr OFF
__term_sd_task_pre_ext_10 z-tipo-extension OFF
__term_sd_task_pre_ext_11 kohya-config-webui OFF
__term_sd_task_pre_ext_12 sd-webui-additional-networks OFF
__term_sd_task_pre_ext_13 a1111-sd-webui-tagcomplete ON
__term_sd_task_pre_ext_14 multidiffusion-upscaler-for-automatic1111 ON
__term_sd_task_pre_ext_15 sd-dynamic-thresholding ON
__term_sd_task_pre_ext_16 sd-webui-cutoff OFF
__term_sd_task_pre_ext_17 sd-webui-model-converter ON
__term_sd_task_pre_ext_18 sd-webui-supermerger ON
__term_sd_task_pre_ext_19 stable-diffusion-webui-localization-zh_Hans ON
__term_sd_task_pre_ext_20 sd-webui-wd14-tagger ON
__term_sd_task_pre_ext_21 sd-webui-regional-prompter ON
__term_sd_task_pre_ext_22 sd-webui-infinite-image-browsing ON
__term_sd_task_pre_ext_23 stable-diffusion-webui-anti-burn OFF
__term_sd_task_pre_ext_24 loopback_scaler OFF
__term_sd_task_pre_ext_25 latentcoupleregionmapper OFF
__term_sd_task_pre_ext_26 ultimate-upscale-for-automatic1111 ON
__term_sd_task_pre_ext_27 deforum-for-automatic1111-webui OFF
__term_sd_task_pre_ext_28 stable-diffusion-webui-images-browser OFF
__term_sd_task_pre_ext_29 stable-diffusion-webui-huggingface OFF
__term_sd_task_pre_ext_30 sd-civitai-browser OFF
__term_sd_task_pre_ext_31 a1111-stable-diffusion-webui-vram-estimator OFF
__term_sd_task_pre_ext_32 openpose-editor OFF
__term_sd_task_pre_ext_33 sd-webui-depth-lib OFF
__term_sd_task_pre_ext_34 posex OFF
__term_sd_task_pre_ext_35 sd-webui-tunnels OFF
__term_sd_task_pre_ext_36 batchlinks-webui OFF
__term_sd_task_pre_ext_37 stable-diffusion-webui-catppuccin OFF
__term_sd_task_pre_ext_38 a1111-sd-webui-lycoris OFF
__term_sd_task_pre_ext_39 stable-diffusion-webui-rembg OFF
__term_sd_task_pre_ext_40 stable-diffusion-webui-two-shot OFF
__term_sd_task_pre_ext_41 sd-webui-lora-block-weight ON
__term_sd_task_pre_ext_42 sd-face-editor OFF
__term_sd_task_pre_ext_43 sd-webui-prompt-all-in-one ON
__term_sd_task_pre_ext_44 sd-webui-comfyui OFF
__term_sd_task_pre_ext_45 sd-webui-photopea-embed OFF
__term_sd_task_pre_ext_46 sd-webui-openpose-editor ON
__term_sd_task_pre_ext_47 sd-webui-llul OFF
__term_sd_task_pre_ext_48 sd-webui-bilingual-localization OFF
__term_sd_task_pre_ext_49 sd-webui-mov2mov OFF
__term_sd_task_pre_ext_50 ebsynth_utility OFF
__term_sd_task_pre_ext_51 sd_dreambooth_extension OFF
__term_sd_task_pre_ext_52 sd-webui-memory-release OFF
__term_sd_task_pre_ext_53 stable-diffusion-webui-dataset-tag-editor OFF
__term_sd_task_pre_ext_54 sd-webui-deoldify OFF
__term_sd_task_pre_ext_55 stable-diffusion-webui-model-toolkit ON
__term_sd_task_pre_ext_56 sd-webui-oldsix-prompt-dynamic OFF
__term_sd_task_pre_ext_57 sd-webui-fastblend OFF
__term_sd_task_pre_ext_58 StyleSelectorXL OFF
__term_sd_task_pre_ext_59 sd-dynamic-prompts OFF
__term_sd_task_pre_ext_60 LightDiffusionFlow OFF
__term_sd_task_pre_ext_61 sd-webui-workspace OFF
__term_sd_task_pre_ext_62 openOutpaint-webUI-extension OFF
__term_sd_task_pre_ext_63 sd-webui-samplers-scheduler OFF
__term_sd_task_pre_ext_64 sd-webui-boomer OFF
__term_sd_task_pre_ext_65 model-keyword OFF
__term_sd_task_pre_ext_66 Stable-Diffusion-WebUI-TensorRT OFF
__term_sd_task_pre_ext_67 sd-webui-lobe-theme OFF
__term_sd_task_pre_ext_68 stable-diffusion-webui-GPU-temperature-protection OFF
__term_sd_task_pre_ext_69 sd-webui-api-payload-display OFF
__term_sd_task_pre_ext_70 sd-webui-aspect-ratio-helper OFF
__term_sd_task_pre_ext_71 sd-webui-cd-tuner OFF
__term_sd_task_pre_ext_72 sd-webui-negpip OFF
__term_sd_task_pre_ext_73 sd-webui-agent-scheduler OFF
__term_sd_task_pre_ext_74 Stable-Diffusion-Webui-Civitai-Helper OFF
__term_sd_task_pre_ext_75 sd-webui-Lora-queue-helper OFF
__term_sd_task_pre_ext_76 PBRemTools OFF
__term_sd_task_pre_ext_77 sd-webui-rich-text OFF
__term_sd_task_pre_ext_78 image-deduplicate-cluster-webui OFF
__term_sd_task_pre_ext_79 stable-diffusion-webui-composable-lora OFF
__term_sd_task_pre_ext_80 sdweb-merge-block-weighted-gui OFF
__term_sd_task_pre_ext_81 sd-civitai-browser-plus OFF
__term_sd_task_pre_ext_82 sd-webui-weight-helper OFF
__term_sd_task_pre_ext_83 sd-danbooru-tags-upsampler OFF
__term_sd_task_pre_ext_84 Stylez OFF
__term_sd_task_pre_ext_85 sd-webui-next-style OFF
__term_sd_task_pre_ext_86 a1111-sd-webui-haku-img ON
__term_sd_task_pre_ext_87 Kohaku-NAI OFF
__term_sd_task_pre_ext_88 sd-webui-cli-interruption OFF
__term_sd_task_pre_ext_89 sdwebui-close-confirmation-dialogue OFF
__term_sd_task_pre_ext_90 sd-webui-hires-fix-tweaks OFF
__term_sd_task_pre_ext_91 sd-webui-custom-autolaunch OFF
__term_sd_task_pre_ext_92 sd-webui-triposr OFF
__term_sd_task_pre_ext_93 sd-webui-qic-console OFF
__term_sd_task_pre_ext_94 sd-webui-qrcode-toolkit OFF
__term_sd_task_pre_ext_95 sd-webui-controlnet-marigold OFF
__term_sd_task_pre_ext_96 Euler-Smea-Dyn-Sampler OFF
__term_sd_task_pre_ext_97 advanced_euler_sampler_extension OFF
__term_sd_task_pre_ext_98 sd-webui-vectorscope-cc OFF
__term_sd_task_pre_ext_99 sd-webui-smea OFF
__term_sd_task_pre_ext_100 sd-webui-neutral-prompt OFF
__term_sd_task_pre_ext_101 sd-webui-tabs-extension OFF
__term_sd_task_pre_ext_102 sd-forge-ic-light OFF
__term_sd_task_pre_ext_103 webui-fooocus-prompt-expansion OFF
__term_sd_task_pre_ext_104 sd-webui-model-patcher OFF
__term_sd_task_pre_ext_105 lora-prompt-tool OFF
__term_sd_task_pre_ext_106 sd-webui-easy-tag-insert OFF
__term_sd_task_pre_ext_107 sd-webui-i2i-ancestral-tree OFF
__term_sd_task_pre_ext_108 sd-forge-couple OFF
__term_sd_task_pre_ext_109 sd-webui-advanced-xyz OFF
__term_sd_task_pre_ext_110 sd-webui-mosaic-outpaint ON
__term_sd_task_pre_ext_111 sd-webui-image-comparison OFF
__term_sd_task_pre_ext_112 sd-webui-diffusion-cg OFF
__term_sd_task_pre_ext_113 sd-webui-resharpen OFF
__term_sd_task_pre_ext_114 sd-webui-mobile-friendly OFF
__term_sd_task_pre_ext_115 sd-webui-prompt-format OFF
__term_sd_task_pre_ext_116 sd-webui-aaa OFF
__term_sd_task_pre_ext_117 sd-webui-clear-screen OFF
__term_sd_task_pre_ext_118 sd-webui-auto-res OFF
__term_sd_task_pre_ext_119 sd-webui-moar-generate OFF
__term_sd_task_pre_ext_120 metadata_utils OFF
__term_sd_task_pre_ext_121 sd-webui-xyz-addon OFF
__term_sd_task_pre_ext_122 sd-webui-flash-attention-zluda-win OFF
__term_sd_task_pre_ext_123 sd-webui-split-layout OFF
__term_sd_task_pre_ext_124 sd-webui-oldsix-prompt OFF
__term_sd_task_pre_ext_125 sd-webui-ipex-enhancement OFF
__term_sd_task_pre_ext_126 sd-webui-udav2 OFF
__term_sd_task_pre_ext_127 sd-webui-cn-sam-preprocessor OFF
__term_sd_task_pre_ext_128 sd-webui-pnginfo-beautify OFF
__term_sd_task_pre_ext_129 sd-webui-resource-monitor ON
__term_sd_task_pre_ext_130 chara-searcher OFF
__term_sd_task_pre_ext_131 sd-webui-to_top_button OFF
__term_sd_task_pre_ext_132 sd-webui-aurasr OFF
__term_sd_task_pre_ext_133 a1111-intelli-prompt OFF
__term_sd_task_pre_ext_134 sd-webui-decadetw-auto-prompt-llm OFF
__term_sd_task_pre_ext_135 sd-forge-temperature-settings OFF
__term_sd_task_pre_ext_136 forge-space-SUPIR OFF
__term_sd_task_pre_ext_137 forge-space-ollama OFF
__term_sd_task_pre_ext_138 sd-webui-cardmaster OFF
__term_sd_task_pre_ext_139 extra-network-side-panel-for-a1111 OFF
__term_sd_task_pre_ext_140 sd-forge-regional-prompter OFF
__term_sd_task_pre_ext_141 --sd-webui-ar-plus OFF
__term_sd_task_pre_ext_142 forge2_cleaner OFF
__term_sd_task_pre_ext_143 sd-webui-cleaner OFF
__term_sd_task_pre_ext_144 HyperTile OFF
__term_sd_task_pre_ext_145 forgeFlux_dualPrompt OFF
__term_sd_task_pre_ext_146 GPU_For_T5 OFF
__term_sd_task_pre_ext_147 sd-webui-top-k-emphasis OFF
__term_sd_task_pre_ext_148 uddetailer OFF
__term_sd_task_pre_ext_149 Config-Presets OFF
__term_sd_task_pre_ext_150 seamless-tile-inpainting OFF
__term_sd_task_pre_ext_151 sd-webui-ux OFF
__term_sd_task_pre_ext_152 sd-webui-replacer OFF
__term_sd_task_pre_ext_153 stable-diffusion-webui-wildcards OFF
__term_sd_task_pre_ext_154 sd-webui-freeu OFF
__term_sd_task_pre_ext_155 sd-webui-incantations OFF
__term_sd_task_pre_ext_156 sd-webui-kohya-hiresfix OFF
__term_sd_task_pre_ext_157 sd-webui-model-mixer OFF
__term_sd_task_pre_ext_158 sd-webui-flash-attention2-rdna3-rocm OFF
__term_sd_task_pre_ext_159 sd-webui-tcd-sampler OFF
__term_sd_task_pre_ext_160 sd-webui-birefnet OFF
__term_sd_task_pre_ext_161 stable-diffusion-NPW OFF
__term_sd_task_pre_ext_162 sd_forge_hypertile_svd_z123 OFF
__term_sd_task_pre_ext_163 stable-diffusion-webui-zoomimage OFF
__term_sd_task_pre_ext_164 sd-simple-dimension-preset OFF
__term_sd_task_pre_ext_165 sd-hub OFF
__term_sd_task_pre_ext_166 lora-keywords-finder OFF
__term_sd_task_pre_ext_167 sd-webui-quickrecents OFF
__term_sd_task_pre_ext_168 sd-forge-blockcache OFF
__term_sd_task_pre_ext_169 sd-forge-blockcache OFF
__term_sd_task_pre_ext_170 sd-webui-rewrite-history OFF
__term_sd_task_pre_ext_171 sd-refdrop-forge OFF
__term_sd_task_pre_ext_172 sd-refdrop OFF
__term_sd_task_pre_ext_173 sd-forge-negpip OFF
__term_sd_task_pre_ext_174 sd-webui-segment-anything-altoids OFF
__term_sd_task_pre_ext_175 sd-webui-framepack OFF
__term_sd_task_pre_ext_176 sd-webui-different-save-button-image-format OFF
__term_sd_task_pre_ext_177 sd-webui-frequency-separation OFF
__term_sd_task_pre_ext_178 sd-webui-hide-gradio-message OFF
__term_sd_task_pre_ext_179 sd-webui-licyk-style-image ON
|
2301_81996401/term-sd
|
install/sd_webui/dialog_sd_webui_extension.sh
|
Shell
|
agpl-3.0
| 9,618
|
__term_sd_task_pre_model_1 =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 nai1-artist_all_in_one_merge(2.13g) OFF
__term_sd_task_pre_model_5 Counterfeit-V3.0(4.24g) OFF
__term_sd_task_pre_model_6 cetusMix_Whalefall2(3.85g) OFF
__term_sd_task_pre_model_7 cuteyukimixAdorable_neochapter3(2.3g) OFF
__term_sd_task_pre_model_8 ekmix-pastel(2.13g) OFF
__term_sd_task_pre_model_9 ex2K_sse2(2.38g) OFF
__term_sd_task_pre_model_10 kohakuV5_rev2(2.13g) OFF
__term_sd_task_pre_model_11 meinamix_meinaV11(2.13g) OFF
__term_sd_task_pre_model_12 oukaStar_10(5.43g) OFF
__term_sd_task_pre_model_13 pastelMixStylizedAnime(2.13g) OFF
__term_sd_task_pre_model_14 rabbit_v6(1.97g) OFF
__term_sd_task_pre_model_15 sweetSugarSyndrome_rev15(2.13g) OFF
__term_sd_task_pre_model_16 AnythingV5Ink_ink(2.13g) OFF
__term_sd_task_pre_model_17 bartstyledbBlueArchiveArtStyle(2.13g) OFF
__term_sd_task_pre_model_18 meinapastel_v6(2.13g) OFF
__term_sd_task_pre_model_19 qteamix(2.13g) OFF
__term_sd_task_pre_model_20 tmndMix(2.13g) OFF
__term_sd_task_pre_model_21 =====SD2.1大模型===== OFF
__term_sd_task_pre_model_22 v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_23 wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_24 wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_25 =====SDXL大模型===== OFF
__term_sd_task_pre_model_26 sd_xl_offset_example-lora_1.0(49.6m) OFF
__term_sd_task_pre_model_27 sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_28 sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_29 sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_30 cosxl(6.94g) OFF
__term_sd_task_pre_model_31 cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_32 animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_33 animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_34 animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_35 animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_36 animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_37 animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_38 holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_39 kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_40 clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_41 UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_42 RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_43 sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_44 kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_45 kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_46 kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_47 kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_48 kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_49 starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_50 heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_51 heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_52 baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_53 baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_54 sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_55 sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_56 SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_57 SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_58 Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_59 Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_60 Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_61 Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_62 Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_63 Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_64 jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_65 PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_66 miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_67 waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_68 tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_69 noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_70 noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_71 noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_72 noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_73 noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_74 noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_75 noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_76 noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_77 noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_78 noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_79 noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_80 noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_81 noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_82 PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_83 PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_84 ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_85 pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_86 tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_87 omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_88 animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_89 artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_90 artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_91 AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_92 abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_93 animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_94 bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_95 nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_96 CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_97 =====SD3大模型===== OFF
__term_sd_task_pre_model_98 sd3_medium(4.34g) OFF
__term_sd_task_pre_model_99 sd3_medium_incl_clips(5.97g) OFF
__term_sd_task_pre_model_100 sd3_medium_incl_clips_t5xxlfp8(10.87g) OFF
__term_sd_task_pre_model_101 sd3.5_large(16.5g) OFF
__term_sd_task_pre_model_102 sd3.5_large_fp8_scaled(14.9g) OFF
__term_sd_task_pre_model_103 sd3.5_large_turbo(16.5g) OFF
__term_sd_task_pre_model_104 sd3.5_medium(5.1g) OFF
__term_sd_task_pre_model_105 sd3.5_medium_incl_clips_t5xxlfp8scaled(11.6g) OFF
__term_sd_task_pre_model_106 emi3(16.5g) OFF
__term_sd_task_pre_model_107 =====SD3文本编码器===== OFF
__term_sd_task_pre_model_108 clip_g(1.39g) OFF
__term_sd_task_pre_model_109 clip_l(246.1m) OFF
__term_sd_task_pre_model_110 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_111 t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_112 t5xxl_fp8_e4m3fn_scaled(5.16g) OFF
__term_sd_task_pre_model_113 =====FLUX模型===== OFF
__term_sd_task_pre_model_114 flux1-dev(23.8g) OFF
__term_sd_task_pre_model_115 flux1-dev-fp8(17.2g) OFF
__term_sd_task_pre_model_116 flux_dev_fp8_scaled_diffusion_model(11.9g) OFF
__term_sd_task_pre_model_117 flux1-dev-bnb-nf4-v2(12g) OFF
__term_sd_task_pre_model_118 flux1-dev-bnb-nf4(11.5g) OFF
__term_sd_task_pre_model_119 flux1-dev-Q2_K-gguf(4.03g) OFF
__term_sd_task_pre_model_120 flux1-dev-Q3_K_S-gguf(5.23g) OFF
__term_sd_task_pre_model_121 flux1-dev-Q4_0-gguf(6.79g) OFF
__term_sd_task_pre_model_122 flux1-dev-Q4_1-gguf(7.53g) OFF
__term_sd_task_pre_model_123 flux1-dev-Q4_K_S-gguf(6.81g) OFF
__term_sd_task_pre_model_124 flux1-dev-Q5_0-gguf(8.27g) OFF
__term_sd_task_pre_model_125 flux1-dev-Q5_1-gguf(9.01g) OFF
__term_sd_task_pre_model_126 flux1-dev-Q5_K_S-gguf(8.29g) OFF
__term_sd_task_pre_model_127 flux1-dev-Q6_K-gguf(9.86g) OFF
__term_sd_task_pre_model_128 flux1-dev-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_129 flux1-dev-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_130 flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_131 flux1-schnell-fp8(17.2g) OFF
__term_sd_task_pre_model_132 flux1-schnell-Q2_K-gguf(4.01g) OFF
__term_sd_task_pre_model_133 flux1-schnell-Q3_K_S-gguf(5.21g) OFF
__term_sd_task_pre_model_134 flux1-schnell-Q4_0-gguf(6.77g) OFF
__term_sd_task_pre_model_135 flux1-schnell-Q4_1-gguf(7.51g) OFF
__term_sd_task_pre_model_136 flux1-schnell-Q4_K_S-gguf(6.78g) OFF
__term_sd_task_pre_model_137 flux1-schnell-Q5_0-gguf(8.25g) OFF
__term_sd_task_pre_model_138 flux1-schnell-Q5_1-gguf(8.99g) OFF
__term_sd_task_pre_model_139 flux1-schnell-Q5_K_S-gguf(8.26g) OFF
__term_sd_task_pre_model_140 flux1-schnell-Q6_K-gguf(9.83g) OFF
__term_sd_task_pre_model_141 flux1-schnell-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_142 flux1-schnell-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_143 ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_144 jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_145 nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_146 shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_147 flux1-krea-dev_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_148 flux1-krea-dev(23.8g) OFF
__term_sd_task_pre_model_149 flux1-dev-kontext_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_150 flux1-kontext-dev(23.8g) OFF
__term_sd_task_pre_model_151 chroma-unlocked-v50(23.8g) OFF
__term_sd_task_pre_model_152 =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_153 clip_l(246.1m) OFF
__term_sd_task_pre_model_154 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_155 t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_156 t5-v1_1-xxl-encoder-Q3_K_L-gguf(2.46g) OFF
__term_sd_task_pre_model_157 t5-v1_1-xxl-encoder-Q3_K_M-gguf(2.3g) OFF
__term_sd_task_pre_model_158 t5-v1_1-xxl-encoder-Q3_K_S-gguf(2.1g) OFF
__term_sd_task_pre_model_159 t5-v1_1-xxl-encoder-Q4_K_M-gguf(2.9g) OFF
__term_sd_task_pre_model_160 t5-v1_1-xxl-encoder-Q4_K_S-gguf(2.74g) OFF
__term_sd_task_pre_model_161 t5-v1_1-xxl-encoder-Q5_K_M-gguf(3.39g) OFF
__term_sd_task_pre_model_162 t5-v1_1-xxl-encoder-Q5_K_S-gguf(3.29g) OFF
__term_sd_task_pre_model_163 t5-v1_1-xxl-encoder-Q6_K-gguf(3.91g) OFF
__term_sd_task_pre_model_164 t5-v1_1-xxl-encoder-Q8_0-gguf(5.06g) OFF
__term_sd_task_pre_model_165 t5-v1_1-xxl-encoder-f16-gguf(9.53g) OFF
__term_sd_task_pre_model_166 t5-v1_1-xxl-encoder-f32-gguf(19.1g) OFF
__term_sd_task_pre_model_167 ae(335m) OFF
__term_sd_task_pre_model_168 =====VAE模型===== OFF
__term_sd_task_pre_model_169 vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_170 vae-ft-mse-840000-ema-pruned(334.6m) ON
__term_sd_task_pre_model_171 sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_172 sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_173 =====VAE-approx模型===== OFF
__term_sd_task_pre_model_174 model(0.2m) ON
__term_sd_task_pre_model_175 vaeapprox-sdxl(0.2m) ON
__term_sd_task_pre_model_176 vaeapprox-sd3(0.2m) OFF
__term_sd_task_pre_model_177 =====放大模型===== OFF
__term_sd_task_pre_model_178 codeformer-v0.1.0(376.6m) OFF
__term_sd_task_pre_model_179 DAT_2_x2(139.7m) OFF
__term_sd_task_pre_model_180 DAT_2_x3(140.4m) OFF
__term_sd_task_pre_model_181 DAT_2_x4(140.3m) OFF
__term_sd_task_pre_model_182 DAT_S_x2(87.7m) OFF
__term_sd_task_pre_model_183 DAT_S_x3(88.4m) OFF
__term_sd_task_pre_model_184 DAT_S_x4(88.2m) OFF
__term_sd_task_pre_model_185 DAT_light_x2(45.7m) OFF
__term_sd_task_pre_model_186 DAT_light_x3(45.7m) OFF
__term_sd_task_pre_model_187 DAT_light_x4(45.8m) OFF
__term_sd_task_pre_model_188 DAT_x2(154.1m) OFF
__term_sd_task_pre_model_189 DAT_x3(154.8m) OFF
__term_sd_task_pre_model_190 DAT_x4(154.7m) OFF
__term_sd_task_pre_model_191 16xPSNR(67.2m) OFF
__term_sd_task_pre_model_192 1x-ITF-SkinDiffDetail-Lite-v1(20.1m) OFF
__term_sd_task_pre_model_193 1x_NMKD-BrightenRedux_200k(66.6m) OFF
__term_sd_task_pre_model_194 1x_NMKD-YandereInpaint_375000_G(66.6m) OFF
__term_sd_task_pre_model_195 1x_NMKDDetoon_97500_G(66.6m) OFF
__term_sd_task_pre_model_196 1x_NoiseToner-Poisson-Detailed_108000_G(66.6m) OFF
__term_sd_task_pre_model_197 1x_NoiseToner-Uniform-Detailed_100000_G(66.6m) OFF
__term_sd_task_pre_model_198 4x-UltraSharp(66.9m) OFF
__term_sd_task_pre_model_199 4xPSNR(66.9m) OFF
__term_sd_task_pre_model_200 4x_CountryRoads_377000_G(66.9m) OFF
__term_sd_task_pre_model_201 4x_Fatality_Comix_260000_G(66.9m) OFF
__term_sd_task_pre_model_202 4x_NMKD-Siax_200k(66.9m) OFF
__term_sd_task_pre_model_203 4x_NMKD-Superscale-Artisoftject_210000_G(66.9m) OFF
__term_sd_task_pre_model_204 4x_NMKD-Superscale-SP_178000_G(66.9m) ON
__term_sd_task_pre_model_205 4x_NMKD-UltraYandere-Lite_280k(20.1m) OFF
__term_sd_task_pre_model_206 4x_NMKD-UltraYandere_300k(66.9m) OFF
__term_sd_task_pre_model_207 4x_NMKD-YandereNeoXL_200k(66.9m) OFF
__term_sd_task_pre_model_208 4x_NMKDSuperscale_Artisoft_120000_G(67.1m) OFF
__term_sd_task_pre_model_209 4x_NickelbackFS_72000_G(67.1m) OFF
__term_sd_task_pre_model_210 4x_Nickelback_70000G(66.9m) OFF
__term_sd_task_pre_model_211 4x_RealisticRescaler_100000_G(134.1m) OFF
__term_sd_task_pre_model_212 4x_Valar_v1(67.5m) OFF
__term_sd_task_pre_model_213 4x_fatal_Anime_500000_G(66.9m) OFF
__term_sd_task_pre_model_214 4x_foolhardy_Remacri(67m) OFF
__term_sd_task_pre_model_215 8xPSNR(67.1m) OFF
__term_sd_task_pre_model_216 8x_NMKD-Superscale_150000_G(67.1m) OFF
__term_sd_task_pre_model_217 8x_NMKD-Typescale_175k(67.1m) OFF
__term_sd_task_pre_model_218 A_ESRGAN_Single(134.1m) OFF
__term_sd_task_pre_model_219 BSRGAN(67.1m) OFF
__term_sd_task_pre_model_220 BSRGANx2(66.8m) OFF
__term_sd_task_pre_model_221 BSRNet(67.1m) OFF
__term_sd_task_pre_model_222 ESRGAN_4x(66.9m) OFF
__term_sd_task_pre_model_223 LADDIER1_282500_G(66.9m) OFF
__term_sd_task_pre_model_224 4x_UniversalUpscalerV2-Neutral_115000_swaG(66.9m) OFF
__term_sd_task_pre_model_225 4x_UniversalUpscalerV2-Sharp_101000_G(66.9m) OFF
__term_sd_task_pre_model_226 4x_UniversalUpscalerV2-Sharper_103000_G(66.9m) OFF
__term_sd_task_pre_model_227 4x_UniversalUpscaler-Detailed_155000_G(66.9m) OFF
__term_sd_task_pre_model_228 4x_UniversalUpscaler-Soft_190000_G(66.9m) OFF
__term_sd_task_pre_model_229 WaifuGAN_v3_30000(66.9m) OFF
__term_sd_task_pre_model_230 lollypop(66.9m) OFF
__term_sd_task_pre_model_231 sudo_rife4_269.662_testV1_scale1(33.7m) OFF
__term_sd_task_pre_model_232 GFPGANv1.3(348.6m) OFF
__term_sd_task_pre_model_233 GFPGANv1.4(348.6m) OFF
__term_sd_task_pre_model_234 detection_Resnet50_Final(109.5m) OFF
__term_sd_task_pre_model_235 parsing_bisenet(12.2m) OFF
__term_sd_task_pre_model_236 parsing_parsenet(85.3m) OFF
__term_sd_task_pre_model_237 RealESRGAN_x4plus(67m) ON
__term_sd_task_pre_model_238 RealESRGAN_x4plus_anime_6B(17.9m) ON
__term_sd_task_pre_model_239 001_classicalSR_DF2K_s64w8_SwinIR-M_x2(67.2m) OFF
__term_sd_task_pre_model_240 001_classicalSR_DF2K_s64w8_SwinIR-M_x3(68m) OFF
__term_sd_task_pre_model_241 001_classicalSR_DF2K_s64w8_SwinIR-M_x4(67.8m) OFF
__term_sd_task_pre_model_242 001_classicalSR_DF2K_s64w8_SwinIR-M_x8(68.4m) OFF
__term_sd_task_pre_model_243 001_classicalSR_DIV2K_s48w8_SwinIR-M_x2(59m) OFF
__term_sd_task_pre_model_244 001_classicalSR_DIV2K_s48w8_SwinIR-M_x3(59.7m) OFF
__term_sd_task_pre_model_245 001_classicalSR_DIV2K_s48w8_SwinIR-M_x4(59.6m) OFF
__term_sd_task_pre_model_246 001_classicalSR_DIV2K_s48w8_SwinIR-M_x8(60.2m) OFF
__term_sd_task_pre_model_247 Swin2SR_ClassicalSR_X2_64(68.7m) OFF
__term_sd_task_pre_model_248 Swin2SR_ClassicalSR_X4_64(69.3m) OFF
__term_sd_task_pre_model_249 Swin2SR_CompressedSR_X4_48(61.1m) OFF
__term_sd_task_pre_model_250 Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR(68.6m) OFF
__term_sd_task_pre_model_251 SwinIR_4x(142.4m) OFF
__term_sd_task_pre_model_252 =====图生图反推Tag模型===== OFF
__term_sd_task_pre_model_253 model_base_caption_capfilt_large(896m) OFF
__term_sd_task_pre_model_254 model-resnet_custom_v3(644.1m) OFF
__term_sd_task_pre_model_255 =====Embedding模型===== OFF
__term_sd_task_pre_model_256 EasyNegativeV2(0.1m) ON
__term_sd_task_pre_model_257 bad-artist-anime(0.1m) ON
__term_sd_task_pre_model_258 bad-artist(0.1m) ON
__term_sd_task_pre_model_259 bad-hands-5(0.1m) ON
__term_sd_task_pre_model_260 bad-image-v2-39000(0.1m) ON
__term_sd_task_pre_model_261 bad_prompt_version2(0.1m) ON
__term_sd_task_pre_model_262 ng_deepnegative_v1_75t(0.1m) ON
__term_sd_task_pre_model_263 verybadimagenegative_v1.3(0.1m) ON
|
2301_81996401/term-sd
|
install/sd_webui/dialog_sd_webui_hf_model.sh
|
Shell
|
agpl-3.0
| 16,140
|
__term_sd_task_pre_model_1 =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 nai1-artist_all_in_one_merge(2.13g) OFF
__term_sd_task_pre_model_5 Counterfeit-V3.0(4.24g) OFF
__term_sd_task_pre_model_6 cetusMix_Whalefall2(3.85g) OFF
__term_sd_task_pre_model_7 cuteyukimixAdorable_neochapter3(2.3g) OFF
__term_sd_task_pre_model_8 ekmix-pastel(2.13g) OFF
__term_sd_task_pre_model_9 ex2K_sse2(2.38g) OFF
__term_sd_task_pre_model_10 kohakuV5_rev2(2.13g) OFF
__term_sd_task_pre_model_11 meinamix_meinaV11(2.13g) OFF
__term_sd_task_pre_model_12 oukaStar_10(5.43g) OFF
__term_sd_task_pre_model_13 pastelMixStylizedAnime(2.13g) OFF
__term_sd_task_pre_model_14 rabbit_v6(1.97g) OFF
__term_sd_task_pre_model_15 sweetSugarSyndrome_rev15(2.13g) OFF
__term_sd_task_pre_model_16 AnythingV5Ink_ink(2.13g) OFF
__term_sd_task_pre_model_17 bartstyledbBlueArchiveArtStyle(2.13g) OFF
__term_sd_task_pre_model_18 meinapastel_v6(2.13g) OFF
__term_sd_task_pre_model_19 qteamix(2.13g) OFF
__term_sd_task_pre_model_20 tmndMix(2.13g) OFF
__term_sd_task_pre_model_21 =====SD2.1大模型===== OFF
__term_sd_task_pre_model_22 v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_23 wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_24 wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_25 =====SDXL大模型===== OFF
__term_sd_task_pre_model_26 sd_xl_offset_example-lora_1.0(49.6m) OFF
__term_sd_task_pre_model_27 sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_28 sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_29 sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_30 cosxl(6.94g) OFF
__term_sd_task_pre_model_31 cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_32 animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_33 animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_34 animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_35 animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_36 animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_37 animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_38 holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_39 kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_40 clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_41 UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_42 RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_43 sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_44 kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_45 kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_46 kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_47 kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_48 kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_49 starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_50 heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_51 heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_52 baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_53 baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_54 sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_55 sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_56 SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_57 SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_58 Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_59 Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_60 Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_61 Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_62 Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_63 Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_64 jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_65 PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_66 miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_67 waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_68 tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_69 noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_70 noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_71 noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_72 noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_73 noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_74 noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_75 noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_76 noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_77 noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_78 noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_79 noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_80 noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_81 noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_82 PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_83 PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_84 ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_85 pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_86 tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_87 omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_88 animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_89 artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_90 artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_91 AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_92 abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_93 animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_94 bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_95 nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_96 CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_97 =====SD3大模型===== OFF
__term_sd_task_pre_model_98 sd3_medium(4.34g) OFF
__term_sd_task_pre_model_99 sd3_medium_incl_clips(5.97g) OFF
__term_sd_task_pre_model_100 sd3_medium_incl_clips_t5xxlfp8(10.87g) OFF
__term_sd_task_pre_model_101 sd3.5_large(16.5g) OFF
__term_sd_task_pre_model_102 sd3.5_large_fp8_scaled(14.9g) OFF
__term_sd_task_pre_model_103 sd3.5_large_turbo(16.5g) OFF
__term_sd_task_pre_model_104 sd3.5_medium(5.1g) OFF
__term_sd_task_pre_model_105 sd3.5_medium_incl_clips_t5xxlfp8scaled(11.6g) OFF
__term_sd_task_pre_model_106 emi3(16.5g) OFF
__term_sd_task_pre_model_107 =====SD3文本编码器===== OFF
__term_sd_task_pre_model_108 clip_g(1.39g) OFF
__term_sd_task_pre_model_109 clip_l(246.1m) OFF
__term_sd_task_pre_model_110 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_111 t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_112 t5xxl_fp8_e4m3fn_scaled(5.16g) OFF
__term_sd_task_pre_model_113 =====FLUX模型===== OFF
__term_sd_task_pre_model_114 flux1-dev(23.8g) OFF
__term_sd_task_pre_model_115 flux1-dev-fp8(17.2g) OFF
__term_sd_task_pre_model_116 flux_dev_fp8_scaled_diffusion_model(11.9g) OFF
__term_sd_task_pre_model_117 flux1-dev-bnb-nf4-v2(12g) OFF
__term_sd_task_pre_model_118 flux1-dev-bnb-nf4(11.5g) OFF
__term_sd_task_pre_model_119 flux1-dev-Q2_K-gguf(4.03g) OFF
__term_sd_task_pre_model_120 flux1-dev-Q3_K_S-gguf(5.23g) OFF
__term_sd_task_pre_model_121 flux1-dev-Q4_0-gguf(6.79g) OFF
__term_sd_task_pre_model_122 flux1-dev-Q4_1-gguf(7.53g) OFF
__term_sd_task_pre_model_123 flux1-dev-Q4_K_S-gguf(6.81g) OFF
__term_sd_task_pre_model_124 flux1-dev-Q5_0-gguf(8.27g) OFF
__term_sd_task_pre_model_125 flux1-dev-Q5_1-gguf(9.01g) OFF
__term_sd_task_pre_model_126 flux1-dev-Q5_K_S-gguf(8.29g) OFF
__term_sd_task_pre_model_127 flux1-dev-Q6_K-gguf(9.86g) OFF
__term_sd_task_pre_model_128 flux1-dev-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_129 flux1-dev-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_130 flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_131 flux1-schnell-fp8(17.2g) OFF
__term_sd_task_pre_model_132 flux1-schnell-Q2_K-gguf(4.01g) OFF
__term_sd_task_pre_model_133 flux1-schnell-Q3_K_S-gguf(5.21g) OFF
__term_sd_task_pre_model_134 flux1-schnell-Q4_0-gguf(6.77g) OFF
__term_sd_task_pre_model_135 flux1-schnell-Q4_1-gguf(7.51g) OFF
__term_sd_task_pre_model_136 flux1-schnell-Q4_K_S-gguf(6.78g) OFF
__term_sd_task_pre_model_137 flux1-schnell-Q5_0-gguf(8.25g) OFF
__term_sd_task_pre_model_138 flux1-schnell-Q5_1-gguf(8.99g) OFF
__term_sd_task_pre_model_139 flux1-schnell-Q5_K_S-gguf(8.26g) OFF
__term_sd_task_pre_model_140 flux1-schnell-Q6_K-gguf(9.83g) OFF
__term_sd_task_pre_model_141 flux1-schnell-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_142 flux1-schnell-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_143 ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_144 jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_145 nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_146 shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_147 flux1-krea-dev_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_148 flux1-krea-dev(23.8g) OFF
__term_sd_task_pre_model_149 flux1-dev-kontext_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_150 flux1-kontext-dev(23.8g) OFF
__term_sd_task_pre_model_151 chroma-unlocked-v50(23.8g) OFF
__term_sd_task_pre_model_152 =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_153 clip_l(246.1m) OFF
__term_sd_task_pre_model_154 t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_155 t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_156 t5-v1_1-xxl-encoder-Q3_K_L-gguf(2.46g) OFF
__term_sd_task_pre_model_157 t5-v1_1-xxl-encoder-Q3_K_M-gguf(2.3g) OFF
__term_sd_task_pre_model_158 t5-v1_1-xxl-encoder-Q3_K_S-gguf(2.1g) OFF
__term_sd_task_pre_model_159 t5-v1_1-xxl-encoder-Q4_K_M-gguf(2.9g) OFF
__term_sd_task_pre_model_160 t5-v1_1-xxl-encoder-Q4_K_S-gguf(2.74g) OFF
__term_sd_task_pre_model_161 t5-v1_1-xxl-encoder-Q5_K_M-gguf(3.39g) OFF
__term_sd_task_pre_model_162 t5-v1_1-xxl-encoder-Q5_K_S-gguf(3.29g) OFF
__term_sd_task_pre_model_163 t5-v1_1-xxl-encoder-Q6_K-gguf(3.91g) OFF
__term_sd_task_pre_model_164 t5-v1_1-xxl-encoder-Q8_0-gguf(5.06g) OFF
__term_sd_task_pre_model_165 t5-v1_1-xxl-encoder-f16-gguf(9.53g) OFF
__term_sd_task_pre_model_166 t5-v1_1-xxl-encoder-f32-gguf(19.1g) OFF
__term_sd_task_pre_model_167 ae(335m) OFF
__term_sd_task_pre_model_168 =====VAE模型===== OFF
__term_sd_task_pre_model_169 vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_170 vae-ft-mse-840000-ema-pruned(334.6m) ON
__term_sd_task_pre_model_171 sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_172 sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_173 =====VAE-approx模型===== OFF
__term_sd_task_pre_model_174 model(0.2m) ON
__term_sd_task_pre_model_175 vaeapprox-sdxl(0.2m) ON
__term_sd_task_pre_model_176 vaeapprox-sd3(0.2m) OFF
__term_sd_task_pre_model_177 =====放大模型===== OFF
__term_sd_task_pre_model_178 codeformer-v0.1.0(376.6m) OFF
__term_sd_task_pre_model_179 DAT_2_x2(139.7m) OFF
__term_sd_task_pre_model_180 DAT_2_x3(140.4m) OFF
__term_sd_task_pre_model_181 DAT_2_x4(140.3m) OFF
__term_sd_task_pre_model_182 DAT_S_x2(87.7m) OFF
__term_sd_task_pre_model_183 DAT_S_x3(88.4m) OFF
__term_sd_task_pre_model_184 DAT_S_x4(88.2m) OFF
__term_sd_task_pre_model_185 DAT_light_x2(45.7m) OFF
__term_sd_task_pre_model_186 DAT_light_x3(45.7m) OFF
__term_sd_task_pre_model_187 DAT_light_x4(45.8m) OFF
__term_sd_task_pre_model_188 DAT_x2(154.1m) OFF
__term_sd_task_pre_model_189 DAT_x3(154.8m) OFF
__term_sd_task_pre_model_190 DAT_x4(154.7m) OFF
__term_sd_task_pre_model_191 16xPSNR(67.2m) OFF
__term_sd_task_pre_model_192 1x-ITF-SkinDiffDetail-Lite-v1(20.1m) OFF
__term_sd_task_pre_model_193 1x_NMKD-BrightenRedux_200k(66.6m) OFF
__term_sd_task_pre_model_194 1x_NMKD-YandereInpaint_375000_G(66.6m) OFF
__term_sd_task_pre_model_195 1x_NMKDDetoon_97500_G(66.6m) OFF
__term_sd_task_pre_model_196 1x_NoiseToner-Poisson-Detailed_108000_G(66.6m) OFF
__term_sd_task_pre_model_197 1x_NoiseToner-Uniform-Detailed_100000_G(66.6m) OFF
__term_sd_task_pre_model_198 4x-UltraSharp(66.9m) OFF
__term_sd_task_pre_model_199 4xPSNR(66.9m) OFF
__term_sd_task_pre_model_200 4x_CountryRoads_377000_G(66.9m) OFF
__term_sd_task_pre_model_201 4x_Fatality_Comix_260000_G(66.9m) OFF
__term_sd_task_pre_model_202 4x_NMKD-Siax_200k(66.9m) OFF
__term_sd_task_pre_model_203 4x_NMKD-Superscale-Artisoftject_210000_G(66.9m) OFF
__term_sd_task_pre_model_204 4x_NMKD-Superscale-SP_178000_G(66.9m) ON
__term_sd_task_pre_model_205 4x_NMKD-UltraYandere-Lite_280k(20.1m) OFF
__term_sd_task_pre_model_206 4x_NMKD-UltraYandere_300k(66.9m) OFF
__term_sd_task_pre_model_207 4x_NMKD-YandereNeoXL_200k(66.9m) OFF
__term_sd_task_pre_model_208 4x_NMKDSuperscale_Artisoft_120000_G(67.1m) OFF
__term_sd_task_pre_model_209 4x_NickelbackFS_72000_G(67.1m) OFF
__term_sd_task_pre_model_210 4x_Nickelback_70000G(66.9m) OFF
__term_sd_task_pre_model_211 4x_RealisticRescaler_100000_G(134.1m) OFF
__term_sd_task_pre_model_212 4x_Valar_v1(67.5m) OFF
__term_sd_task_pre_model_213 4x_fatal_Anime_500000_G(66.9m) OFF
__term_sd_task_pre_model_214 4x_foolhardy_Remacri(67m) OFF
__term_sd_task_pre_model_215 8xPSNR(67.1m) OFF
__term_sd_task_pre_model_216 8x_NMKD-Superscale_150000_G(67.1m) OFF
__term_sd_task_pre_model_217 8x_NMKD-Typescale_175k(67.1m) OFF
__term_sd_task_pre_model_218 A_ESRGAN_Single(134.1m) OFF
__term_sd_task_pre_model_219 BSRGAN(67.1m) OFF
__term_sd_task_pre_model_220 BSRGANx2(66.8m) OFF
__term_sd_task_pre_model_221 BSRNet(67.1m) OFF
__term_sd_task_pre_model_222 ESRGAN_4x(66.9m) OFF
__term_sd_task_pre_model_223 LADDIER1_282500_G(66.9m) OFF
__term_sd_task_pre_model_224 4x_UniversalUpscalerV2-Neutral_115000_swaG(66.9m) OFF
__term_sd_task_pre_model_225 4x_UniversalUpscalerV2-Sharp_101000_G(66.9m) OFF
__term_sd_task_pre_model_226 4x_UniversalUpscalerV2-Sharper_103000_G(66.9m) OFF
__term_sd_task_pre_model_227 4x_UniversalUpscaler-Detailed_155000_G(66.9m) OFF
__term_sd_task_pre_model_228 4x_UniversalUpscaler-Soft_190000_G(66.9m) OFF
__term_sd_task_pre_model_229 WaifuGAN_v3_30000(66.9m) OFF
__term_sd_task_pre_model_230 lollypop(66.9m) OFF
__term_sd_task_pre_model_231 sudo_rife4_269.662_testV1_scale1(33.7m) OFF
__term_sd_task_pre_model_232 GFPGANv1.3(348.6m) OFF
__term_sd_task_pre_model_233 GFPGANv1.4(348.6m) OFF
__term_sd_task_pre_model_234 detection_Resnet50_Final(109.5m) OFF
__term_sd_task_pre_model_235 parsing_bisenet(12.2m) OFF
__term_sd_task_pre_model_236 parsing_parsenet(85.3m) OFF
__term_sd_task_pre_model_237 RealESRGAN_x4plus(67m) ON
__term_sd_task_pre_model_238 RealESRGAN_x4plus_anime_6B(17.9m) ON
__term_sd_task_pre_model_239 001_classicalSR_DF2K_s64w8_SwinIR-M_x2(67.2m) OFF
__term_sd_task_pre_model_240 001_classicalSR_DF2K_s64w8_SwinIR-M_x3(68m) OFF
__term_sd_task_pre_model_241 001_classicalSR_DF2K_s64w8_SwinIR-M_x4(67.8m) OFF
__term_sd_task_pre_model_242 001_classicalSR_DF2K_s64w8_SwinIR-M_x8(68.4m) OFF
__term_sd_task_pre_model_243 001_classicalSR_DIV2K_s48w8_SwinIR-M_x2(59m) OFF
__term_sd_task_pre_model_244 001_classicalSR_DIV2K_s48w8_SwinIR-M_x3(59.7m) OFF
__term_sd_task_pre_model_245 001_classicalSR_DIV2K_s48w8_SwinIR-M_x4(59.6m) OFF
__term_sd_task_pre_model_246 001_classicalSR_DIV2K_s48w8_SwinIR-M_x8(60.2m) OFF
__term_sd_task_pre_model_247 Swin2SR_ClassicalSR_X2_64(68.7m) OFF
__term_sd_task_pre_model_248 Swin2SR_ClassicalSR_X4_64(69.3m) OFF
__term_sd_task_pre_model_249 Swin2SR_CompressedSR_X4_48(61.1m) OFF
__term_sd_task_pre_model_250 Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR(68.6m) OFF
__term_sd_task_pre_model_251 SwinIR_4x(142.4m) OFF
__term_sd_task_pre_model_252 =====图生图反推Tag模型===== OFF
__term_sd_task_pre_model_253 model_base_caption_capfilt_large(896m) OFF
__term_sd_task_pre_model_254 model-resnet_custom_v3(644.1m) OFF
__term_sd_task_pre_model_255 =====Embedding模型===== OFF
__term_sd_task_pre_model_256 EasyNegativeV2(0.1m) ON
__term_sd_task_pre_model_257 bad-artist-anime(0.1m) ON
__term_sd_task_pre_model_258 bad-artist(0.1m) ON
__term_sd_task_pre_model_259 bad-hands-5(0.1m) ON
__term_sd_task_pre_model_260 bad-image-v2-39000(0.1m) ON
__term_sd_task_pre_model_261 bad_prompt_version2(0.1m) ON
__term_sd_task_pre_model_262 ng_deepnegative_v1_75t(0.1m) ON
__term_sd_task_pre_model_263 verybadimagenegative_v1.3(0.1m) ON
|
2301_81996401/term-sd
|
install/sd_webui/dialog_sd_webui_ms_model.sh
|
Shell
|
agpl-3.0
| 16,140
|
__term_sd_task_sys term_sd_mkdir "${SD_WEBUI_PARENT_PATH}"
__term_sd_task_sys cd "${SD_WEBUI_PARENT_PATH}"
__term_sd_task_sys term_sd_tmp_enable_proxy
__term_sd_task_pre_core git_clone_repository "${SD_WEBUI_REPO}" "${SD_WEBUI_PARENT_PATH}" "${SD_WEBUI_FOLDER}"
__term_sd_task_sys is_sd_repo_exist "${SD_WEBUI_ROOT_PATH}"
__term_sd_task_pre_core switch_sd_webui_branch "${SD_WEBUI_BRANCH}"
__term_sd_task_pre_core create_venv "${SD_WEBUI_ROOT_PATH}"
__term_sd_task_sys enter_venv "${SD_WEBUI_ROOT_PATH}"
__term_sd_task_pre_core install_sd_webui_component
__term_sd_task_sys term_sd_tmp_disable_proxy # 临时取消代理, 避免一些不必要的网络减速
__term_sd_task_pre_core install_pytorch # 安装 PyTorch
__term_sd_task_sys term_sd_tmp_enable_proxy
__term_sd_task_pre_core install_python_package git+$(git_format_repository_url ${GITHUB_MIRROR} https://github.com/openai/CLIP)
__term_sd_task_sys term_sd_tmp_disable_proxy # 临时取消代理, 避免一些不必要的网络减速
__term_sd_task_pre_core install_sd_webui_requirement
__term_sd_task_pre_core term_sd_echo "生成配置中"
__term_sd_task_pre_core set_sd_webui_normal_config
|
2301_81996401/term-sd
|
install/sd_webui/sd_webui_core.sh
|
Shell
|
agpl-3.0
| 1,151
|
__term_sd_task_pre_ext_1 git_clone_repository https://github.com/Mikubill/sd-webui-controlnet "${SD_WEBUI_ROOT_PATH}"/extensions ON # 图片生成控制
__term_sd_task_pre_ext_2 git_clone_repository https://github.com/continue-revolution/sd-webui-animatediff "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 视频生成扩展
__term_sd_task_pre_ext_3 git_clone_repository https://github.com/Bing-su/adetailer "${SD_WEBUI_ROOT_PATH}"/extensions ON # 图片细节修复扩展
__term_sd_task_pre_ext_4 git_clone_repository https://github.com/ClockZinc/sd-webui-IS-NET-pro "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 人物抠图
__term_sd_task_pre_ext_5 git_clone_repository https://github.com/continue-revolution/sd-webui-segment-anything "${SD_WEBUI_ROOT_PATH}"/extensions ON # 图片语义分割
__term_sd_task_pre_ext_6 git_clone_repository https://github.com/Uminosachi/sd-webui-inpaint-anything "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使用seg生成的蒙版进行图像重绘
__term_sd_task_pre_ext_7 git_clone_repository https://github.com/lllyasviel/sd-forge-layerdiffuse "${SD_WEBUI_ROOT_PATH}"/extensions OFF # LayerDiffusion插件，仅支持sd-webui-forge
__term_sd_task_pre_ext_8 git_clone_repository https://github.com/KohakuBlueleaf/z-a1111-sd-webui-dtg "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使用Danboou风格对tag进行润色，使出图效果更好，内容更丰富
__term_sd_task_pre_ext_9 git_clone_repository https://github.com/pkuliyi2015/sd-webui-stablesr "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图片放大
__term_sd_task_pre_ext_10 git_clone_repository https://github.com/KohakuBlueleaf/z-tipo-extension "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使用danbooru-tag和自然语言对提示词进行润色，增强模型的出图效果
__term_sd_task_pre_ext_11 git_clone_repository https://github.com/WSH032/kohya-config-webui "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 一个用于生成kohya-ss训练脚本使用的toml配置文件的WebUI
__term_sd_task_pre_ext_12 git_clone_repository https://github.com/kohya-ss/sd-webui-additional-networks "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 将LoRA等模型添加到stablediffusion以生成图像的扩展
__term_sd_task_pre_ext_13 git_clone_repository https://github.com/DominikDoom/a1111-sd-webui-tagcomplete "${SD_WEBUI_ROOT_PATH}"/extensions ON # 输入Tag时提供booru风格（如Danbooru）的TAG自动补全
__term_sd_task_pre_ext_14 git_clone_repository https://github.com/pkuliyi2015/multidiffusion-upscaler-for-automatic1111 "${SD_WEBUI_ROOT_PATH}"/extensions ON # 在有限的显存中进行大型图像绘制，提供图片区域控制
__term_sd_task_pre_ext_15 git_clone_repository https://github.com/mcmonkeyprojects/sd-dynamic-thresholding "${SD_WEBUI_ROOT_PATH}"/extensions ON # 解决使用更高的CFGScale而出现颜色问题
__term_sd_task_pre_ext_16 git_clone_repository https://github.com/hnmr293/sd-webui-cutoff "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 解决tag污染
__term_sd_task_pre_ext_17 git_clone_repository https://github.com/Akegarasu/sd-webui-model-converter "${SD_WEBUI_ROOT_PATH}"/extensions ON # 模型转换扩展
__term_sd_task_pre_ext_18 git_clone_repository https://github.com/hako-mikan/sd-webui-supermerger "${SD_WEBUI_ROOT_PATH}"/extensions ON # 模型融合扩展
__term_sd_task_pre_ext_19 git_clone_repository https://github.com/hanamizuki-ai/stable-diffusion-webui-localization-zh_Hans "${SD_WEBUI_ROOT_PATH}"/extensions ON # WEBUI中文扩展
__term_sd_task_pre_ext_20 git_clone_repository https://github.com/licyk/sd-webui-wd14-tagger "${SD_WEBUI_ROOT_PATH}"/extensions ON # 图片tag反推
__term_sd_task_pre_ext_21 git_clone_repository https://github.com/hako-mikan/sd-webui-regional-prompter "${SD_WEBUI_ROOT_PATH}"/extensions ON # 图片区域分割
__term_sd_task_pre_ext_22 git_clone_repository https://github.com/zanllp/sd-webui-infinite-image-browsing "${SD_WEBUI_ROOT_PATH}"/extensions ON # 强大的图像管理器
__term_sd_task_pre_ext_23 git_clone_repository https://github.com/klimaleksus/stable-diffusion-webui-anti-burn "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 通过跳过最后几个步骤并将它们之前的一些图像平均在一起来平滑生成的图像，加快点击停止生成图像后WEBUI的响应速度
__term_sd_task_pre_ext_24 git_clone_repository https://github.com/Elldreth/loopback_scaler "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使用迭代过程增强图像分辨率和质量
__term_sd_task_pre_ext_25 git_clone_repository https://github.com/CodeZombie/latentcoupleregionmapper "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 控制绘制和定义区域
__term_sd_task_pre_ext_26 git_clone_repository https://github.com/Coyote-A/ultimate-upscale-for-automatic1111 "${SD_WEBUI_ROOT_PATH}"/extensions ON # 图片放大工具
__term_sd_task_pre_ext_27 git_clone_repository https://github.com/deforum-art/deforum-for-automatic1111-webui "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 视频生成插件
__term_sd_task_pre_ext_28 git_clone_repository https://github.com/AlUlkesh/stable-diffusion-webui-images-browser "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图像管理器
__term_sd_task_pre_ext_29 git_clone_repository https://github.com/camenduru/stable-diffusion-webui-huggingface "${SD_WEBUI_ROOT_PATH}"/extensions OFF # huggingface模型下载扩展
__term_sd_task_pre_ext_30 git_clone_repository https://github.com/camenduru/sd-civitai-browser "${SD_WEBUI_ROOT_PATH}"/extensions OFF # civitai模型下载扩展
__term_sd_task_pre_ext_31 git_clone_repository https://github.com/space-nuko/a1111-stable-diffusion-webui-vram-estimator "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 显存占用评估
__term_sd_task_pre_ext_32 git_clone_repository https://github.com/fkunn1326/openpose-editor "${SD_WEBUI_ROOT_PATH}"/extensions OFF # openpose姿势编辑
__term_sd_task_pre_ext_33 git_clone_repository https://github.com/jexom/sd-webui-depth-lib "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 深度图库，用于Automatic1111/stable-diffusion-webui的controlnet扩展
__term_sd_task_pre_ext_34 git_clone_repository https://github.com/hnmr293/posex "${SD_WEBUI_ROOT_PATH}"/extensions OFF # openpose姿势编辑
__term_sd_task_pre_ext_35 git_clone_repository https://github.com/camenduru/sd-webui-tunnels "${SD_WEBUI_ROOT_PATH}"/extensions OFF # WEBUI端口映射扩展
__term_sd_task_pre_ext_36 git_clone_repository https://github.com/etherealxx/batchlinks-webui "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 批处理链接下载器
__term_sd_task_pre_ext_37 git_clone_repository https://github.com/camenduru/stable-diffusion-webui-catppuccin "${SD_WEBUI_ROOT_PATH}"/extensions OFF # WEBUI主题
__term_sd_task_pre_ext_38 git_clone_repository https://github.com/KohakuBlueleaf/a1111-sd-webui-lycoris "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加lycoris模型支持
__term_sd_task_pre_ext_39 git_clone_repository https://github.com/AUTOMATIC1111/stable-diffusion-webui-rembg "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 人物背景去除
__term_sd_task_pre_ext_40 git_clone_repository https://github.com/ashen-sensored/stable-diffusion-webui-two-shot "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图片区域分割和控制
__term_sd_task_pre_ext_41 git_clone_repository https://github.com/hako-mikan/sd-webui-lora-block-weight "${SD_WEBUI_ROOT_PATH}"/extensions ON # lora分层扩展
__term_sd_task_pre_ext_42 git_clone_repository https://github.com/ototadana/sd-face-editor "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 面部编辑器
__term_sd_task_pre_ext_43 git_clone_repository https://github.com/Physton/sd-webui-prompt-all-in-one "${SD_WEBUI_ROOT_PATH}"/extensions ON # tag翻译和管理插件
__term_sd_task_pre_ext_44 git_clone_repository https://github.com/ModelSurge/sd-webui-comfyui "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 在WEBUI添加ComfyUI界面
__term_sd_task_pre_ext_45 git_clone_repository https://github.com/yankooliveira/sd-webui-photopea-embed "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 在WEBUI界面添加ps功能
__term_sd_task_pre_ext_46 git_clone_repository https://github.com/huchenlei/sd-webui-openpose-editor "${SD_WEBUI_ROOT_PATH}"/extensions ON # ControlNet的pose编辑器
__term_sd_task_pre_ext_47 git_clone_repository https://github.com/hnmr293/sd-webui-llul "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 给图片的选定区域增加细节
__term_sd_task_pre_ext_48 git_clone_repository https://github.com/journey-ad/sd-webui-bilingual-localization "${SD_WEBUI_ROOT_PATH}"/extensions OFF # WEBUI双语对照翻译插件
__term_sd_task_pre_ext_49 git_clone_repository https://github.com/Scholar01/sd-webui-mov2mov "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 视频逐帧处理插件
__term_sd_task_pre_ext_50 git_clone_repository https://github.com/s9roll7/ebsynth_utility "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 视频处理扩展
__term_sd_task_pre_ext_51 git_clone_repository https://github.com/d8ahazard/sd_dreambooth_extension "${SD_WEBUI_ROOT_PATH}"/extensions OFF # dreambooth模型训练
__term_sd_task_pre_ext_52 git_clone_repository https://github.com/Haoming02/sd-webui-memory-release "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 显存释放扩展
__term_sd_task_pre_ext_53 git_clone_repository https://github.com/toshiaki1729/stable-diffusion-webui-dataset-tag-editor "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 训练集打标和处理扩展
__term_sd_task_pre_ext_54 git_clone_repository https://github.com/SpenserCai/sd-webui-deoldify "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 黑白图片上色
__term_sd_task_pre_ext_55 git_clone_repository https://github.com/arenasys/stable-diffusion-webui-model-toolkit "${SD_WEBUI_ROOT_PATH}"/extensions ON # 大模型数据查看
__term_sd_task_pre_ext_56 git_clone_repository https://github.com/Bobo-1125/sd-webui-oldsix-prompt-dynamic "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 动态提示词
__term_sd_task_pre_ext_57 git_clone_repository https://github.com/Artiprocher/sd-webui-fastblend "${SD_WEBUI_ROOT_PATH}"/extensions OFF # ai视频平滑
__term_sd_task_pre_ext_58 git_clone_repository https://github.com/ahgsql/StyleSelectorXL "${SD_WEBUI_ROOT_PATH}"/extensions OFF # SDXL模型画风选择
__term_sd_task_pre_ext_59 git_clone_repository https://github.com/adieyal/sd-dynamic-prompts "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 动态提示词
__term_sd_task_pre_ext_60 git_clone_repository https://github.com/Tencent/LightDiffusionFlow "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 保存工作流
__term_sd_task_pre_ext_61 git_clone_repository https://github.com/Scholar01/sd-webui-workspace "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 保存webui生图的参数
__term_sd_task_pre_ext_62 git_clone_repository https://github.com/zero01101/openOutpaint-webUI-extension "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 提供类似InvokeAI的统一画布的功能
__term_sd_task_pre_ext_63 git_clone_repository https://github.com/Carzit/sd-webui-samplers-scheduler "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 采样器调度器，可以在不同的生成步骤中应用不同的采样器
__term_sd_task_pre_ext_64 git_clone_repository https://github.com/Haoming02/sd-webui-boomer "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 恢复新版webui已经移除的按钮
__term_sd_task_pre_ext_65 git_clone_repository https://github.com/mix1009/model-keyword "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 用于补全模型对应的提示词，比如使用lora模型的提示词
__term_sd_task_pre_ext_66 git_clone_repository https://github.com/NVIDIA/Stable-Diffusion-WebUI-TensorRT "${SD_WEBUI_ROOT_PATH}"/extensions OFF # nvidia官方加速工具，加速图片生成
__term_sd_task_pre_ext_67 git_clone_repository https://github.com/lobehub/sd-webui-lobe-theme "${SD_WEBUI_ROOT_PATH}"/extensions OFF # webui主题
__term_sd_task_pre_ext_68 git_clone_repository https://github.com/w-e-w/stable-diffusion-webui-GPU-temperature-protection "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 显卡过热保护
__term_sd_task_pre_ext_69 git_clone_repository https://github.com/huchenlei/sd-webui-api-payload-display "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 生图完成后展示api参数
__term_sd_task_pre_ext_70 git_clone_repository https://github.com/thomasasfk/sd-webui-aspect-ratio-helper "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图片尺寸比例固定
__term_sd_task_pre_ext_71 git_clone_repository https://github.com/hako-mikan/sd-webui-cd-tuner "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 修改输出图像中的细节和色调的数量
__term_sd_task_pre_ext_72 git_clone_repository https://github.com/hako-mikan/sd-webui-negpip "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 解决tag的强污染，效果比cutoff更强
__term_sd_task_pre_ext_73 git_clone_repository https://github.com/ArtVentureX/sd-webui-agent-scheduler "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 生图队列管理，可制作一个参数不同的队列来进行批量生图
__term_sd_task_pre_ext_74 git_clone_repository https://github.com/butaixianran/Stable-Diffusion-Webui-Civitai-Helper "${SD_WEBUI_ROOT_PATH}"/extensions OFF # civitai模型管理
__term_sd_task_pre_ext_75 git_clone_repository https://github.com/Yinzo/sd-webui-Lora-queue-helper "${SD_WEBUI_ROOT_PATH}"/extensions OFF # Lora队列助手，用于比较具有相同提示和设置的相同角色的Lora/从同一来源生成不同的角色/或者只需切换和选择Lora，而无需更改选项卡
__term_sd_task_pre_ext_76 git_clone_repository https://github.com/mattyamonaca/PBRemTools "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图片背景去除，并且可以生成蒙版图像
__term_sd_task_pre_ext_77 git_clone_repository https://github.com/songweige/sd-webui-rich-text "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使用富文本进行图像生成，并且能够通过提示词来精准的控制图像
__term_sd_task_pre_ext_78 git_clone_repository https://github.com/WSH032/image-deduplicate-cluster-webui "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图像查重和图片聚类
__term_sd_task_pre_ext_79 git_clone_repository https://github.com/opparco/stable-diffusion-webui-composable-lora "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 将LoRA在提示中的插入位置与“AND”语法相关联
__term_sd_task_pre_ext_80 git_clone_repository https://github.com/bbc-mc/sdweb-merge-block-weighted-gui "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 模型U-NET权重调整与合并
__term_sd_task_pre_ext_81 git_clone_repository https://github.com/BlafKing/sd-civitai-browser-plus "${SD_WEBUI_ROOT_PATH}"/extensions OFF # civitai助手升级版，支持更多功能
__term_sd_task_pre_ext_82 git_clone_repository https://github.com/nihedon/sd-webui-weight-helper "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 快捷调整lora分层参数
__term_sd_task_pre_ext_83 git_clone_repository https://github.com/p1atdev/sd-danbooru-tags-upsampler "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 将用于生图的提示词进行润色，使其出图的画面多样化，更自然
__term_sd_task_pre_ext_84 git_clone_repository https://github.com/javsezlol1/Stylez "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 提示词预设风格选择工具
__term_sd_task_pre_ext_85 git_clone_repository https://github.com/Firetheft/sd-webui-next-style "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 提示词预设风格选择工具，增加了汉化并添加Fooocus全部风格模板
__term_sd_task_pre_ext_86 git_clone_repository https://github.com/licyk/a1111-sd-webui-haku-img "${SD_WEBUI_ROOT_PATH}"/extensions ON # 图像处理工具
__term_sd_task_pre_ext_87 git_clone_repository https://github.com/KohakuBlueleaf/Kohaku-NAI "${SD_WEBUI_ROOT_PATH}"/extensions OFF # novelai_api调用工具
__term_sd_task_pre_ext_88 git_clone_repository https://github.com/light-and-ray/sd-webui-cli-interruption "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 当在终端中按下Ctrl+C时，若此时正在生图，则将Ctrl+C的终止程序信号更改为终止生图的信号
__term_sd_task_pre_ext_89 git_clone_repository https://github.com/w-e-w/sdwebui-close-confirmation-dialogue "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加关闭SD-WebUI界面的确认提醒
__term_sd_task_pre_ext_90 git_clone_repository https://github.com/w-e-w/sd-webui-hires-fix-tweaks "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加更多高清修复的选项
__term_sd_task_pre_ext_91 git_clone_repository https://github.com/w-e-w/sd-webui-custom-autolaunch "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 自定义启动SD-WebUI界面的浏览器
__term_sd_task_pre_ext_92 git_clone_repository https://github.com/AlbedoFire/sd-webui-triposr "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加Triposr支持
__term_sd_task_pre_ext_93 git_clone_repository https://github.com/SenshiSentou/sd-webui-qic-console "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 在SD-WebUI界面添加Python终端，用于简单的调试
__term_sd_task_pre_ext_94 git_clone_repository https://github.com/antfu/sd-webui-qrcode-toolkit "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 二维码处理工具
__term_sd_task_pre_ext_95 git_clone_repository https://github.com/huchenlei/sd-webui-controlnet-marigold "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为controlnet插件添加marigold深度预处理器
__term_sd_task_pre_ext_96 git_clone_repository https://github.com/Koishi-Star/Euler-Smea-Dyn-Sampler "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加Eular-SMEA-Dy采样算法
__term_sd_task_pre_ext_97 git_clone_repository https://github.com/licyk/advanced_euler_sampler_extension "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加Eular-SMEA-Dy，Eular-SMEA采样算法
__term_sd_task_pre_ext_98 git_clone_repository https://github.com/Haoming02/sd-webui-vectorscope-cc "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 噪声偏移插件，可用于调整亮度，对比度和颜色
__term_sd_task_pre_ext_99 git_clone_repository https://github.com/AG-w/sd-webui-smea "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加Eular-Smea采样器和TCD采样器
__term_sd_task_pre_ext_100 git_clone_repository https://github.com/ljleb/sd-webui-neutral-prompt "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加AND_PERP、AND_SALT、AND_TOPK提示词用法
__term_sd_task_pre_ext_101 git_clone_repository https://github.com/Haoming02/sd-webui-tabs-extension "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 优化WebUI选项卡的排版
__term_sd_task_pre_ext_102 git_clone_repository https://github.com/Haoming02/sd-forge-ic-light "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加ic-light支持
__term_sd_task_pre_ext_103 git_clone_repository https://github.com/power88/webui-fooocus-prompt-expansion "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加fooocus的提示词扩写支持
__term_sd_task_pre_ext_104 git_clone_repository https://github.com/huchenlei/sd-webui-model-patcher "${SD_WEBUI_ROOT_PATH}"/extensions OFF # ComfyUI样式的LDM修补插件
__term_sd_task_pre_ext_105 git_clone_repository https://github.com/a2569875/lora-prompt-tool "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 快捷管理lora模型的触发词
__term_sd_task_pre_ext_106 git_clone_repository https://github.com/Haoming02/sd-webui-easy-tag-insert "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 提示词快捷插入
__term_sd_task_pre_ext_107 git_clone_repository https://github.com/Haoming02/sd-webui-i2i-ancestral-tree "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图生图的可视化图片关系
__term_sd_task_pre_ext_108 git_clone_repository https://github.com/Haoming02/sd-forge-couple "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加分区绘制的功能，仅支持forge
__term_sd_task_pre_ext_109 git_clone_repository https://github.com/Haoming02/sd-webui-advanced-xyz "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 改进xyz图表的功能
__term_sd_task_pre_ext_110 git_clone_repository https://github.com/Haoming02/sd-webui-mosaic-outpaint "${SD_WEBUI_ROOT_PATH}"/extensions ON # 快捷扩图工具
__term_sd_task_pre_ext_111 git_clone_repository https://github.com/Haoming02/sd-webui-image-comparison "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图片对比工具
__term_sd_task_pre_ext_112 git_clone_repository https://github.com/Haoming02/sd-webui-diffusion-cg "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 在潜空间张量范围执行颜色分级，改善出图的效果
__term_sd_task_pre_ext_113 git_clone_repository https://github.com/Haoming02/sd-webui-resharpen "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图片锐化工具，改善出图效果
__term_sd_task_pre_ext_114 git_clone_repository https://github.com/Haoming02/sd-webui-mobile-friendly "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使界面排版在手机上更合理
__term_sd_task_pre_ext_115 git_clone_repository https://github.com/Haoming02/sd-webui-prompt-format "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 提示词格式化工具
__term_sd_task_pre_ext_116 git_clone_repository https://github.com/Haoming02/sd-webui-aaa "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为主体生成用于修复的蒙版，使背景与主体融合更融洽
__term_sd_task_pre_ext_117 git_clone_repository https://github.com/Haoming02/sd-webui-clear-screen "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 清理控制台输出
__term_sd_task_pre_ext_118 git_clone_repository https://github.com/Haoming02/sd-webui-auto-res "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 通过预设自动设置不同模型的分辨率
__term_sd_task_pre_ext_119 git_clone_repository https://github.com/Haoming02/sd-webui-moar-generate "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加了另一个生成按钮，用于当有太多活动扩展但不想每次都一直向上滚动时
__term_sd_task_pre_ext_120 git_clone_repository https://github.com/Tzigo/metadata_utils "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为sd-webui-supermerger融合的模型添加元数据
__term_sd_task_pre_ext_121 git_clone_repository https://github.com/w-e-w/sd-webui-xyz-addon "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为xyz脚本添加更多功能
__term_sd_task_pre_ext_122 git_clone_repository https://github.com/Repeerc/sd-webui-flash-attention-zluda-win "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为zluda添加flash-attension优化
__term_sd_task_pre_ext_123 git_clone_repository https://github.com/thisjam/sd-webui-split-layout "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 调整界面布局
__term_sd_task_pre_ext_124 git_clone_repository https://github.com/thisjam/sd-webui-oldsix-prompt "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 提示词辅助工具
__term_sd_task_pre_ext_125 git_clone_repository https://github.com/Nuullll/sd-webui-ipex-enhancement "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 优化IPEX后端的运行体验
__term_sd_task_pre_ext_126 git_clone_repository https://github.com/MackinationsAi/sd-webui-udav2 "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加DepthAnythingV2支持
__term_sd_task_pre_ext_127 git_clone_repository https://github.com/light-and-ray/sd-webui-cn-sam-preprocessor "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为ControlNet插件添加SegmentAnything预处理器
__term_sd_task_pre_ext_128 git_clone_repository https://github.com/bluelovers/sd-webui-pnginfo-beautify "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 将图片下方的生图信息进行美化排版
__term_sd_task_pre_ext_129 git_clone_repository https://github.com/Haoming02/sd-webui-resource-monitor "${SD_WEBUI_ROOT_PATH}"/extensions ON # 性能监测
__term_sd_task_pre_ext_130 git_clone_repository https://github.com/NON906/chara-searcher "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 角色图片搜索
__term_sd_task_pre_ext_131 git_clone_repository https://github.com/MakkiShizu/sd-webui-to_top_button "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加一个回滚至顶部按钮
__term_sd_task_pre_ext_132 git_clone_repository https://github.com/AndreyRGW/sd-webui-aurasr "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加AuraSR放大算法支持
__term_sd_task_pre_ext_133 git_clone_repository https://github.com/quanghuyn94/a1111-intelli-prompt "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 提示词辅助插件
__term_sd_task_pre_ext_134 git_clone_repository https://github.com/xlinx/sd-webui-decadetw-auto-prompt-llm "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使用LLM辅助编写提示词
__term_sd_task_pre_ext_135 git_clone_repository https://github.com/Haoming02/sd-forge-temperature-settings "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图片色温调节，仅支持Forge
__term_sd_task_pre_ext_136 git_clone_repository https://github.com/Haoming02/forge-space-SUPIR "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为sd-webui-forge添加SUPIR支持
__term_sd_task_pre_ext_137 git_clone_repository https://github.com/Haoming02/forge-space-ollama "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为sd-webui-forge添加ollama支持
__term_sd_task_pre_ext_138 git_clone_repository https://github.com/SenshiSentou/sd-webui-cardmaster "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 优化模型选项卡
__term_sd_task_pre_ext_139 git_clone_repository https://github.com/CurtisDS/extra-network-side-panel-for-a1111 "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 恢复旧版扩展模型按钮
__term_sd_task_pre_ext_140 git_clone_repository https://github.com/jessearodriguez/sd-forge-regional-prompter "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为sd-webui-forge添加分区提示词支持
__term_sd_task_pre_ext_141 git_clone_repository https://github.com/LEv145/--sd-webui-ar-plus "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 宽高比选择工具
__term_sd_task_pre_ext_142 git_clone_repository https://github.com/DenOfEquity/forge2_cleaner "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为sd-webui-forge添加图像内容擦除功能
__term_sd_task_pre_ext_143 git_clone_repository https://github.com/novitalabs/sd-webui-cleaner "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加图像内容擦除功能
__term_sd_task_pre_ext_144 git_clone_repository https://github.com/DenOfEquity/HyperTile "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为sd-webui-forge添加HyperTile支持
__term_sd_task_pre_ext_145 git_clone_repository https://github.com/DenOfEquity/forgeFlux_dualPrompt "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为sd-webui-forge添加多提示词功能
__term_sd_task_pre_ext_146 git_clone_repository https://github.com/Juqowel/GPU_For_T5 "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为sd-webui-forge添加移动t5模型功能，可将t5模型权重移至指定gpu上
__term_sd_task_pre_ext_147 git_clone_repository https://github.com/Filexor/sd-webui-top-k-emphasis "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为sd-webui-forge添加Top_K_Emphasis提示词语法
__term_sd_task_pre_ext_148 git_clone_repository https://github.com/wkpark/uddetailer "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 面部修复工具
__term_sd_task_pre_ext_149 git_clone_repository https://github.com/Zyin055/Config-Presets "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 生图参数预设保存工具
__term_sd_task_pre_ext_150 git_clone_repository https://github.com/brick2face/seamless-tile-inpainting "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 平滑平铺工具
__term_sd_task_pre_ext_151 git_clone_repository https://github.com/anapnoe/sd-webui-ux "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 更改sd-webui的界面
__term_sd_task_pre_ext_152 git_clone_repository https://github.com/light-and-ray/sd-webui-replacer "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图片内容替换工具
__term_sd_task_pre_ext_153 git_clone_repository https://github.com/sdbds/stable-diffusion-webui-wildcards "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加提示词通配符支持
__term_sd_task_pre_ext_154 git_clone_repository https://github.com/ljleb/sd-webui-freeu "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加FreeU支持
__term_sd_task_pre_ext_155 git_clone_repository https://github.com/v0xie/sd-webui-incantations "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加PerturbedAttentionGuidance支持
__term_sd_task_pre_ext_156 git_clone_repository https://github.com/w-e-w/sd-webui-kohya-hiresfix "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 修复在直出高分辨率图片时画面异常的问题
__term_sd_task_pre_ext_157 git_clone_repository https://github.com/wkpark/sd-webui-model-mixer "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 模型融合工具
__term_sd_task_pre_ext_158 git_clone_repository https://github.com/Repeerc/sd-webui-flash-attention2-rdna3-rocm "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为Windows下的ZLUDA添加FlashAttension支持
__term_sd_task_pre_ext_159 git_clone_repository https://github.com/licyk/sd-webui-tcd-sampler "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为SDWebUI添加tcd采样算法
__term_sd_task_pre_ext_160 git_clone_repository https://github.com/dimitribarbot/sd-webui-birefnet "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加BiRefNet支持，用于移除背景
__term_sd_task_pre_ext_161 git_clone_repository https://github.com/muerrilla/stable-diffusion-NPW "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为反向提示词添加整体权重设置
__term_sd_task_pre_ext_162 git_clone_repository https://github.com/licyk/sd_forge_hypertile_svd_z123 "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为sd-webui和sd-webui-forge添加hypertile，svd，stable-z123支持
__term_sd_task_pre_ext_163 git_clone_repository https://github.com/viyiviyi/stable-diffusion-webui-zoomimage "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为图片查看窗口添加鼠标缩放拖动功能
__term_sd_task_pre_ext_164 git_clone_repository https://github.com/gutris1/sd-simple-dimension-preset "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 图片分辨率预设
__term_sd_task_pre_ext_165 git_clone_repository https://github.com/gutris1/sd-hub "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 批量下载管理文件
__term_sd_task_pre_ext_166 git_clone_repository https://github.com/Avaray/lora-keywords-finder "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使用civitai-api查询lora模型触发词
__term_sd_task_pre_ext_167 git_clone_repository https://github.com/MINENEMA/sd-webui-quickrecents "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 查看最近几次图片生成参数并导入
__term_sd_task_pre_ext_168 git_clone_repository https://github.com/Haoming02/sd-forge-blockcache "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使用TeaCache加速SDXL的推理速度
__term_sd_task_pre_ext_169 git_clone_repository https://github.com/DenOfEquity/sd-forge-blockcache "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使用TeaCache加速FLUX的推理速度
__term_sd_task_pre_ext_170 git_clone_repository https://github.com/Haoming02/sd-webui-rewrite-history "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 批量转换图片格式并保留图片信息
__term_sd_task_pre_ext_171 git_clone_repository https://github.com/tocantrell/sd-refdrop-forge "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使用RefDrop保持一致性（SD-WebUI-Forge）
__term_sd_task_pre_ext_172 git_clone_repository https://github.com/tocantrell/sd-refdrop "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 使用RefDrop保持一致性（SD-WebUI-reForge）
__term_sd_task_pre_ext_173 git_clone_repository https://github.com/Haoming02/sd-forge-negpip "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 解决tag强污染，仅支持SD-WebUI-Forge
__term_sd_task_pre_ext_174 git_clone_repository https://github.com/altoiddealer/sd-webui-segment-anything-altoids "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 为sd_webui_forge添加SegmentAnything
__term_sd_task_pre_ext_175 git_clone_repository https://github.com/spawner1145/sd-webui-framepack "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 添加FramePack支持
__term_sd_task_pre_ext_176 git_clone_repository https://github.com/w-e-w/sd-webui-different-save-button-image-format "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 设置保存图片时保存的图片格式
__term_sd_task_pre_ext_177 git_clone_repository https://github.com/thavocado/sd-webui-frequency-separation "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 提升图片质量
__term_sd_task_pre_ext_178 git_clone_repository https://github.com/w-e-w/sd-webui-hide-gradio-message "${SD_WEBUI_ROOT_PATH}"/extensions OFF # 隐藏Gradio弹窗消息，将消息输出到控制台
__term_sd_task_pre_ext_179 git_clone_repository https://github.com/licyk/sd-webui-licyk-style-image "${SD_WEBUI_ROOT_PATH}"/extensions ON # 图片滤镜扩展
|
2301_81996401/term-sd
|
install/sd_webui/sd_webui_extension.sh
|
Shell
|
agpl-3.0
| 31,939
|
__term_sd_task_pre_ext_1 term_sd_echo "下载 Controlnet 模型中" # ControlNet(36.12g) ON
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11e_sd15_ip2p_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11e_sd15_shuffle_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11f1e_sd15_tile_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11f1p_sd15_depth_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_canny_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_inpaint_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_lineart_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_mlsd_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_normalbae_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_openpose_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_scribble_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_seg_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15_softedge_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v11p_sd15s2_lineart_anime_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v1p_sd15_brightness.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v1p_sd15_illumination.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/control_v1p_sd15_qrcode_monster.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/sd_control_collection/resolve/main/xinsir-controlnet-union-sdxl-1.0-promax.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter_sd15.pth "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter_sd15_light.pth "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter_sd15_plus.pth "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter_sd15_vit-G.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter_sdxl.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1/resolve/main/ip-adapter-plus_sdxl_vit-h.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/clip_vision/clip_g.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/clip_vision
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/clip_vision/clip_h.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/clip_vision
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/clip_vision/clip_vitl.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/clip_vision
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/hed/ControlNetHED.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/hed
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/lama/ControlNetLama.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/lama
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/leres/latest_net_G.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/leres
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/leres/res101.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/leres
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/lineart/sk_model.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/lineart
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/lineart/sk_model2.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/lineart
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/lineart_anime/netG.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/lineart_anime
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/manga_line/erika.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/manga_line
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/midas/dpt_hybrid-midas-501f0c75.pt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/midas
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/mlsd/mlsd_large_512_fp32.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/mlsd
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/normal_bae/scannet.pt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/normal_bae
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/oneformer/150_16_swin_l_oneformer_coco_100ep.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/oneformer
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/oneformer/250_16_swin_l_oneformer_ade20k_160k.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/oneformer
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/openpose/body_pose_model.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/openpose/dw-ll_ucoco_384.onnx "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/openpose/facenet.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/openpose/hand_pose_model.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/openpose/yolox_l.onnx "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/pidinet/table5_pidinet.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/pidinet
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/uniformer/upernet_global_small.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/uniformer
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/zoedepth/ZoeD_M12_N.pt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/zoedepth
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/anime_face_segment/UNet.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/anime_face_segment
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/densepose/densepose_r50_fpn_dl.torchscript "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/densepose
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/depth_anything/depth_anything_vitl14.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/depth_anything
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/hand_refiner/hr16/ControlNet-HandRefiner-pruned/graphormer_hand_state_dict.bin "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/hand_refiner/hr16/ControlNet-HandRefiner-pruned
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/hand_refiner/hr16/ControlNet-HandRefiner-pruned/hrnetv2_w64_imagenet_pretrained.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/hand_refiner/hr16/ControlNet-HandRefiner-pruned
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/openpose/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.onnx "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/depth_anything_v2/depth_anything_v2_vitl.safetensors "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/depth_anything_v2
__term_sd_task_pre_ext_1 aria2_download https://huggingface.co/licyk/controlnet_v1.1_annotator/resolve/main/mobile_sam/mobile_sam.pt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/mobile_sam
__term_sd_task_pre_ext_2 term_sd_echo "下载 Animatediff 模型" # AnimateDiff(1.67g) OFF
__term_sd_task_pre_ext_2 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-animatediff/v3_sd15_mm.ckpt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-animatediff/model
__term_sd_task_pre_ext_3 term_sd_echo "下载 Adetailer 模型" # Adetailer(224.8m) OFF
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/adetailer/deepfashion2_yolov8s-seg.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/adetailer/face_yolov8m.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/adetailer/face_yolov8n.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/adetailer/face_yolov8n_v2.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/adetailer/face_yolov8s.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/adetailer/hand_yolov8n.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/adetailer/hand_yolov8s.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/adetailer/person_yolov8m-seg.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/adetailer/person_yolov8n-seg.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/adetailer/person_yolov8s-seg.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_4 term_sd_echo "下载 IS-NET 模型" # IS-NET(176.6m) ON
__term_sd_task_pre_ext_4 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-IS-NET-pro/isnet-general-use.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-IS-NET-pro/saved_models/IS-Net
__term_sd_task_pre_ext_5 term_sd_echo "下载 SD-WebUI-Segment-Anything模型" # Segment-Anything(5.81g) ON
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-segment-anything/sam_vit_h_4b8939.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/sam
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-segment-anything/sam_vit_l_0b3195.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/sam
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-segment-anything/sam_vit_b_01ec64.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/sam
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-segment-anything/mobile_sam.pt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/sam
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-segment-anything/groundingdino_swint_ogc.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/grounding-dino
__term_sd_task_pre_ext_5 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-segment-anything/groundingdino_swinb_cogcoor.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/grounding-dino
__term_sd_task_pre_ext_6 term_sd_echo "下载 SD-WebUII-Inpaint-Anything 模型" # Inpaint-Anything(4.18g) ON
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-segment-anything/sam_vit_h_4b8939.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-inpaint-anything/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-segment-anything/sam_vit_l_0b3195.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-inpaint-anything/models
__term_sd_task_pre_ext_6 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-segment-anything/sam_vit_b_01ec64.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-inpaint-anything/models
__term_sd_task_pre_ext_7 term_sd_echo "下载 SD-Forge-LayerDiffusion 模型" # LayerDiffusion(10.29g) ON
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_bg2ble.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_bgble2fg.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_fg2ble.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_fgble2bg.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_transparent_attn.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/layer_xl_transparent_conv.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/vae_transparent_decoder.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 aria2_download https://huggingface.co/licyk/layerdiffusion/resolve/main/vae_transparent_encoder.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_8 term_sd_echo "下载 DanTagGen 模型" # DanTagGen(1.53g) OFF
__term_sd_task_pre_ext_8 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/a1111-sd-webui-dtg/DanTagGen-delta-rev2_ggml-model-Q6_K.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/a1111-sd-webui-dtg/models
__term_sd_task_pre_ext_8 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/a1111-sd-webui-dtg/DanTagGen-delta-rev2_ggml-model-Q8_0.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/a1111-sd-webui-dtg/models
__term_sd_task_pre_ext_8 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/a1111-sd-webui-dtg/DanTagGen-delta-rev2_ggml-model-f16.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/a1111-sd-webui-dtg/models
__term_sd_task_pre_ext_9 term_sd_echo "下载 sd-webui-stablesr 模型" # StableSR(422.3m) ON
__term_sd_task_pre_ext_9 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/sd-webui-stablesr/webui_768v_139.ckpt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-stablesr/models
__term_sd_task_pre_ext_10 term_sd_echo "下载 z-tipo-extension 模型" # z-tipo-extension(1.42g) ON
__term_sd_task_pre_ext_10 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/z-tipo-extension/TIPO-500M_epoch5-F16.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/z-tipo-extension/models
__term_sd_task_pre_ext_10 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/z-tipo-extension/TIPO-200M-40Btok-F16.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/z-tipo-extension/models
__term_sd_task_pre_ext_10 aria2_download https://huggingface.co/licyk/sd-extensions-model/resolve/main/z-tipo-extension/TIPO-200M-ft-F16.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/z-tipo-extension/models
|
2301_81996401/term-sd
|
install/sd_webui/sd_webui_extension_hf_model.sh
|
Shell
|
agpl-3.0
| 19,629
|
__term_sd_task_pre_ext_1 term_sd_echo "下载 ControlNet 模型中" # ControlNet(36.12g) ON
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11e_sd15_ip2p_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11e_sd15_shuffle_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11f1e_sd15_tile_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11f1p_sd15_depth_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_canny_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_inpaint_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_lineart_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_mlsd_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_normalbae_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_openpose_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_scribble_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_seg_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15_softedge_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v11p_sd15s2_lineart_anime_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v1p_sd15_brightness.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v1p_sd15_illumination.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/control_v1p_sd15_qrcode_monster.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/sd_control_collection/master/xinsir-controlnet-union-sdxl-1.0-promax.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter_sd15.pth "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter_sd15_light.pth "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter_sd15_plus.pth "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter_sd15_vit-G.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter_sdxl.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1/master/ip-adapter-plus_sdxl_vit-h.safetensors "${SD_WEBUI_ROOT_PATH}"/models/ControlNet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/clip_vision/clip_g.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/clip_vision
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/clip_vision/clip_h.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/clip_vision
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/clip_vision/clip_vitl.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/clip_vision
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/hed/ControlNetHED.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/hed
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/lama/ControlNetLama.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/lama
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/leres/latest_net_G.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/leres
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/leres/res101.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/leres
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/lineart/sk_model.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/lineart
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/lineart/sk_model2.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/lineart
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/lineart_anime/netG.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/lineart_anime
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/manga_line/erika.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/manga_line
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/midas/dpt_hybrid-midas-501f0c75.pt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/midas
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/mlsd/mlsd_large_512_fp32.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/mlsd
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/normal_bae/scannet.pt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/normal_bae
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/oneformer/150_16_swin_l_oneformer_coco_100ep.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/oneformer
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/oneformer/250_16_swin_l_oneformer_ade20k_160k.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/oneformer
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/openpose/body_pose_model.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/openpose/dw-ll_ucoco_384.onnx "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/openpose/facenet.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/openpose/hand_pose_model.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/openpose/yolox_l.onnx "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/pidinet/table5_pidinet.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/pidinet
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/uniformer/upernet_global_small.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/uniformer
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/zoedepth/ZoeD_M12_N.pt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/zoedepth
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/anime_face_segment/UNet.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/anime_face_segment
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/densepose/densepose_r50_fpn_dl.torchscript "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/densepose
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/depth_anything/depth_anything_vitl14.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/depth_anything
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/hand_refiner/hr16/ControlNet-HandRefiner-pruned/graphormer_hand_state_dict.bin "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/hand_refiner/hr16/ControlNet-HandRefiner-pruned
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/hand_refiner/hr16/ControlNet-HandRefiner-pruned/hrnetv2_w64_imagenet_pretrained.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/hand_refiner/hr16/ControlNet-HandRefiner-pruned
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/openpose/rtmpose-m_simcc-ap10k_pt-aic-coco_210e-256x256-7a041aa1_20230206.onnx "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/openpose
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/depth_anything_v2/depth_anything_v2_vitl.safetensors "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/depth_anything_v2
__term_sd_task_pre_ext_1 get_modelscope_model licyks/controlnet_v1.1_annotator/master/mobile_sam/mobile_sam.pt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-controlnet/annotator/downloads/mobile_sam
__term_sd_task_pre_ext_2 term_sd_echo "下载 AnimateDiff 模型" # AnimateDiff(1.67g) OFF
__term_sd_task_pre_ext_2 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-animatediff/v3_sd15_mm.ckpt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-animatediff/model
__term_sd_task_pre_ext_3 term_sd_echo "下载 Adetailer 模型" # Adetailer(224.8m) OFF
__term_sd_task_pre_ext_3 get_modelscope_model licyks/sd-extensions-model/master/adetailer/deepfashion2_yolov8s-seg.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 get_modelscope_model licyks/sd-extensions-model/master/adetailer/face_yolov8m.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 get_modelscope_model licyks/sd-extensions-model/master/adetailer/face_yolov8n.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 get_modelscope_model licyks/sd-extensions-model/master/adetailer/face_yolov8n_v2.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 get_modelscope_model licyks/sd-extensions-model/master/adetailer/face_yolov8s.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 get_modelscope_model licyks/sd-extensions-model/master/adetailer/hand_yolov8n.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 get_modelscope_model licyks/sd-extensions-model/master/adetailer/hand_yolov8s.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 get_modelscope_model licyks/sd-extensions-model/master/adetailer/person_yolov8m-seg.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 get_modelscope_model licyks/sd-extensions-model/master/adetailer/person_yolov8n-seg.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_3 get_modelscope_model licyks/sd-extensions-model/master/adetailer/person_yolov8s-seg.pt "${SD_WEBUI_ROOT_PATH}"/models/adetailer
__term_sd_task_pre_ext_4 term_sd_echo "下载 IS-NET 模型" # IS-NET(176.6m) ON
__term_sd_task_pre_ext_4 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-IS-NET-pro/isnet-general-use.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-IS-NET-pro/saved_models/IS-Net
__term_sd_task_pre_ext_5 term_sd_echo "下载 SD-WebUI-Segment-Anything模型" # Segment-Anything(5.81g) ON
__term_sd_task_pre_ext_5 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-segment-anything/sam_vit_h_4b8939.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/sam
__term_sd_task_pre_ext_5 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-segment-anything/sam_vit_l_0b3195.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/sam
__term_sd_task_pre_ext_5 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-segment-anything/sam_vit_b_01ec64.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/sam
__term_sd_task_pre_ext_5 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-segment-anything/mobile_sam.pt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/sam
__term_sd_task_pre_ext_5 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-segment-anything/groundingdino_swint_ogc.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/grounding-dino
__term_sd_task_pre_ext_5 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-segment-anything/groundingdino_swinb_cogcoor.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-segment-anything/models/grounding-dino
__term_sd_task_pre_ext_6 term_sd_echo "下载 SD-WebUII-Inpaint-Anything 模型" # Inpaint-Anything(4.18g) ON
__term_sd_task_pre_ext_6 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-segment-anything/sam_vit_h_4b8939.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-inpaint-anything/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-segment-anything/sam_vit_l_0b3195.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-inpaint-anything/models
__term_sd_task_pre_ext_6 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-segment-anything/sam_vit_b_01ec64.pth "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-inpaint-anything/models
__term_sd_task_pre_ext_7 term_sd_echo "下载 SD-Forge-LayerDiffusion 模型" # LayerDiffusion(10.29g) ON
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_bg2ble.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_bgble2fg.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_fg2ble.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_fgble2bg.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_transparent_attn.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/layer_xl_transparent_conv.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/vae_transparent_decoder.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_7 get_modelscope_model licyks/layerdiffusion/master/vae_transparent_encoder.safetensors "${SD_WEBUI_ROOT_PATH}"/models/layer_model
__term_sd_task_pre_ext_8 term_sd_echo "下载 DanTagGen 模型" # DanTagGen(1.53g) OFF
__term_sd_task_pre_ext_8 get_modelscope_model licyks/sd-extensions-model/master/a1111-sd-webui-dtg/DanTagGen-delta-rev2_ggml-model-Q6_K.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/a1111-sd-webui-dtg/models
__term_sd_task_pre_ext_8 get_modelscope_model licyks/sd-extensions-model/master/a1111-sd-webui-dtg/DanTagGen-delta-rev2_ggml-model-Q8_0.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/a1111-sd-webui-dtg/models
__term_sd_task_pre_ext_8 get_modelscope_model licyks/sd-extensions-model/master/a1111-sd-webui-dtg/DanTagGen-delta-rev2_ggml-model-f16.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/a1111-sd-webui-dtg/models
__term_sd_task_pre_ext_9 term_sd_echo "下载 sd-webui-stablesr 模型" # StableSR(422.3m) ON
__term_sd_task_pre_ext_9 get_modelscope_model licyks/sd-extensions-model/master/sd-webui-stablesr/webui_768v_139.ckpt "${SD_WEBUI_ROOT_PATH}"/extensions/sd-webui-stablesr/models
__term_sd_task_pre_ext_10 term_sd_echo "下载 z-tipo-extension 模型" # z-tipo-extension(1.02g) ON
__term_sd_task_pre_ext_10 get_modelscope_model licyks/sd-extensions-model/master/z-tipo-extension/TIPO-500M_epoch5-F16.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/z-tipo-extension/models
__term_sd_task_pre_ext_10 get_modelscope_model licyks/sd-extensions-model/master/z-tipo-extension/TIPO-200M-40Btok-F16.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/z-tipo-extension/models
__term_sd_task_pre_ext_10 get_modelscope_model licyks/sd-extensions-model/master/z-tipo-extension/TIPO-200M-ft-F16.gguf "${SD_WEBUI_ROOT_PATH}"/extensions/z-tipo-extension/models
|
2301_81996401/term-sd
|
install/sd_webui/sd_webui_extension_ms_model.sh
|
Shell
|
agpl-3.0
| 17,604
|
__term_sd_task_pre_model_1 # =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/v1-5-pruned-emaonly.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # 大模型 v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/animefull-final-pruned.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/nai1-artist_all_in_one_merge.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # nai1-artist_all_in_one_merge(2.13g) OFF
__term_sd_task_pre_model_5 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/Counterfeit-V3.0_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Counterfeit-V3.0(4.24g) OFF
__term_sd_task_pre_model_6 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/cetusMix_Whalefall2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # cetusMix_Whalefall2(3.85g) OFF
__term_sd_task_pre_model_7 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/cuteyukimixAdorable_neochapter3.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # cuteyukimixAdorable_neochapter3(2.3g) OFF
__term_sd_task_pre_model_8 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/ekmix-pastel-fp16-no-ema.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # ekmix-pastel(2.13g) OFF
__term_sd_task_pre_model_9 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/ex2K_sse2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # ex2K_sse2(2.38g) OFF
__term_sd_task_pre_model_10 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/kohakuV5_rev2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohakuV5_rev2(2.13g) OFF
__term_sd_task_pre_model_11 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/meinamix_meinaV11.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # meinamix_meinaV11(2.13g) OFF
__term_sd_task_pre_model_12 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/oukaStar_10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # oukaStar_10(5.43g) OFF
__term_sd_task_pre_model_13 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/pastelMixStylizedAnime_pastelMixPrunedFP16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # pastelMixStylizedAnime(2.13g) OFF
__term_sd_task_pre_model_14 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/rabbit_v6.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # rabbit_v6(1.97g) OFF
__term_sd_task_pre_model_15 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/sweetSugarSyndrome_rev15.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sweetSugarSyndrome_rev15(2.13g) OFF
__term_sd_task_pre_model_16 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/AnythingV5Ink_ink.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # AnythingV5Ink_ink(2.13g) OFF
__term_sd_task_pre_model_17 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/bartstyledbBlueArchiveArtStyleFineTunedModel_v10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # bartstyledbBlueArchiveArtStyle(2.13g) OFF
__term_sd_task_pre_model_18 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/meinapastel_v6Pastel.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # meinapastel_v6(2.13g) OFF
__term_sd_task_pre_model_19 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/qteamixQ_omegaFp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # qteamix(2.13g) OFF
__term_sd_task_pre_model_20 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_1.5/tmndMix_tmndMixSPRAINBOW.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # tmndMix(2.13g) OFF
__term_sd_task_pre_model_21 # =====SD2.1大模型===== OFF
__term_sd_task_pre_model_22 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/v2-1_768-ema-pruned.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_23 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/wd-1-4-anime_e2.ckpt "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_24 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sd_2.1/wd-mofu-fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_25 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_26 aria2_download https://huggingface.co/licyk/sd-lora/resolve/main/sdxl/sd_xl_offset_example-lora_1.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Lora # sd_xl_offset_example-lora_1.0(49.6m) OFF
__term_sd_task_pre_model_27 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_base_1.0_0.9vae.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_28 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_refiner_1.0_0.9vae.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_29 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_turbo_1.0_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_30 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/cosxl.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # cosxl(6.94g) OFF
__term_sd_task_pre_model_31 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/cosxl_edit.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_32 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.0-base.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_33 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_34 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-3.1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_35 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_36 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0-opt.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_37 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animagine-xl-4.0-zero.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_38 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/holodayo-xl-2.1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_39 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kivotos-xl-2.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_40 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/clandestine-xl-1.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_41 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/UrangDiffusion-1.1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_42 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/RaeDiffusion-XL-v2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_43 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sd_xl_anime_V52.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_44 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-delta-rev1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_45 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohakuXLEpsilon_rev1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_46 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-epsilon-rev2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_47 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-epsilon-rev3.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_48 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/kohaku-xl-zeta.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_49 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/starryXLV52_v52.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_50 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/heartOfAppleXL_v20.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_51 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/heartOfAppleXL_v30.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_52 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/baxlBartstylexlBlueArchiveFlatCelluloid_xlv1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_53 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/baxlBlueArchiveFlatCelluloidStyle_xlv3.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_54 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sanaexlAnimeV10_v10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_55 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/sanaexlAnimeV10_v11.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_56 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/SanaeXL-Anime-v1.2-aesthetic.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_57 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/SanaeXL-Anime-v1.3-aesthetic.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_58 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v0.1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_59 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v0.1-GUIDED.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_60 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v1.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_61 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v1.1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_62 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v2.0-stable.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_63 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/Illustrious-XL-v2.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_64 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/jruTheJourneyRemains_v25XL.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_65 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_illustriousxl10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_66 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/miaomiaoHarem_v15a.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_67 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/waiNSFWIllustrious_v80.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_68 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/tIllunai3_v4.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_69 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_earlyAccessVersion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_70 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred05Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_71 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred075.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_72 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred077.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_73 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred10Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_74 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_epsilonPred11Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_75 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPredTestVersion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_76 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred05Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_77 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred06Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_78 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred065SVersion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_79 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred075SVersion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_80 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred09RVersion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_81 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/noobaiXLNAIXL_vPred10Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_82 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_nbxl12.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_83 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/PVCStyleModelMovable_nbxlVPredV10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_84 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/ponyDiffusionV6XL_v6StartWithThisOne.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_85 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/pdForAnime_v20.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_86 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/tPonynai3_v51WeightOptimized.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_87 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/omegaPonyXLAnime_v20.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_88 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animeIllustDiffusion_v061.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_89 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/artiwaifuDiffusion_v10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_90 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/artiwaifu-diffusion-v2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_91 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/AnythingXL_xl.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_92 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/abyssorangeXLElse_v10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_93 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/animaPencilXL_v200.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_94 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/bluePencilXL_v401.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_95 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/nekorayxl_v06W3.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_96 aria2_download https://huggingface.co/licyk/sd-model/resolve/main/sdxl_1.0/CounterfeitXL-V1.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_97 # =====SD3大模型===== OFF
__term_sd_task_pre_model_98 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3_medium.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3_medium(4.34g) OFF
__term_sd_task_pre_model_99 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3_medium_incl_clips.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3_medium_incl_clips(5.97g) OFF
__term_sd_task_pre_model_100 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3_medium_incl_clips_t5xxlfp8.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3_medium_incl_clips_t5xxlfp8(10.87g) OFF
__term_sd_task_pre_model_101 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3.5_large.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3.5_large(16.5g) OFF
__term_sd_task_pre_model_102 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3.5_large_fp8_scaled.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3.5_large_fp8_scaled(14.9g) OFF
__term_sd_task_pre_model_103 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3.5_large_turbo.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3.5_large_turbo(16.5g) OFF
__term_sd_task_pre_model_104 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3.5_medium.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3.5_medium(5.1g) OFF
__term_sd_task_pre_model_105 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/sd3.5_medium_incl_clips_t5xxlfp8scaled.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3.5_medium_incl_clips_t5xxlfp8scaled(11.6g) OFF
__term_sd_task_pre_model_106 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/emi3.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # emi3(16.5g) OFF
__term_sd_task_pre_model_107 # =====SD3文本编码器===== OFF
__term_sd_task_pre_model_108 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/text_encoders/clip_g.safetensors "${SD_WEBUI_ROOT_PATH}"/models/CLIP # clip_g(1.39g) OFF
__term_sd_task_pre_model_109 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/text_encoders/clip_l.safetensors "${SD_WEBUI_ROOT_PATH}"/models/CLIP # clip_l(246.1m) OFF
__term_sd_task_pre_model_110 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/text_encoders/t5xxl_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/CLIP # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_111 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/text_encoders/t5xxl_fp8_e4m3fn.safetensors "${SD_WEBUI_ROOT_PATH}"/models/CLIP # t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_112 aria2_download https://huggingface.co/licyk/sd-3-model/resolve/main/text_encoders/t5xxl_fp8_e4m3fn_scaled.safetensors "${SD_WEBUI_ROOT_PATH}"/models/CLIP # t5xxl_fp8_e4m3fn_scaled(5.16g) OFF
__term_sd_task_pre_model_113 # =====FLUX模型===== OFF
__term_sd_task_pre_model_114 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev(23.8g) OFF
__term_sd_task_pre_model_115 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-fp8.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-fp8(17.2g) OFF
__term_sd_task_pre_model_116 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux_dev_fp8_scaled_diffusion_model.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux_dev_fp8_scaled_diffusion_model(11.9g) OFF
__term_sd_task_pre_model_117 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-bnb-nf4-v2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-bnb-nf4-v2(12g) OFF
__term_sd_task_pre_model_118 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-bnb-nf4.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-bnb-nf4(11.5g) OFF
__term_sd_task_pre_model_119 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q2_K.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q2_K-gguf(4.03g) OFF
__term_sd_task_pre_model_120 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q3_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q3_K_S-gguf(5.23g) OFF
__term_sd_task_pre_model_121 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q4_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q4_0-gguf(6.79g) OFF
__term_sd_task_pre_model_122 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q4_1.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q4_1-gguf(7.53g) OFF
__term_sd_task_pre_model_123 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q4_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q4_K_S-gguf(6.81g) OFF
__term_sd_task_pre_model_124 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q5_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q5_0-gguf(8.27g) OFF
__term_sd_task_pre_model_125 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q5_1.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q5_1-gguf(9.01g) OFF
__term_sd_task_pre_model_126 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q5_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q5_K_S-gguf(8.29g) OFF
__term_sd_task_pre_model_127 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q6_K.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q6_K-gguf(9.86g) OFF
__term_sd_task_pre_model_128 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-Q8_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_129 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-F16.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_130 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_131 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-fp8.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-fp8(17.2g) OFF
__term_sd_task_pre_model_132 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q2_K.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q2_K-gguf(4.01g) OFF
__term_sd_task_pre_model_133 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q3_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q3_K_S-gguf(5.21g) OFF
__term_sd_task_pre_model_134 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q4_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q4_0-gguf(6.77g) OFF
__term_sd_task_pre_model_135 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q4_1.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q4_1-gguf(7.51g) OFF
__term_sd_task_pre_model_136 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q4_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q4_K_S-gguf(6.78g) OFF
__term_sd_task_pre_model_137 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q5_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q5_0-gguf(8.25g) OFF
__term_sd_task_pre_model_138 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q5_1.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q5_1-gguf(8.99g) OFF
__term_sd_task_pre_model_139 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q5_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q5_K_S-gguf(8.26g) OFF
__term_sd_task_pre_model_140 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q6_K.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q6_K-gguf(9.83g) OFF
__term_sd_task_pre_model_141 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-Q8_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_142 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-schnell-F16.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_143 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/ashen0209-flux1-dev2pro.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_144 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/jimmycarter-LibreFLUX.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_145 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/nyanko7-flux-dev-de-distill.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_146 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/shuttle-3-diffusion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_147 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-krea-dev_fp8_scaled.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-krea-dev_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_148 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-krea-dev.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-krea-dev(23.8g) OFF
__term_sd_task_pre_model_149 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-dev-kontext_fp8_scaled.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-kontext_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_150 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/flux1-kontext-dev.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-kontext-dev(23.8g) OFF
__term_sd_task_pre_model_151 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_1/chroma-unlocked-v50.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # chroma-unlocked-v50(23.8g) OFF
__term_sd_task_pre_model_152 # =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_153 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/clip_l.safetensors "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # clip_l(246.1m) OFF
__term_sd_task_pre_model_154 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5xxl_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_155 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5xxl_fp8_e4m3fn.safetensors "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_156 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_L.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q3_K_L-gguf(2.46g) OFF
__term_sd_task_pre_model_157 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_M.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q3_K_M-gguf(2.3g) OFF
__term_sd_task_pre_model_158 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q3_K_S-gguf(2.1g) OFF
__term_sd_task_pre_model_159 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q4_K_M.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q4_K_M-gguf(2.9g) OFF
__term_sd_task_pre_model_160 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q4_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q4_K_S-gguf(2.74g) OFF
__term_sd_task_pre_model_161 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q5_K_M.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q5_K_M-gguf(3.39g) OFF
__term_sd_task_pre_model_162 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q5_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q5_K_S-gguf(3.29g) OFF
__term_sd_task_pre_model_163 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q6_K.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q6_K-gguf(3.91g) OFF
__term_sd_task_pre_model_164 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-Q8_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q8_0-gguf(5.06g) OFF
__term_sd_task_pre_model_165 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-f16.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-f16-gguf(9.53g) OFF
__term_sd_task_pre_model_166 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_text_encoders/t5-v1_1-xxl-encoder-f32.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-f32-gguf(19.1g) OFF
__term_sd_task_pre_model_167 aria2_download https://huggingface.co/licyk/flux-model/resolve/main/flux_vae/ae.safetensors "${SD_WEBUI_ROOT_PATH}"/models/VAE # ae(335m) OFF
__term_sd_task_pre_model_168 # =====VAE模型===== OFF
__term_sd_task_pre_model_169 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sd_1.5/vae-ft-ema-560000-ema-pruned.safetensors "${SD_WEBUI_ROOT_PATH}"/models/VAE # vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_170 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sd_1.5/vae-ft-mse-840000-ema-pruned.safetensors "${SD_WEBUI_ROOT_PATH}"/models/VAE # VAE模型 vae-ft-mse-840000-ema-pruned(334.6m) ON
__term_sd_task_pre_model_171 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sdxl_1.0/sdxl_vae.safetensors "${SD_WEBUI_ROOT_PATH}"/models/VAE # sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_172 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/sdxl_1.0/sdxl_fp16_fix_vae.safetensors "${SD_WEBUI_ROOT_PATH}"/models/VAE # sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_173 # =====VAE-approx模型===== OFF
__term_sd_task_pre_model_174 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/vae-approx/model.pt "${SD_WEBUI_ROOT_PATH}"/models/VAE-approx # VAE-approx模型 model(0.2m) ON
__term_sd_task_pre_model_175 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/vae-approx/vaeapprox-sdxl.pt "${SD_WEBUI_ROOT_PATH}"/models/VAE-approx # vaeapprox-sdxl(0.2m) ON
__term_sd_task_pre_model_176 aria2_download https://huggingface.co/licyk/sd-vae/resolve/main/vae-approx/vaeapprox-sd3.pt "${SD_WEBUI_ROOT_PATH}"/models/VAE-approx # vaeapprox-sd3(0.2m) OFF
__term_sd_task_pre_model_177 # =====放大模型===== OFF
__term_sd_task_pre_model_178 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/Codeformer/codeformer-v0.1.0.pth "${SD_WEBUI_ROOT_PATH}"/models/Codeformer # codeformer-v0.1.0(376.6m) OFF
__term_sd_task_pre_model_179 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_2_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_2_x2(139.7m) OFF
__term_sd_task_pre_model_180 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_2_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_2_x3(140.4m) OFF
__term_sd_task_pre_model_181 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_2_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_2_x4(140.3m) OFF
__term_sd_task_pre_model_182 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_S_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_S_x2(87.7m) OFF
__term_sd_task_pre_model_183 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_S_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_S_x3(88.4m) OFF
__term_sd_task_pre_model_184 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_S_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_S_x4(88.2m) OFF
__term_sd_task_pre_model_185 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_light_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_light_x2(45.7m) OFF
__term_sd_task_pre_model_186 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_light_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_light_x3(45.7m) OFF
__term_sd_task_pre_model_187 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_light_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_light_x4(45.8m) OFF
__term_sd_task_pre_model_188 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_x2(154.1m) OFF
__term_sd_task_pre_model_189 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_x3(154.8m) OFF
__term_sd_task_pre_model_190 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/DAT/DAT_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_x4(154.7m) OFF
__term_sd_task_pre_model_191 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/16xPSNR.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 16xPSNR(67.2m) OFF
__term_sd_task_pre_model_192 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x-ITF-SkinDiffDetail-Lite-v1.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x-ITF-SkinDiffDetail-Lite-v1(20.1m) OFF
__term_sd_task_pre_model_193 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x_NMKD-BrightenRedux_200k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x_NMKD-BrightenRedux_200k(66.6m) OFF
__term_sd_task_pre_model_194 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x_NMKD-YandereInpaint_375000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x_NMKD-YandereInpaint_375000_G(66.6m) OFF
__term_sd_task_pre_model_195 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x_NMKDDetoon_97500_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x_NMKDDetoon_97500_G(66.6m) OFF
__term_sd_task_pre_model_196 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x_NoiseToner-Poisson-Detailed_108000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x_NoiseToner-Poisson-Detailed_108000_G(66.6m) OFF
__term_sd_task_pre_model_197 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/1x_NoiseToner-Uniform-Detailed_100000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x_NoiseToner-Uniform-Detailed_100000_G(66.6m) OFF
__term_sd_task_pre_model_198 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x-UltraSharp.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x-UltraSharp(66.9m) OFF
__term_sd_task_pre_model_199 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4xPSNR.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4xPSNR(66.9m) OFF
__term_sd_task_pre_model_200 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_CountryRoads_377000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_CountryRoads_377000_G(66.9m) OFF
__term_sd_task_pre_model_201 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_Fatality_Comix_260000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_Fatality_Comix_260000_G(66.9m) OFF
__term_sd_task_pre_model_202 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-Siax_200k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-Siax_200k(66.9m) OFF
__term_sd_task_pre_model_203 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-Superscale-Artisoftject_210000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-Superscale-Artisoftject_210000_G(66.9m) OFF
__term_sd_task_pre_model_204 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-Superscale-SP_178000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-Superscale-SP_178000_G(66.9m) ON
__term_sd_task_pre_model_205 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-UltraYandere-Lite_280k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-UltraYandere-Lite_280k(20.1m) OFF
__term_sd_task_pre_model_206 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-UltraYandere_300k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-UltraYandere_300k(66.9m) OFF
__term_sd_task_pre_model_207 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKD-YandereNeoXL_200k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-YandereNeoXL_200k(66.9m) OFF
__term_sd_task_pre_model_208 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NMKDSuperscale_Artisoft_120000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKDSuperscale_Artisoft_120000_G(67.1m) OFF
__term_sd_task_pre_model_209 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_NickelbackFS_72000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NickelbackFS_72000_G(67.1m) OFF
__term_sd_task_pre_model_210 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_Nickelback_70000G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_Nickelback_70000G(66.9m) OFF
__term_sd_task_pre_model_211 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_RealisticRescaler_100000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_RealisticRescaler_100000_G(134.1m) OFF
__term_sd_task_pre_model_212 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_Valar_v1.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_Valar_v1(67.5m) OFF
__term_sd_task_pre_model_213 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_fatal_Anime_500000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_fatal_Anime_500000_G(66.9m) OFF
__term_sd_task_pre_model_214 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/4x_foolhardy_Remacri.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_foolhardy_Remacri(67m) OFF
__term_sd_task_pre_model_215 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/8xPSNR.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 8xPSNR(67.1m) OFF
__term_sd_task_pre_model_216 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/8x_NMKD-Superscale_150000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 8x_NMKD-Superscale_150000_G(67.1m) OFF
__term_sd_task_pre_model_217 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/8x_NMKD-Typescale_175k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 8x_NMKD-Typescale_175k(67.1m) OFF
__term_sd_task_pre_model_218 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/A_ESRGAN_Single.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # A_ESRGAN_Single(134.1m) OFF
__term_sd_task_pre_model_219 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/BSRGAN.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # BSRGAN(67.1m) OFF
__term_sd_task_pre_model_220 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/BSRGANx2.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # BSRGANx2(66.8m) OFF
__term_sd_task_pre_model_221 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/BSRNet.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # BSRNet(67.1m) OFF
__term_sd_task_pre_model_222 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/ESRGAN_4x.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # ESRGAN_4x(66.9m) OFF
__term_sd_task_pre_model_223 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/LADDIER1_282500_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # LADDIER1_282500_G(66.9m) OFF
__term_sd_task_pre_model_224 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Neutral_115000_swaG.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_UniversalUpscalerV2-Neutral_115000_swaG(66.9m) OFF
__term_sd_task_pre_model_225 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Sharp_101000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_UniversalUpscalerV2-Sharp_101000_G(66.9m) OFF
__term_sd_task_pre_model_226 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Sharper_103000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_UniversalUpscalerV2-Sharper_103000_G(66.9m) OFF
__term_sd_task_pre_model_227 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/UniversalUpscaler/Legacy/4x_UniversalUpscaler-Detailed_155000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_UniversalUpscaler-Detailed_155000_G(66.9m) OFF
__term_sd_task_pre_model_228 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/UniversalUpscaler/Legacy/4x_UniversalUpscaler-Soft_190000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_UniversalUpscaler-Soft_190000_G(66.9m) OFF
__term_sd_task_pre_model_229 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/WaifuGAN_v3_30000.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # WaifuGAN_v3_30000(66.9m) OFF
__term_sd_task_pre_model_230 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/lollypop.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # lollypop(66.9m) OFF
__term_sd_task_pre_model_231 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/ESRGAN/sudo_rife4_269.662_testV1_scale1.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # sudo_rife4_269.662_testV1_scale1(33.7m) OFF
__term_sd_task_pre_model_232 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/GFPGAN/GFPGANv1.3.pth "${SD_WEBUI_ROOT_PATH}"/models/GFPGAN # GFPGANv1.3(348.6m) OFF
__term_sd_task_pre_model_233 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/GFPGAN/GFPGANv1.4.pth "${SD_WEBUI_ROOT_PATH}"/models/GFPGAN # GFPGANv1.4(348.6m) OFF
__term_sd_task_pre_model_234 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/GFPGAN/detection_Resnet50_Final.pth "${SD_WEBUI_ROOT_PATH}"/models/GFPGAN # detection_Resnet50_Final(109.5m) OFF
__term_sd_task_pre_model_235 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/GFPGAN/parsing_bisenet.pth "${SD_WEBUI_ROOT_PATH}"/models/GFPGAN # parsing_bisenet(12.2m) OFF
__term_sd_task_pre_model_236 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/GFPGAN/parsing_parsenet.pth "${SD_WEBUI_ROOT_PATH}"/models/GFPGAN # parsing_parsenet(85.3m) OFF
__term_sd_task_pre_model_237 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/RealESRGAN/RealESRGAN_x4plus.pth "${SD_WEBUI_ROOT_PATH}"/models/RealESRGAN # RealESRGAN_x4plus(67m) ON
__term_sd_task_pre_model_238 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/RealESRGAN/RealESRGAN_x4plus_anime_6B.pth "${SD_WEBUI_ROOT_PATH}"/models/RealESRGAN # RealESRGAN_x4plus_anime_6B(17.9m) ON
__term_sd_task_pre_model_239 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DF2K_s64w8_SwinIR-M_x2(67.2m) OFF
__term_sd_task_pre_model_240 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DF2K_s64w8_SwinIR-M_x3(68m) OFF
__term_sd_task_pre_model_241 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DF2K_s64w8_SwinIR-M_x4(67.8m) OFF
__term_sd_task_pre_model_242 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x8.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DF2K_s64w8_SwinIR-M_x8(68.4m) OFF
__term_sd_task_pre_model_243 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x2(59m) OFF
__term_sd_task_pre_model_244 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x3(59.7m) OFF
__term_sd_task_pre_model_245 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x4(59.6m) OFF
__term_sd_task_pre_model_246 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x8.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x8(60.2m) OFF
__term_sd_task_pre_model_247 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/Swin2SR_ClassicalSR_X2_64.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # Swin2SR_ClassicalSR_X2_64(68.7m) OFF
__term_sd_task_pre_model_248 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/Swin2SR_ClassicalSR_X4_64.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # Swin2SR_ClassicalSR_X4_64(69.3m) OFF
__term_sd_task_pre_model_249 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/Swin2SR_CompressedSR_X4_48.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # Swin2SR_CompressedSR_X4_48(61.1m) OFF
__term_sd_task_pre_model_250 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR(68.6m) OFF
__term_sd_task_pre_model_251 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/SwinIR/SwinIR_4x.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # SwinIR_4x(142.4m) OFF
__term_sd_task_pre_model_252 # =====图生图反推Tag模型===== OFF
__term_sd_task_pre_model_253 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/BLIP/model_base_caption_capfilt_large.pth "${SD_WEBUI_ROOT_PATH}"/models/BLIP # BLIP模型 model_base_caption_capfilt_large(896m) OFF
__term_sd_task_pre_model_254 aria2_download https://huggingface.co/licyk/sd-upscaler-models/resolve/main/torch_deepdanbooru/model-resnet_custom_v3.pt "${SD_WEBUI_ROOT_PATH}"/models/torch_deepdanbooru # deepdanbooru模型 model-resnet_custom_v3(644.1m) OFF
__term_sd_task_pre_model_255 # =====Embedding模型===== OFF
__term_sd_task_pre_model_256 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/EasyNegativeV2.safetensors "${SD_WEBUI_ROOT_PATH}"/embeddings # embeddings模型 EasyNegativeV2(0.1m) ON
__term_sd_task_pre_model_257 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/bad-artist-anime.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # bad-artist-anime(0.1m) ON
__term_sd_task_pre_model_258 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/bad-artist.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # bad-artist(0.1m) ON
__term_sd_task_pre_model_259 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/bad-hands-5.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # bad-hands-5(0.1m) ON
__term_sd_task_pre_model_260 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/bad-image-v2-39000.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # bad-image-v2-39000(0.1m) ON
__term_sd_task_pre_model_261 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/bad_prompt_version2.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # bad_prompt_version2(0.1m) ON
__term_sd_task_pre_model_262 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/ng_deepnegative_v1_75t.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # ng_deepnegative_v1_75t(0.1m) ON
__term_sd_task_pre_model_263 aria2_download https://huggingface.co/licyk/sd-embeddings/resolve/main/sd_1.5/verybadimagenegative_v1.3.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # verybadimagenegative_v1.3(0.1m) ON
|
2301_81996401/term-sd
|
install/sd_webui/sd_webui_hf_model.sh
|
Shell
|
agpl-3.0
| 54,867
|
__term_sd_task_pre_model_1 # =====SD1.5大模型===== OFF
__term_sd_task_pre_model_2 get_modelscope_model licyks/sd-model/master/sd_1.5/v1-5-pruned-emaonly.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # 大模型 v1-5-pruned-emaonly(4.27g) OFF
__term_sd_task_pre_model_3 get_modelscope_model licyks/sd-model/master/sd_1.5/animefull-final-pruned.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animefull-final-pruned(4.27g) OFF
__term_sd_task_pre_model_4 get_modelscope_model licyks/sd-model/master/sd_1.5/nai1-artist_all_in_one_merge.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # nai1-artist_all_in_one_merge(2.13g) OFF
__term_sd_task_pre_model_5 get_modelscope_model licyks/sd-model/master/sd_1.5/Counterfeit-V3.0_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Counterfeit-V3.0(4.24g) OFF
__term_sd_task_pre_model_6 get_modelscope_model licyks/sd-model/master/sd_1.5/cetusMix_Whalefall2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # cetusMix_Whalefall2(3.85g) OFF
__term_sd_task_pre_model_7 get_modelscope_model licyks/sd-model/master/sd_1.5/cuteyukimixAdorable_neochapter3.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # cuteyukimixAdorable_neochapter3(2.3g) OFF
__term_sd_task_pre_model_8 get_modelscope_model licyks/sd-model/master/sd_1.5/ekmix-pastel-fp16-no-ema.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # ekmix-pastel(2.13g) OFF
__term_sd_task_pre_model_9 get_modelscope_model licyks/sd-model/master/sd_1.5/ex2K_sse2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # ex2K_sse2(2.38g) OFF
__term_sd_task_pre_model_10 get_modelscope_model licyks/sd-model/master/sd_1.5/kohakuV5_rev2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohakuV5_rev2(2.13g) OFF
__term_sd_task_pre_model_11 get_modelscope_model licyks/sd-model/master/sd_1.5/meinamix_meinaV11.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # meinamix_meinaV11(2.13g) OFF
__term_sd_task_pre_model_12 get_modelscope_model licyks/sd-model/master/sd_1.5/oukaStar_10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # oukaStar_10(5.43g) OFF
__term_sd_task_pre_model_13 get_modelscope_model licyks/sd-model/master/sd_1.5/pastelMixStylizedAnime_pastelMixPrunedFP16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # pastelMixStylizedAnime(2.13g) OFF
__term_sd_task_pre_model_14 get_modelscope_model licyks/sd-model/master/sd_1.5/rabbit_v6.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # rabbit_v6(1.97g) OFF
__term_sd_task_pre_model_15 get_modelscope_model licyks/sd-model/master/sd_1.5/sweetSugarSyndrome_rev15.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sweetSugarSyndrome_rev15(2.13g) OFF
__term_sd_task_pre_model_16 get_modelscope_model licyks/sd-model/master/sd_1.5/AnythingV5Ink_ink.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # AnythingV5Ink_ink(2.13g) OFF
__term_sd_task_pre_model_17 get_modelscope_model licyks/sd-model/master/sd_1.5/bartstyledbBlueArchiveArtStyleFineTunedModel_v10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # bartstyledbBlueArchiveArtStyle(2.13g) OFF
__term_sd_task_pre_model_18 get_modelscope_model licyks/sd-model/master/sd_1.5/meinapastel_v6Pastel.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # meinapastel_v6(2.13g) OFF
__term_sd_task_pre_model_19 get_modelscope_model licyks/sd-model/master/sd_1.5/qteamixQ_omegaFp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # qteamix(2.13g) OFF
__term_sd_task_pre_model_20 get_modelscope_model licyks/sd-model/master/sd_1.5/tmndMix_tmndMixSPRAINBOW.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # tmndMix(2.13g) OFF
__term_sd_task_pre_model_21 # =====SD2.1大模型===== OFF
__term_sd_task_pre_model_22 get_modelscope_model licyks/sd-model/master/sd_2.1/v2-1_768-ema-pruned.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # v2-1_768-ema-pruned(5.21g) OFF
__term_sd_task_pre_model_23 get_modelscope_model licyks/sd-model/master/sd_2.1/wd-1-4-anime_e2.ckpt "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # wd-1-4-anime_e2(5.16g) OFF
__term_sd_task_pre_model_24 get_modelscope_model licyks/sd-model/master/sd_2.1/wd-mofu-fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # wd-mofu-fp16(2.58g) OFF
__term_sd_task_pre_model_25 # =====SDXL大模型===== OFF
__term_sd_task_pre_model_26 get_modelscope_model licyks/sd-lora/master/sdxl/sd_xl_offset_example-lora_1.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Lora # sd_xl_offset_example-lora_1.0(49.6m) OFF
__term_sd_task_pre_model_27 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_base_1.0_0.9vae.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd_xl_base_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_28 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_refiner_1.0_0.9vae.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd_xl_refiner_1.0_0.9vae(6.94g) OFF
__term_sd_task_pre_model_29 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_turbo_1.0_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd_xl_turbo_1.0_fp16(6.94g) OFF
__term_sd_task_pre_model_30 get_modelscope_model licyks/sd-model/master/sdxl_1.0/cosxl.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # cosxl(6.94g) OFF
__term_sd_task_pre_model_31 get_modelscope_model licyks/sd-model/master/sdxl_1.0/cosxl_edit.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # cosxl_edit(6.94g) OFF
__term_sd_task_pre_model_32 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.0-base.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-3.0-base(6.94g) OFF
__term_sd_task_pre_model_33 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-3.0(6.94g) OFF
__term_sd_task_pre_model_34 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-3.1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-3.1(6.94g) OFF
__term_sd_task_pre_model_35 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-4.0(6.94g) OFF
__term_sd_task_pre_model_36 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0-opt.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-4.0-opt(6.94g) OFF
__term_sd_task_pre_model_37 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animagine-xl-4.0-zero.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animagine-xl-4.0-zero(6.94g) OFF
__term_sd_task_pre_model_38 get_modelscope_model licyks/sd-model/master/sdxl_1.0/holodayo-xl-2.1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # holodayo-xl-2.1(6.94g) OFF
__term_sd_task_pre_model_39 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kivotos-xl-2.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kivotos-xl-2.0(6.94g) OFF
__term_sd_task_pre_model_40 get_modelscope_model licyks/sd-model/master/sdxl_1.0/clandestine-xl-1.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # clandestine-xl-1.0(6.94g) OFF
__term_sd_task_pre_model_41 get_modelscope_model licyks/sd-model/master/sdxl_1.0/UrangDiffusion-1.1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # UrangDiffusion-1.1(6.94g) OFF
__term_sd_task_pre_model_42 get_modelscope_model licyks/sd-model/master/sdxl_1.0/RaeDiffusion-XL-v2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # RaeDiffusion-XL-v2(6.94g) OFF
__term_sd_task_pre_model_43 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sd_xl_anime_V52.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd_xl_anime_V52(6.94g) OFF
__term_sd_task_pre_model_44 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-delta-rev1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohaku-xl-delta-rev1(6.94g) OFF
__term_sd_task_pre_model_45 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohakuXLEpsilon_rev1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohakuXLEpsilon_rev1(6.94g) OFF
__term_sd_task_pre_model_46 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-epsilon-rev2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohaku-xl-epsilon-rev2(6.94g) OFF
__term_sd_task_pre_model_47 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-epsilon-rev3.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohaku-xl-epsilon-rev3(6.94g) OFF
__term_sd_task_pre_model_48 get_modelscope_model licyks/sd-model/master/sdxl_1.0/kohaku-xl-zeta.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # kohaku-xl-zeta(6.94g) OFF
__term_sd_task_pre_model_49 get_modelscope_model licyks/sd-model/master/sdxl_1.0/starryXLV52_v52.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # starryXLV52_v52(6.94g) OFF
__term_sd_task_pre_model_50 get_modelscope_model licyks/sd-model/master/sdxl_1.0/heartOfAppleXL_v20.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # heartOfAppleXL_v20(6.94g) OFF
__term_sd_task_pre_model_51 get_modelscope_model licyks/sd-model/master/sdxl_1.0/heartOfAppleXL_v30.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # heartOfAppleXL_v30(6.94g) OFF
__term_sd_task_pre_model_52 get_modelscope_model licyks/sd-model/master/sdxl_1.0/baxlBartstylexlBlueArchiveFlatCelluloid_xlv1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # baxlBartstylexlBlueArchiveFlatCelluloid_xlv1(6.94g) OFF
__term_sd_task_pre_model_53 get_modelscope_model licyks/sd-model/master/sdxl_1.0/baxlBlueArchiveFlatCelluloidStyle_xlv3.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # baxlBlueArchiveFlatCelluloidStyle_xlv3(6.94g) OFF
__term_sd_task_pre_model_54 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sanaexlAnimeV10_v10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sanaexlAnimeV10_v10(6.94g) OFF
__term_sd_task_pre_model_55 get_modelscope_model licyks/sd-model/master/sdxl_1.0/sanaexlAnimeV10_v11.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sanaexlAnimeV10_v11(6.94g) OFF
__term_sd_task_pre_model_56 get_modelscope_model licyks/sd-model/master/sdxl_1.0/SanaeXL-Anime-v1.2-aesthetic.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # SanaeXL-Anime-v1.2-aesthetic(6.94g) OFF
__term_sd_task_pre_model_57 get_modelscope_model licyks/sd-model/master/sdxl_1.0/SanaeXL-Anime-v1.3-aesthetic.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # SanaeXL-Anime-v1.3-aesthetic(6.94g) OFF
__term_sd_task_pre_model_58 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v0.1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v0.1(6.94g) OFF
__term_sd_task_pre_model_59 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v0.1-GUIDED.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v0.1-GUIDED(6.94g) OFF
__term_sd_task_pre_model_60 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v1.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v1.0(6.94g) ON
__term_sd_task_pre_model_61 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v1.1.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v1.1(6.94g) OFF
__term_sd_task_pre_model_62 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v2.0-stable.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v2.0-stable(6.94g) OFF
__term_sd_task_pre_model_63 get_modelscope_model licyks/sd-model/master/sdxl_1.0/Illustrious-XL-v2.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # Illustrious-XL-v2.0(6.94g) OFF
__term_sd_task_pre_model_64 get_modelscope_model licyks/sd-model/master/sdxl_1.0/jruTheJourneyRemains_v25XL.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # jruTheJourneyRemains_v25XL(6.94g) OFF
__term_sd_task_pre_model_65 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_illustriousxl10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # PVCStyleModelMovable_illustriousxl10(6.94g) OFF
__term_sd_task_pre_model_66 get_modelscope_model licyks/sd-model/master/sdxl_1.0/miaomiaoHarem_v15a.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # miaomiaoHarem_v15a(6.94g) OFF
__term_sd_task_pre_model_67 get_modelscope_model licyks/sd-model/master/sdxl_1.0/waiNSFWIllustrious_v80.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # waiNSFWIllustrious_v80(6.94g) OFF
__term_sd_task_pre_model_68 get_modelscope_model licyks/sd-model/master/sdxl_1.0/tIllunai3_v4.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # tIllunai3_v4(6.94g) OFF
__term_sd_task_pre_model_69 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_earlyAccessVersion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_earlyAccessVersion(6.94g) OFF
__term_sd_task_pre_model_70 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred05Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_epsilonPred05Version(6.94g) OFF
__term_sd_task_pre_model_71 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred075.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_epsilonPred075(6.94g) OFF
__term_sd_task_pre_model_72 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred077.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_epsilonPred077(6.94g) OFF
__term_sd_task_pre_model_73 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred10Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_epsilonPred10Version(6.94g) OFF
__term_sd_task_pre_model_74 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_epsilonPred11Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_epsilonPred11Version(6.94g) OFF
__term_sd_task_pre_model_75 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPredTestVersion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPredTestVersion(6.94g) OFF
__term_sd_task_pre_model_76 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred05Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred05Version(6.94g) OFF
__term_sd_task_pre_model_77 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred06Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred06Version(6.94g) OFF
__term_sd_task_pre_model_78 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred065SVersion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred065SVersion(6.94g) OFF
__term_sd_task_pre_model_79 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred075SVersion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred075SVersion(6.94g) OFF
__term_sd_task_pre_model_80 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred09RVersion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred09RVersion(6.94g) OFF
__term_sd_task_pre_model_81 get_modelscope_model licyks/sd-model/master/sdxl_1.0/noobaiXLNAIXL_vPred10Version.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # noobaiXLNAIXL_vPred10Version(6.94g) OFF
__term_sd_task_pre_model_82 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_nbxl12.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # PVCStyleModelMovable_nbxl12(6.94g) OFF
__term_sd_task_pre_model_83 get_modelscope_model licyks/sd-model/master/sdxl_1.0/PVCStyleModelMovable_nbxlVPredV10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # PVCStyleModelMovable_nbxlVPredV10(6.94g) OFF
__term_sd_task_pre_model_84 get_modelscope_model licyks/sd-model/master/sdxl_1.0/ponyDiffusionV6XL_v6StartWithThisOne.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # ponyDiffusionV6XL_v6(6.94g) OFF
__term_sd_task_pre_model_85 get_modelscope_model licyks/sd-model/master/sdxl_1.0/pdForAnime_v20.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # pdForAnime_v20(7.11g) OFF
__term_sd_task_pre_model_86 get_modelscope_model licyks/sd-model/master/sdxl_1.0/tPonynai3_v51WeightOptimized.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # tPonynai3_v51WeightOptimized(6.94g) OFF
__term_sd_task_pre_model_87 get_modelscope_model licyks/sd-model/master/sdxl_1.0/omegaPonyXLAnime_v20.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # omegaPonyXLAnime_v20(6.94g) OFF
__term_sd_task_pre_model_88 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animeIllustDiffusion_v061.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animeIllustDiffusion_v061(6.94g) OFF
__term_sd_task_pre_model_89 get_modelscope_model licyks/sd-model/master/sdxl_1.0/artiwaifuDiffusion_v10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # artiwaifuDiffusion_v10(6.94g) OFF
__term_sd_task_pre_model_90 get_modelscope_model licyks/sd-model/master/sdxl_1.0/artiwaifu-diffusion-v2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # artiwaifu-diffusion-v2(6.94g) OFF
__term_sd_task_pre_model_91 get_modelscope_model licyks/sd-model/master/sdxl_1.0/AnythingXL_xl.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # AnythingXL_xl(6.94g) OFF
__term_sd_task_pre_model_92 get_modelscope_model licyks/sd-model/master/sdxl_1.0/abyssorangeXLElse_v10.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # abyssorangeXLElse_v10(6.94g) OFF
__term_sd_task_pre_model_93 get_modelscope_model licyks/sd-model/master/sdxl_1.0/animaPencilXL_v200.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # animaPencilXL_v200(6.94g) OFF
__term_sd_task_pre_model_94 get_modelscope_model licyks/sd-model/master/sdxl_1.0/bluePencilXL_v401.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # bluePencilXL_v401(6.94g) OFF
__term_sd_task_pre_model_95 get_modelscope_model licyks/sd-model/master/sdxl_1.0/nekorayxl_v06W3.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # nekorayxl_v06W3(6.94g) OFF
__term_sd_task_pre_model_96 get_modelscope_model licyks/sd-model/master/sdxl_1.0/CounterfeitXL-V1.0.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # CounterfeitXL-V1.0(6.94g) OFF
__term_sd_task_pre_model_97 # =====SD3大模型===== OFF
__term_sd_task_pre_model_98 get_modelscope_model licyks/sd-3-model/master/sd3_medium.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3_medium(4.34g) OFF
__term_sd_task_pre_model_99 get_modelscope_model licyks/sd-3-model/master/sd3_medium_incl_clips.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3_medium_incl_clips(5.97g) OFF
__term_sd_task_pre_model_100 get_modelscope_model licyks/sd-3-model/master/sd3_medium_incl_clips_t5xxlfp8.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3_medium_incl_clips_t5xxlfp8(10.87g) OFF
__term_sd_task_pre_model_101 get_modelscope_model licyks/sd-3-model/master/sd3.5_large.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3.5_large(16.5g) OFF
__term_sd_task_pre_model_102 get_modelscope_model licyks/sd-3-model/master/sd3.5_large_fp8_scaled.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3.5_large_fp8_scaled(14.9g) OFF
__term_sd_task_pre_model_103 get_modelscope_model licyks/sd-3-model/master/sd3.5_large_turbo.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3.5_large_turbo(16.5g) OFF
__term_sd_task_pre_model_104 get_modelscope_model licyks/sd-3-model/master/sd3.5_medium.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3.5_medium(5.1g) OFF
__term_sd_task_pre_model_105 get_modelscope_model licyks/sd-3-model/master/sd3.5_medium_incl_clips_t5xxlfp8scaled.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # sd3.5_medium_incl_clips_t5xxlfp8scaled(11.6g) OFF
__term_sd_task_pre_model_106 get_modelscope_model licyks/sd-3-model/master/emi3.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # emi3(16.5g) OFF
__term_sd_task_pre_model_107 # =====SD3文本编码器===== OFF
__term_sd_task_pre_model_108 get_modelscope_model licyks/sd-3-model/master/text_encoders/clip_g.safetensors "${SD_WEBUI_ROOT_PATH}"/models/CLIP # clip_g(1.39g) OFF
__term_sd_task_pre_model_109 get_modelscope_model licyks/sd-3-model/master/text_encoders/clip_l.safetensors "${SD_WEBUI_ROOT_PATH}"/models/CLIP # clip_l(246.1m) OFF
__term_sd_task_pre_model_110 get_modelscope_model licyks/sd-3-model/master/text_encoders/t5xxl_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/CLIP # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_111 get_modelscope_model licyks/sd-3-model/master/text_encoders/t5xxl_fp8_e4m3fn.safetensors "${SD_WEBUI_ROOT_PATH}"/models/CLIP # t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_112 get_modelscope_model licyks/sd-3-model/master/text_encoders/t5xxl_fp8_e4m3fn_scaled.safetensors "${SD_WEBUI_ROOT_PATH}"/models/CLIP # t5xxl_fp8_e4m3fn_scaled(5.16g) OFF
__term_sd_task_pre_model_113 # =====FLUX模型===== OFF
__term_sd_task_pre_model_114 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev(23.8g) OFF
__term_sd_task_pre_model_115 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-fp8.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-fp8(17.2g) OFF
__term_sd_task_pre_model_116 get_modelscope_model licyks/flux-model/master/flux_1/flux_dev_fp8_scaled_diffusion_model.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux_dev_fp8_scaled_diffusion_model(11.9g) OFF
__term_sd_task_pre_model_117 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-bnb-nf4-v2.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-bnb-nf4-v2(12g) OFF
__term_sd_task_pre_model_118 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-bnb-nf4.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-bnb-nf4(11.5g) OFF
__term_sd_task_pre_model_119 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q2_K.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q2_K-gguf(4.03g) OFF
__term_sd_task_pre_model_120 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q3_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q3_K_S-gguf(5.23g) OFF
__term_sd_task_pre_model_121 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q4_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q4_0-gguf(6.79g) OFF
__term_sd_task_pre_model_122 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q4_1.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q4_1-gguf(7.53g) OFF
__term_sd_task_pre_model_123 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q4_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q4_K_S-gguf(6.81g) OFF
__term_sd_task_pre_model_124 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q5_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q5_0-gguf(8.27g) OFF
__term_sd_task_pre_model_125 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q5_1.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q5_1-gguf(9.01g) OFF
__term_sd_task_pre_model_126 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q5_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q5_K_S-gguf(8.29g) OFF
__term_sd_task_pre_model_127 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q6_K.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q6_K-gguf(9.86g) OFF
__term_sd_task_pre_model_128 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-Q8_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_129 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-F16.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_130 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell(23.8g) OFF
__term_sd_task_pre_model_131 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-fp8.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-fp8(17.2g) OFF
__term_sd_task_pre_model_132 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q2_K.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q2_K-gguf(4.01g) OFF
__term_sd_task_pre_model_133 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q3_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q3_K_S-gguf(5.21g) OFF
__term_sd_task_pre_model_134 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q4_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q4_0-gguf(6.77g) OFF
__term_sd_task_pre_model_135 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q4_1.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q4_1-gguf(7.51g) OFF
__term_sd_task_pre_model_136 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q4_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q4_K_S-gguf(6.78g) OFF
__term_sd_task_pre_model_137 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q5_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q5_0-gguf(8.25g) OFF
__term_sd_task_pre_model_138 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q5_1.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q5_1-gguf(8.99g) OFF
__term_sd_task_pre_model_139 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q5_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q5_K_S-gguf(8.26g) OFF
__term_sd_task_pre_model_140 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q6_K.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q6_K-gguf(9.83g) OFF
__term_sd_task_pre_model_141 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-Q8_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-Q8_0-gguf(12.7g) OFF
__term_sd_task_pre_model_142 get_modelscope_model licyks/flux-model/master/flux_1/flux1-schnell-F16.gguf "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-schnell-F16-gguf(23.8g) OFF
__term_sd_task_pre_model_143 get_modelscope_model licyks/flux-model/master/flux_1/ashen0209-flux1-dev2pro.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # ashen0209-flux1-dev2pro(23.8g) OFF
__term_sd_task_pre_model_144 get_modelscope_model licyks/flux-model/master/flux_1/jimmycarter-LibreFLUX.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # jimmycarter-LibreFLUX(23.8g) OFF
__term_sd_task_pre_model_145 get_modelscope_model licyks/flux-model/master/flux_1/nyanko7-flux-dev-de-distill.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # nyanko7-flux-dev-de-distill(23.8g) OFF
__term_sd_task_pre_model_146 get_modelscope_model licyks/flux-model/master/flux_1/shuttle-3-diffusion.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # shuttle-3-diffusion(23.8g) OFF
__term_sd_task_pre_model_147 get_modelscope_model licyks/flux-model/master/flux_1/flux1-krea-dev_fp8_scaled.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-krea-dev_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_148 get_modelscope_model licyks/flux-model/master/flux_1/flux1-krea-dev.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-krea-dev(23.8g) OFF
__term_sd_task_pre_model_149 get_modelscope_model licyks/flux-model/master/flux_1/flux1-dev-kontext_fp8_scaled.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-dev-kontext_fp8_scaled(23.8g) OFF
__term_sd_task_pre_model_150 get_modelscope_model licyks/flux-model/master/flux_1/flux1-kontext-dev.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # flux1-kontext-dev(23.8g) OFF
__term_sd_task_pre_model_151 get_modelscope_model licyks/flux-model/master/flux_1/chroma-unlocked-v50.safetensors "${SD_WEBUI_ROOT_PATH}"/models/Stable-diffusion # chroma-unlocked-v50(23.8g) OFF
__term_sd_task_pre_model_152 # =====FLUX-文本编码器/VAE模型===== OFF
__term_sd_task_pre_model_153 get_modelscope_model licyks/flux-model/master/flux_text_encoders/clip_l.safetensors "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # clip_l(246.1m) OFF
__term_sd_task_pre_model_154 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5xxl_fp16.safetensors "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5xxl_fp16(9.79g) OFF
__term_sd_task_pre_model_155 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5xxl_fp8_e4m3fn.safetensors "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5xxl_fp8_e4m3fn(4.89g) OFF
__term_sd_task_pre_model_156 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_L.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q3_K_L-gguf(2.46g) OFF
__term_sd_task_pre_model_157 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_M.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q3_K_M-gguf(2.3g) OFF
__term_sd_task_pre_model_158 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q3_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q3_K_S-gguf(2.1g) OFF
__term_sd_task_pre_model_159 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q4_K_M.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q4_K_M-gguf(2.9g) OFF
__term_sd_task_pre_model_160 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q4_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q4_K_S-gguf(2.74g) OFF
__term_sd_task_pre_model_161 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q5_K_M.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q5_K_M-gguf(3.39g) OFF
__term_sd_task_pre_model_162 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q5_K_S.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q5_K_S-gguf(3.29g) OFF
__term_sd_task_pre_model_163 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q6_K.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q6_K-gguf(3.91g) OFF
__term_sd_task_pre_model_164 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-Q8_0.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-Q8_0-gguf(5.06g) OFF
__term_sd_task_pre_model_165 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-f16.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-f16-gguf(9.53g) OFF
__term_sd_task_pre_model_166 get_modelscope_model licyks/flux-model/master/flux_text_encoders/t5-v1_1-xxl-encoder-f32.gguf "${SD_WEBUI_ROOT_PATH}"/models/text_encoder # t5-v1_1-xxl-encoder-f32-gguf(19.1g) OFF
__term_sd_task_pre_model_167 get_modelscope_model licyks/flux-model/master/flux_vae/ae.safetensors "${SD_WEBUI_ROOT_PATH}"/models/VAE # ae(335m) OFF
__term_sd_task_pre_model_168 # =====VAE模型===== OFF
__term_sd_task_pre_model_169 get_modelscope_model licyks/sd-vae/master/sd_1.5/vae-ft-ema-560000-ema-pruned.safetensors "${SD_WEBUI_ROOT_PATH}"/models/VAE # VAE模型 vae-ft-ema-560000-ema-pruned(334.6m) OFF
__term_sd_task_pre_model_170 get_modelscope_model licyks/sd-vae/master/sd_1.5/vae-ft-mse-840000-ema-pruned.safetensors "${SD_WEBUI_ROOT_PATH}"/models/VAE # vae-ft-mse-840000-ema-pruned(334.6m) ON
__term_sd_task_pre_model_171 get_modelscope_model licyks/sd-vae/master/sdxl_1.0/sdxl_vae.safetensors "${SD_WEBUI_ROOT_PATH}"/models/VAE # sdxl_vae(334.6m) OFF
__term_sd_task_pre_model_172 get_modelscope_model licyks/sd-vae/master/sdxl_1.0/sdxl_fp16_fix_vae.safetensors "${SD_WEBUI_ROOT_PATH}"/models/VAE # sdxl_fp16_fix_vae(334.6m) OFF
__term_sd_task_pre_model_173 # =====VAE-approx模型===== OFF
__term_sd_task_pre_model_174 get_modelscope_model licyks/sd-vae/master/vae-approx/model.pt "${SD_WEBUI_ROOT_PATH}"/models/VAE-approx # VAE-approx模型 model(0.2m) ON
__term_sd_task_pre_model_175 get_modelscope_model licyks/sd-vae/master/vae-approx/vaeapprox-sdxl.pt "${SD_WEBUI_ROOT_PATH}"/models/VAE-approx # vaeapprox-sdxl(0.2m) ON
__term_sd_task_pre_model_176 get_modelscope_model licyks/sd-vae/master/vae-approx/vaeapprox-sd3.pt "${SD_WEBUI_ROOT_PATH}"/models/VAE-approx # vaeapprox-sd3(0.2m) OFF
__term_sd_task_pre_model_177 # =====放大模型===== OFF
__term_sd_task_pre_model_178 get_modelscope_model licyks/sd-upscaler-models/master/Codeformer/codeformer-v0.1.0.pth "${SD_WEBUI_ROOT_PATH}"/models/Codeformer # codeformer-v0.1.0(376.6m) OFF
__term_sd_task_pre_model_179 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_2_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_2_x2(139.7m) OFF
__term_sd_task_pre_model_180 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_2_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_2_x3(140.4m) OFF
__term_sd_task_pre_model_181 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_2_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_2_x4(140.3m) OFF
__term_sd_task_pre_model_182 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_S_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_S_x2(87.7m) OFF
__term_sd_task_pre_model_183 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_S_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_S_x3(88.4m) OFF
__term_sd_task_pre_model_184 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_S_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_S_x4(88.2m) OFF
__term_sd_task_pre_model_185 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_light_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_light_x2(45.7m) OFF
__term_sd_task_pre_model_186 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_light_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_light_x3(45.7m) OFF
__term_sd_task_pre_model_187 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_light_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_light_x4(45.8m) OFF
__term_sd_task_pre_model_188 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_x2(154.1m) OFF
__term_sd_task_pre_model_189 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_x3(154.8m) OFF
__term_sd_task_pre_model_190 get_modelscope_model licyks/sd-upscaler-models/master/DAT/DAT_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/DAT # DAT_x4(154.7m) OFF
__term_sd_task_pre_model_191 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/16xPSNR.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 16xPSNR(67.2m) OFF
__term_sd_task_pre_model_192 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x-ITF-SkinDiffDetail-Lite-v1.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x-ITF-SkinDiffDetail-Lite-v1(20.1m) OFF
__term_sd_task_pre_model_193 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x_NMKD-BrightenRedux_200k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x_NMKD-BrightenRedux_200k(66.6m) OFF
__term_sd_task_pre_model_194 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x_NMKD-YandereInpaint_375000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x_NMKD-YandereInpaint_375000_G(66.6m) OFF
__term_sd_task_pre_model_195 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x_NMKDDetoon_97500_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x_NMKDDetoon_97500_G(66.6m) OFF
__term_sd_task_pre_model_196 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x_NoiseToner-Poisson-Detailed_108000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x_NoiseToner-Poisson-Detailed_108000_G(66.6m) OFF
__term_sd_task_pre_model_197 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/1x_NoiseToner-Uniform-Detailed_100000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 1x_NoiseToner-Uniform-Detailed_100000_G(66.6m) OFF
__term_sd_task_pre_model_198 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x-UltraSharp.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x-UltraSharp(66.9m) OFF
__term_sd_task_pre_model_199 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4xPSNR.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4xPSNR(66.9m) OFF
__term_sd_task_pre_model_200 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_CountryRoads_377000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_CountryRoads_377000_G(66.9m) OFF
__term_sd_task_pre_model_201 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_Fatality_Comix_260000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_Fatality_Comix_260000_G(66.9m) OFF
__term_sd_task_pre_model_202 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-Siax_200k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-Siax_200k(66.9m) OFF
__term_sd_task_pre_model_203 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-Superscale-Artisoftject_210000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-Superscale-Artisoftject_210000_G(66.9m) OFF
__term_sd_task_pre_model_204 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-Superscale-SP_178000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-Superscale-SP_178000_G(66.9m) ON
__term_sd_task_pre_model_205 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-UltraYandere-Lite_280k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-UltraYandere-Lite_280k(20.1m) OFF
__term_sd_task_pre_model_206 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-UltraYandere_300k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-UltraYandere_300k(66.9m) OFF
__term_sd_task_pre_model_207 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKD-YandereNeoXL_200k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKD-YandereNeoXL_200k(66.9m) OFF
__term_sd_task_pre_model_208 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NMKDSuperscale_Artisoft_120000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NMKDSuperscale_Artisoft_120000_G(67.1m) OFF
__term_sd_task_pre_model_209 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_NickelbackFS_72000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_NickelbackFS_72000_G(67.1m) OFF
__term_sd_task_pre_model_210 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_Nickelback_70000G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_Nickelback_70000G(66.9m) OFF
__term_sd_task_pre_model_211 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_RealisticRescaler_100000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_RealisticRescaler_100000_G(134.1m) OFF
__term_sd_task_pre_model_212 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_Valar_v1.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_Valar_v1(67.5m) OFF
__term_sd_task_pre_model_213 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_fatal_Anime_500000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_fatal_Anime_500000_G(66.9m) OFF
__term_sd_task_pre_model_214 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/4x_foolhardy_Remacri.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_foolhardy_Remacri(67m) OFF
__term_sd_task_pre_model_215 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/8xPSNR.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 8xPSNR(67.1m) OFF
__term_sd_task_pre_model_216 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/8x_NMKD-Superscale_150000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 8x_NMKD-Superscale_150000_G(67.1m) OFF
__term_sd_task_pre_model_217 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/8x_NMKD-Typescale_175k.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 8x_NMKD-Typescale_175k(67.1m) OFF
__term_sd_task_pre_model_218 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/A_ESRGAN_Single.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # A_ESRGAN_Single(134.1m) OFF
__term_sd_task_pre_model_219 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/BSRGAN.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # BSRGAN(67.1m) OFF
__term_sd_task_pre_model_220 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/BSRGANx2.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # BSRGANx2(66.8m) OFF
__term_sd_task_pre_model_221 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/BSRNet.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # BSRNet(67.1m) OFF
__term_sd_task_pre_model_222 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/ESRGAN_4x.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # ESRGAN_4x(66.9m) OFF
__term_sd_task_pre_model_223 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/LADDIER1_282500_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # LADDIER1_282500_G(66.9m) OFF
__term_sd_task_pre_model_224 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Neutral_115000_swaG.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_UniversalUpscalerV2-Neutral_115000_swaG(66.9m) OFF
__term_sd_task_pre_model_225 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Sharp_101000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_UniversalUpscalerV2-Sharp_101000_G(66.9m) OFF
__term_sd_task_pre_model_226 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/UniversalUpscaler/4x_UniversalUpscalerV2-Sharper_103000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_UniversalUpscalerV2-Sharper_103000_G(66.9m) OFF
__term_sd_task_pre_model_227 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/UniversalUpscaler/Legacy/4x_UniversalUpscaler-Detailed_155000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_UniversalUpscaler-Detailed_155000_G(66.9m) OFF
__term_sd_task_pre_model_228 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/UniversalUpscaler/Legacy/4x_UniversalUpscaler-Soft_190000_G.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # 4x_UniversalUpscaler-Soft_190000_G(66.9m) OFF
__term_sd_task_pre_model_229 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/WaifuGAN_v3_30000.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # WaifuGAN_v3_30000(66.9m) OFF
__term_sd_task_pre_model_230 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/lollypop.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # lollypop(66.9m) OFF
__term_sd_task_pre_model_231 get_modelscope_model licyks/sd-upscaler-models/master/ESRGAN/sudo_rife4_269.662_testV1_scale1.pth "${SD_WEBUI_ROOT_PATH}"/models/ESRGAN # sudo_rife4_269.662_testV1_scale1(33.7m) OFF
__term_sd_task_pre_model_232 get_modelscope_model licyks/sd-upscaler-models/master/GFPGAN/GFPGANv1.3.pth "${SD_WEBUI_ROOT_PATH}"/models/GFPGAN # GFPGANv1.3(348.6m) OFF
__term_sd_task_pre_model_233 get_modelscope_model licyks/sd-upscaler-models/master/GFPGAN/GFPGANv1.4.pth "${SD_WEBUI_ROOT_PATH}"/models/GFPGAN # GFPGANv1.4(348.6m) OFF
__term_sd_task_pre_model_234 get_modelscope_model licyks/sd-upscaler-models/master/GFPGAN/detection_Resnet50_Final.pth "${SD_WEBUI_ROOT_PATH}"/models/GFPGAN # detection_Resnet50_Final(109.5m) OFF
__term_sd_task_pre_model_235 get_modelscope_model licyks/sd-upscaler-models/master/GFPGAN/parsing_bisenet.pth "${SD_WEBUI_ROOT_PATH}"/models/GFPGAN # parsing_bisenet(12.2m) OFF
__term_sd_task_pre_model_236 get_modelscope_model licyks/sd-upscaler-models/master/GFPGAN/parsing_parsenet.pth "${SD_WEBUI_ROOT_PATH}"/models/GFPGAN # parsing_parsenet(85.3m) OFF
__term_sd_task_pre_model_237 get_modelscope_model licyks/sd-upscaler-models/master/RealESRGAN/RealESRGAN_x4plus.pth "${SD_WEBUI_ROOT_PATH}"/models/RealESRGAN # RealESRGAN_x4plus(67m) ON
__term_sd_task_pre_model_238 get_modelscope_model licyks/sd-upscaler-models/master/RealESRGAN/RealESRGAN_x4plus_anime_6B.pth "${SD_WEBUI_ROOT_PATH}"/models/RealESRGAN # RealESRGAN_x4plus_anime_6B(17.9m) ON
__term_sd_task_pre_model_239 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DF2K_s64w8_SwinIR-M_x2(67.2m) OFF
__term_sd_task_pre_model_240 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DF2K_s64w8_SwinIR-M_x3(68m) OFF
__term_sd_task_pre_model_241 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DF2K_s64w8_SwinIR-M_x4(67.8m) OFF
__term_sd_task_pre_model_242 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DF2K_s64w8_SwinIR-M_x8.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DF2K_s64w8_SwinIR-M_x8(68.4m) OFF
__term_sd_task_pre_model_243 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x2.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x2(59m) OFF
__term_sd_task_pre_model_244 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x3.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x3(59.7m) OFF
__term_sd_task_pre_model_245 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x4.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x4(59.6m) OFF
__term_sd_task_pre_model_246 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/001_classicalSR_DIV2K_s48w8_SwinIR-M_x8.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # 001_classicalSR_DIV2K_s48w8_SwinIR-M_x8(60.2m) OFF
__term_sd_task_pre_model_247 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/Swin2SR_ClassicalSR_X2_64.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # Swin2SR_ClassicalSR_X2_64(68.7m) OFF
__term_sd_task_pre_model_248 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/Swin2SR_ClassicalSR_X4_64.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # Swin2SR_ClassicalSR_X4_64(69.3m) OFF
__term_sd_task_pre_model_249 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/Swin2SR_CompressedSR_X4_48.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # Swin2SR_CompressedSR_X4_48(61.1m) OFF
__term_sd_task_pre_model_250 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # Swin2SR_RealworldSR_X4_64_BSRGAN_PSNR(68.6m) OFF
__term_sd_task_pre_model_251 get_modelscope_model licyks/sd-upscaler-models/master/SwinIR/SwinIR_4x.pth "${SD_WEBUI_ROOT_PATH}"/models/SwinIR # SwinIR_4x(142.4m) OFF
__term_sd_task_pre_model_252 # =====图生图反推Tag模型===== OFF
__term_sd_task_pre_model_253 get_modelscope_model licyks/sd-upscaler-models/master/BLIP/model_base_caption_capfilt_large.pth "${SD_WEBUI_ROOT_PATH}"/models/BLIP # BLIP模型 model_base_caption_capfilt_large(896m) OFF
__term_sd_task_pre_model_254 get_modelscope_model licyks/sd-upscaler-models/master/torch_deepdanbooru/model-resnet_custom_v3.pt "${SD_WEBUI_ROOT_PATH}"/models/torch_deepdanbooru # deepdanbooru模型 model-resnet_custom_v3(644.1m) OFF
__term_sd_task_pre_model_255 # =====Embedding模型===== OFF
__term_sd_task_pre_model_256 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/EasyNegativeV2.safetensors "${SD_WEBUI_ROOT_PATH}"/embeddings # embeddings模型 EasyNegativeV2(0.1m) ON
__term_sd_task_pre_model_257 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/bad-artist-anime.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # bad-artist-anime(0.1m) ON
__term_sd_task_pre_model_258 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/bad-artist.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # bad-artist(0.1m) ON
__term_sd_task_pre_model_259 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/bad-hands-5.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # bad-hands-5(0.1m) ON
__term_sd_task_pre_model_260 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/bad-image-v2-39000.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # bad-image-v2-39000(0.1m) ON
__term_sd_task_pre_model_261 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/bad_prompt_version2.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # bad_prompt_version2(0.1m) ON
__term_sd_task_pre_model_262 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/ng_deepnegative_v1_75t.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # ng_deepnegative_v1_75t(0.1m) ON
__term_sd_task_pre_model_263 get_modelscope_model licyks/sd-embeddings/master/sd_1.5/verybadimagenegative_v1.3.pt "${SD_WEBUI_ROOT_PATH}"/embeddings # verybadimagenegative_v1.3(0.1m) ON
|
2301_81996401/term-sd
|
install/sd_webui/sd_webui_ms_model.sh
|
Shell
|
agpl-3.0
| 49,345
|
#!/bin/bash
# A1111 SD WebUI 启动脚本参数设置
# 启动参数保存在 <Start Path>/term-sd/config/sd-webui-launch.conf
a1111_sd_webui_launch_args_setting() {
local arg
local dialog_arg
local launch_args
local i
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--checklist "请选择 A1111-Stable-Diffusion-WebUI 启动参数, 确认之后将覆盖原有启动参数配置" \
$(get_dialog_size_menu) \
"1" "(update-all-extensions) 启动时更新所有扩展" OFF \
"2" "(skip-python-version-check) 跳过检查 Python 版本" OFF \
"3" "(skip-torch-cuda-test) 跳过 CUDA 可用性检查" OFF \
"4" "(reinstall-xformers) 启动时重新安装 xFormers" OFF \
"5" "(reinstall-torch) 启动时重新安装 PyTorch" OFF \
"6" "(update-check) 启动时检查更新" OFF \
"7" "(test-server) 配置测试服务器" OFF \
"8" "(log-startup) 显示详细启动日志" OFF \
"9" "(skip-prepare-environment) 跳过所有环境准备工作" OFF \
"10" "(skip-install) 跳过软件包的安装" OFF \
"11" "(dump-sysinfo) 将系统信息文件保存到磁盘并退出" OFF \
"12" "(do-not-download-clip) 跳过下载 CLIP 模型" OFF \
"13" "(no-half) 关闭 UNet 半精度优化" OFF \
"14" "(no-half-vae) 关闭 VAE 模型半精度优化" OFF \
"15" "(no-progressbar-hiding) 不隐藏 Gradio UI 中进度条" OFF \
"16" "(allow-code) 允许从 WebUI 执行自定义脚本" OFF \
"17" "(medvram) 启用显存优化 (显存 < 6g 时推荐使用)" OFF \
"18" "(medvram-sdxl) 仅在 SDXL 模型启用显存优化 (显存 < 8g 时推荐使用)" OFF \
"19" "(lowvram) 启用显存优化 (显存 < 4g 时推荐使用)" OFF \
"20" "(lowram) 将模型加载到显存中而不是内存中" OFF \
"21" "(precision half) 使用模型半精度" OFF \
"22" "(precision full) 使用模型全精度" OFF \
"23" "(upcast-sampling) 使用向上采样法提高精度" OFF \
"24" "(share) 通过 Gradio 共享" OFF \
"25" "(enable-insecure-extension-access) 允许在开放远程访问时安装插件" OFF \
"26" "(xformers) 尝试使用 xFormers 优化" OFF \
"27" "(force-enable-xformers) 强制使用 xFormers 优化" OFF \
"28" "(xformers-flash-attention) 使用 xFormers-Flash优化 (仅支持 SD2.x 以上)" OFF \
"29" "(opt-split-attention) 使用 Split 优化" OFF \
"30" "(opt-sub-quad-attention) 使用 Sub-Quad 优化" OFF \
"31" "(opt-split-attention-invokeai) 使用 Sub-Quad-InvokeAI 优化" OFF \
"32" "(opt-split-attention-v1) 使用 Sub-Quad-V1 优化" OFF \
"33" "(opt-sdp-attention) 使用 Sdp 优化 (仅限 PyTorch2.0 以上)" OFF \
"34" "(opt-sdp-no-mem-attention) 使用无高效内存使用的 Sdp 优化" OFF \
"35" "(disable-opt-split-attention) 禁用 Split 优化" OFF \
"36" "(disable-nan-check) 禁用潜空间 NAN 检查" OFF \
"37" "(use-cpu) 使用 CPU 进行生图" OFF \
"38" "(disable-model-loading-ram-optimization) 禁用减少内存使用的优化" OFF \
"39" "(listen) 开放远程连接" OFF \
"40" "(hide-ui-dir-config) 隐藏 WebUI 目录配置" OFF \
"41" "(freeze-settings) 冻结 WebUI 设置" OFF \
"42" "(gradio-debug) 以 Debug 模式启用 Gradio" OFF \
"43" "(opt-channelslast) 使用 Channelslast 内存格式优化" OFF \
"44" "(autolaunch) 启动 WebUI 完成后自动启动浏览器" OFF \
"45" "(theme dark) 使用黑暗主题" OFF \
"46" "(use-textbox-seed) 使用文本框在 WebUI 中生成的种子" OFF \
"47" "(disable-console-progressbars) 禁用控制台进度条显示" OFF \
"48" "(enable-console-prompts) 启用在生图时输出提示词到控制台" OFF \
"49" "(disable-safe-unpickle) 禁用检查模型是否包含恶意代码" OFF \
"50" "(api) 启用 API" OFF \
"51" "(api-log) 启用输出所有 API 请求的日志记录" OFF \
"52" "(nowebui) 不加载 WebUI 界面" OFF \
"53" "(ui-debug-mode) 不加载模型启动 WebUI (UI Debug)" OFF \
"54" "(administrator) 启用管理员权限" OFF \
"55" "(disable-tls-verify) 禁用 TLS 证书验证" OFF \
"56" "(no-gradio-queue) 禁用 Gradio 队列" OFF \
"57" "(skip-version-check) 禁用 PyTorch, xFormers 版本检查" OFF \
"58" "(no-hashing) 禁用模型 Hash 检查" OFF \
"59" "(no-download-sd-model) 禁用自动下载模型, 即使模型路径无模型" OFF \
"60" "(add-stop-route) 添加 /_stop 路由以停止服务器" OFF \
"61" "(api-server-stop) 通过 API 启用服务器停止/重启/终止功能" OFF \
"62" "(disable-all-extensions) 禁用所有扩展运行" OFF \
"63" "(disable-extra-extensions) 禁用非内置的扩展运行" OFF \
"64" "(use-ipex) 使用 Intel XPU 作为生图后端" OFF \
"65" "(skip-load-model-at-start) 启动 WebUI 时不加载模型, 加速启动" OFF \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
for i in ${dialog_arg}; do
case "${i}" in
1)
arg="--update-all-extensions"
;;
2)
arg="--skip-python-version-check"
;;
3)
arg="--skip-torch-cuda-test"
;;
4)
arg="--reinstall-xformers"
;;
5)
arg="--reinstall-torch"
;;
6)
arg="--update-check"
;;
7)
arg="--test-server"
;;
8)
arg="--log-startup"
;;
9)
arg="--skip-prepare-environment"
;;
10)
arg="--skip-install"
;;
11)
arg="--dump-sysinfo"
;;
12)
arg="--do-not-download-clip"
;;
13)
arg="--no-half"
;;
14)
arg="--no-half-vae"
;;
15)
arg="--no-progressbar-hiding"
;;
16)
arg="--allow-code"
;;
17)
arg="--medvram"
;;
18)
arg="--medvram-sdxl"
;;
19)
arg="--lowvram"
;;
20)
arg="--lowram"
;;
21)
arg="--precision half"
;;
22)
arg="--precision full"
;;
23)
arg="--upcast-sampling"
;;
24)
arg="--share"
;;
25)
arg="--enable-insecure-extension-access"
;;
26)
arg="--xformers"
;;
27)
arg="--force-enable-xformers"
;;
28)
arg="--xformers-flash-attention"
;;
29)
arg="--opt-split-attention"
;;
30)
arg="--opt-sub-quad-attention"
;;
31)
arg="--opt-split-attention-invokeai"
;;
32)
arg="--opt-split-attention-v1"
;;
33)
arg="--opt-sdp-attention"
;;
34)
arg="--opt-sdp-no-mem-attention"
;;
35)
arg="--disable-opt-split-attention"
;;
36)
arg="--disable-nan-check"
;;
37)
arg="--use-cpu all"
;;
38)
arg="--disable-model-loading-ram-optimization"
;;
39)
arg="--listen"
;;
40)
arg="--hide-ui-dir-config"
;;
41)
arg="--freeze-settings"
;;
42)
arg="--gradio-debug"
;;
43)
arg="--opt-channelslast"
;;
44)
arg="--autolaunch"
;;
45)
arg="--theme dark"
;;
46)
arg="--use-textbox-seed"
;;
47)
arg="--disable-console-progressbars"
;;
48)
arg="--enable-console-prompts"
;;
49)
arg="--disable-safe-unpickle"
;;
50)
arg="--api"
;;
51)
arg="--api-log"
;;
52)
arg="--nowebui"
;;
53)
arg="--ui-debug-mode"
;;
54)
arg="--administrator"
;;
55)
arg="--disable-tls-verify"
;;
56)
arg="--no-gradio-queue"
;;
57)
arg="--skip-version-check"
;;
58)
arg="--no-hashing"
;;
59)
arg="--no-download-sd-model"
;;
60)
arg="--add-stop-route"
;;
61)
arg="--api-server-stop"
;;
62)
arg="--disable-all-extensions"
;;
63)
arg="--disable-extra-extensions"
;;
64)
arg="--use-ipex"
;;
65)
arg="--skip-load-model-at-start"
;;
esac
launch_args="${arg} ${launch_args}"
done
# 生成启动脚本
term_sd_echo "设置 A1111-Stable-Diffusion-WebUI 启动参数: ${launch_args}"
echo "launch.py ${launch_args}" > "${START_PATH}"/term-sd/config/sd-webui-launch.conf
else
term_sd_echo "取消设置 A1111-Stable-Diffusion-WebUI 启动参数"
fi
}
# A1111 SD WebUI 启动界面
a1111_sd_webui_launch() {
local dialog_arg
local launch_args
add_a1111_sd_webui_normal_launch_args # 当没有设置启动参数时默认生成一个启动参数
while true; do
launch_args=$(cat "${START_PATH}"/term-sd/config/sd-webui-launch.conf)
if is_use_venv; then
launch_args="python ${launch_args}"
else
launch_args="${TERM_SD_PYTHON_PATH} ${launch_args}"
fi
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 启动选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择启动 A1111-Stable-Diffusion-WebUI / 修改 A1111-Stable-Diffusion-WebUI 启动参数\n当前启动参数: ${launch_args}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 配置预设启动参数" \
"3" "> 修改自定义启动参数" \
"4" "> 重置启动参数" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
term_sd_launch
;;
2)
a1111_sd_webui_launch_args_setting
;;
3)
a1111_sd_webui_launch_args_revise
;;
4)
restore_a1111_sd_webui_launch_args
;;
*)
break
;;
esac
done
}
# A1111 SD WebUI 启动参数修改
# 启动修改界面时将从 <Start Path>/term-sd/config/sd-webui-launch.conf 中读取启动参数
# 可接着上次的启动参数进行修改
a1111_sd_webui_launch_args_revise() {
local dialog_arg
local launch_args
launch_args=$(cat "${START_PATH}"/term-sd/config/sd-webui-launch.conf | awk '{sub("launch.py ","")}1')
dialog_arg=$(dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 自定义启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "请输入 A1111-Stable-Diffusion-WebUI 启动参数" \
$(get_dialog_size) \
"${launch_args}" \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
term_sd_echo "设置 A1111-Stable-Diffusion-WebUI 启动参数: ${dialog_arg}"
echo "launch.py ${dialog_arg}" > "${START_PATH}"/term-sd/config/sd-webui-launch.conf
else
term_sd_echo "取消修改 A1111-Stable-Diffusion-WebUI 启动参数"
fi
}
# 添加默认启动参数配置
add_a1111_sd_webui_normal_launch_args() {
if [[ ! -f "${START_PATH}/term-sd/config/sd-webui-launch.conf" ]]; then # 找不到启动配置时默认生成一个
if [[ "${OSTYPE}" == "darwin"* ]]; then
echo "launch.py --theme dark --autolaunch --api --skip-load-model-at-start --skip-torch-cuda-test --upcast-sampling --no-half-vae --use-cpu interrogate" > "${START_PATH}"/term-sd/config/sd-webui-launch.conf
else
echo "launch.py --theme dark --autolaunch --xformers --api --skip-load-model-at-start" > "${START_PATH}"/term-sd/config/sd-webui-launch.conf
fi
fi
}
# 重置启动参数
restore_a1111_sd_webui_launch_args() {
if (dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 重置启动参数选项选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重置 A1111-Stable-Diffusion-WebUI 启动参数 ?" \
$(get_dialog_size)); then
term_sd_echo "重置 A1111-Stable-Diffusion-WebUI 启动参数"
rm -f "${START_PATH}"/term-sd/config/sd-webui-launch.conf
add_a1111_sd_webui_normal_launch_args
else
term_sd_echo "取消重置 A1111-Stable-Diffusion-WebUI 启动参数操作"
fi
}
|
2301_81996401/term-sd
|
modules/a1111_sd_webui_launch.sh
|
Shell
|
agpl-3.0
| 15,468
|
#!/bin/bash
# ComfyUI 自定义节点管理器
# 管理 <ComfyUI Path>/custom_nodes 文件夹下的自定义节点
comfyui_custom_node_manager() {
local dialog_arg
if [[ ! -d "${COMFYUI_ROOT_PATH}"/custom_nodes ]]; then
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点管理选项" \
--ok-label "确认" \
--msgbox "找不到 ComfyUI 自定义节点目录, 请检查 ComfyUI 是否安装完整" \
$(get_dialog_size)
return 1
fi
while true; do
cd "${COMFYUI_ROOT_PATH}"/custom_nodes # 回到最初路径
dialog_arg=$(dialog --erase-on-exit --notags \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择 ComfyUI 自定义节点管理选项的功能" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 安装自定义节点" \
"2" "> 管理自定义节点" \
"3" "> 更新全部自定义节点" \
"4" "> 安装全部自定义节点依赖" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
# 选择安装
comfyui_custom_node_install
;;
2)
# 选择管理
comfyui_custom_node_list
;;
3)
# 选择更新全部自定义节点
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点管理" \
--yes-label "是" --no-label "否" \
--yesno "是否更新所有 ComfyUI 自定义节点 ?" \
$(get_dialog_size)); then
update_all_extension
fi
;;
4)
# 选择安装全部自定义节点依赖
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点管理" \
--yes-label "是" --no-label "否" \
--yesno "是否安装所有 ComfyUI 自定义节点的依赖 ?" \
$(get_dialog_size)); then
comfyui_extension_depend_install "自定义节点"
fi
;;
*)
break
;;
esac
done
}
# ComfyUI 自定义节点安装
# 使用 COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE 全局变量临时储存安装信息
comfyui_custom_node_install() {
local repo_url
local custom_node_name
repo_url=$(dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点安装选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "输入自定义节点的 Github 地址或其他下载地址" \
$(get_dialog_size) \
3>&1 1>&2 2>&3)
if [[ ! -z "${repo_url}" ]]; then
custom_node_name=$(basename "${repo_url}" | awk -F '.git' '{print $1}')
term_sd_echo "安装 ${custom_node_name} 自定义节点中"
if ! term_sd_is_git_repository_exist "${repo_url}"; then # 检查待安装的自定义节点是否存在于自定义节点文件夹中
term_sd_try git clone --recurse-submodules "${repo_url}" "${COMFYUI_ROOT_PATH}/custom_nodes/${custom_node_name}"
if [[ "$?" == 0 ]]; then
COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE="${custom_node_name} 自定义节点安装成功"
comfyui_extension_depend_install_auto "自定义节点" "${custom_node_name}" # 检查是否存在依赖文件并安装
else
COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE="${custom_node_name} 自定义节点安装失败"
fi
else
COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE="${custom_node_name} 自定义节点已存在"
fi
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点安装结果" \
--ok-label "确认" \
--msgbox "${COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE}" \
$(get_dialog_size)
unset COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点管理选项" \
--ok-label "确认" \
--msgbox "输入的 ComfyUI 自定义节点安装地址为空" \
$(get_dialog_size)
fi
}
# 自定义节点浏览器
# 将列出 <ComfyUI Path>/custom_nodes 中所有的自定义节点的文件夹
comfyui_custom_node_list() {
local custom_node_name
while true; do
cd "${COMFYUI_ROOT_PATH}"/custom_nodes # 回到最初路径
get_dir_folder_list # 获取当前目录下的所有文件夹
if term_sd_is_bash_ver_lower; then # Bash 版本低于 4 时使用旧版列表显示方案
custom_node_name=$(dialog --erase-on-exit \
--ok-label "确认" --cancel-label "取消" \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点列表" \
--menu "使用上下键选择要操作的自定义节点并回车确认" \
$(get_dialog_size_menu) \
"-->返回<--" "<---------" \
"${LOCAL_DIR_LIST}" \
3>&1 1>&2 2>&3)
else
custom_node_name=$(dialog --erase-on-exit \
--ok-label "确认" --cancel-label "取消" \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点列表" \
--menu "使用上下键选择要操作的自定义节点并回车确认" \
$(get_dialog_size_menu) \
"-->返回<--" "<---------" \
"${LOCAL_DIR_LIST[@]}" \
3>&1 1>&2 2>&3)
fi
if [[ "$?" == 0 ]]; then
if [[ "${custom_node_name}" == "-->返回<--" ]]; then
break
elif [[ -d "${custom_node_name}" ]]; then # 选择文件夹
cd "${custom_node_name}"
comfyui_custom_node_interface "${custom_node_name}"
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点管理" \
--ok-label "确认" \
--msgbox "当前的选择非 ComfyUI 自定义节点, 请重新选择" \
$(get_dialog_size)
fi
else
break
fi
done
unset LOCAL_DIR_LIST
}
# ComfyUI 自定义节点管理
# 使用:
# comfyui_custom_node_interface <自定义节点的文件夹名>
comfyui_custom_node_interface() {
local dialog_arg
local custom_node_name
local custom_node_folder=$@
local dialog_buttom
local status_display
local custom_node_status
local tmp_folder_name
while true; do
if [[ "$(awk -F '.' '{print $NF}' <<< ${custom_node_folder})" == "disabled" ]]; then
custom_node_status=0
status_display="已禁用"
dialog_buttom="启用"
else
custom_node_status=1
status_display="已启用"
dialog_buttom="禁用"
fi
custom_node_name=$(awk -F '.disabled' '{print $1}' <<< ${custom_node_folder})
dialog_arg=$(dialog --erase-on-exit --notags \
--title "ComfyUI 选项" \
--backtitle "ComfyUI 自定义节点管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择对 ${custom_node_name} 自定义节点的管理功能\n当前更新源: $(git_remote_display)\n当前分支: $(git_branch_display)\n当前状态: ${status_display}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 更新" \
"2" "> 修复更新" \
"3" "> 安装依赖" \
"4" "> 版本切换" \
"5" "> 更新源切换" \
"6" "> ${dialog_buttom}自定义节点" \
"7" "> 卸载" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
if is_git_repo; then
term_sd_echo "更新 ${custom_node_name} 自定义节点中"
git_pull_repository
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点更新结果" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点更新成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点更新结果" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点更新失败" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点更新结果" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点非 Git 安装, 无法更新" \
$(get_dialog_size)
fi
;;
2)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点修复更新" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 ${custom_node_name} 自定义节点更新 ?" \
$(get_dialog_size)); then
git_fix_pointer_offset
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点修复更新" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点修复更新完成" \
$(get_dialog_size)
else
term_sd_echo "取消修复 ${custom_node_name} 自定义节点的更新"
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点修复更新" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点非 Git 安装, 无法修复更新" \
$(get_dialog_size)
fi
;;
3)
# ComfyUI 并不像 SD WebUI 自动为插件安装依赖, 所以只能手动装
if (dialog --erase-on-exit \
--title "ComfyUI 选项" \
--backtitle "ComfyUI 自定义节点依赖安装选项" \
--yes-label "是" --no-label "否" \
--yesno "是否安装 ${custom_node_name} 自定义节点依赖 ?" \
$(get_dialog_size)); then
comfyui_extension_depend_install_single "自定义节点" "${custom_node_folder}"
else
term_sd_echo "取消安装 ${custom_node_name} 自定义节点依赖"
fi
;;
4)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点版本切换" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 ${custom_node_name} 自定义节点版本 ?" \
$(get_dialog_size)); then
git_ver_switch
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点版本切换" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点版本切换完成, 当前版本为: $(git_branch_display)" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI自定义节点版本切换" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点非 Git 安装, 无法进行版本切换" \
$(get_dialog_size)
fi
;;
5)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点更新源切换" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 ${custom_node_name} 自定义节点更新源 ?" \
$(get_dialog_size)); then
git_remote_url_select_single
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点更新源切换" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点非 Git 安装, 无法进行更新源切换" \
$(get_dialog_size)
fi
;;
6)
if [[ "${custom_node_status}" == 0 ]]; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点更新源切换" \
--yes-label "是" --no-label "否" \
--yesno "是否启用 ${custom_node_name} 自定义节点 ?" \
$(get_dialog_size)); then
tmp_folder_name=$custom_node_folder
custom_node_folder=$(awk -F '.disabled' '{print $1}' <<< ${custom_node_folder})
cd ..
mv "${tmp_folder_name}" "${custom_node_folder}"
cd "${custom_node_folder}"
else
continue
fi
else
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点更新源切换" \
--yes-label "是" --no-label "否" \
--yesno "是否禁用 ${custom_node_name} 自定义节点 ?" \
$(get_dialog_size)); then
tmp_folder_name=$custom_node_folder
custom_node_folder="${custom_node_folder}.disabled"
cd ..
mv -f "${tmp_folder_name}" "${custom_node_folder}"
cd "${custom_node_folder}"
else
continue
fi
fi
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点删除选项" \
--ok-label "确认" \
--msgbox "${dialog_buttom} ${custom_node_name} 自定义节点成功" \
$(get_dialog_size)
;;
7)
if (dialog --erase-on-exit \
--title "ComfyUI 选项" \
--backtitle "ComfyUI 自定义节点删除选项" \
--yes-label "是" --no-label "否" \
--yesno "是否删除 ${custom_node_name} 自定义节点 ?" \
$(get_dialog_size)); then
term_sd_echo "请再次确认是否删除 ${custom_node_name} 自定义节点 (yes/no) ?"
term_sd_echo "警告: 该操作将永久删除 ${custom_node_name} 自定义节点"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
yes|y|YES|Y)
term_sd_echo "删除 ${custom_node_name} 自定义节点中"
cd ..
rm -rf "${COMFYUI_ROOT_PATH}/custom_nodes/${custom_node_folder}"
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义节点删除选项" \
--ok-label "确认" \
--msgbox "删除 ${custom_node_name} 自定义节点完成" \
$(get_dialog_size)
break
;;
*)
term_sd_echo "取消删除 ${custom_node_name} 自定义节点操作"
;;
esac
fi
;;
*)
break
;;
esac
done
}
|
2301_81996401/term-sd
|
modules/comfyui_custom_node_manager.sh
|
Shell
|
agpl-3.0
| 17,991
|
#!/bin/bash
# ComfyUI 插件 / 自定义节点依赖一键安装
# 使用:
# comfyui_extension_depend_install <提示信息>
# 使用时将检测 ComfyUI 插件 / 自定义节点文件夹中包含的 install.py 文件和 requirements.txt 文件
# 如果检测到上述文件, 将通过文件安装依赖
comfyui_extension_depend_install() {
local install_msg
local count=0
local sum=0
local depend_sum=0
local success_count=0
local fail_count=0
local i
local depend_type=$1
# 安装前的准备
download_mirror_select # 下载镜像源选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否安装 ComfyUI 插件 / 自定义节点依赖 ?"; then
term_sd_print_line "${TERM_SD_MANAGE_OBJECT} ${depend_type}依赖一键安装"
term_sd_tmp_disable_proxy
enter_venv "${COMFYUI_ROOT_PATH}"
for i in ./*; do # 统计需要安装的依赖
[[ -f "${i}" ]] && continue # 排除文件
if [[ -f "${i}/install.py" ]] || [[ -f "${i}/requirements.txt" ]]; then
count=$(( count + 1 ))
fi
done
for i in ./*; do
[[ -f "${i}" ]] && continue # 排除文件
cd "${i}"
if [[ -f "install.py" ]] || [[ -f "requirements.txt" ]]; then
sum=$(( sum + 1 ))
term_sd_echo "[${sum}/${count}] 安装 $(echo ${i} | awk -F "/" '{print $NF}') ${depend_type}依赖"
install_msg="${install_msg} $(basename "${i}"):\n" # 作为显示安装结果信息
fi
if [[ -f "install.py" ]]; then # 找到 install.py 文件
depend_sum=$(( depend_sum + 1 ))
term_sd_try term_sd_python install.py
if [[ "$?" = 0 ]]; then # 记录退出状态
install_msg="${install_msg} run install.py: 成功 ✓\n"
success_count=$((success_count + 1))
else
install_msg="${install_msg} run install.py: 失败 ×\n"
fail_count=$((fail_count + 1))
fi
fi
if [[ -f "requirements.txt" ]]; then # 找到requirement.txt文件
depend_sum=$(( depend_sum + 1 ))
install_python_package -r requirements.txt
if [[ "$?" = 0 ]]; then # 记录退出状态
install_msg="${install_msg} install requirements.txt: 成功 ✓\n"
success_count=$(( success_count + 1 ))
else
install_msg="${install_msg} install requirements.txt: 失败 ×\n"
fail_count=$(( fail_count + 1 ))
fi
fi
cd ..
done
exit_venv
term_sd_tmp_enable_proxy
term_sd_print_line
dialog --erase-on-exit \
--title "ComfyUI管理" \
--backtitle "ComfyUI ${depend_type}依赖安装结果" \
--ok-label "确认" \
--msgbox "当前依赖的安装情况列表\n[●: ${depend_sum} | ✓: ${success_count} | ×: ${fail_count}]\n${TERM_SD_DELIMITER}\n${install_msg}${TERM_SD_DELIMITER}" \
$(get_dialog_size)
else
term_sd_echo "取消安装 ComfyUI 插件 / 自定义节点依赖"
fi
clean_install_config # 清理安装参数
}
# 单独为 ComfyUI 插件 / 自定义节点安装依赖的功能
# 使用:
# comfyui_extension_depend_install_single <提示内容> <插件 / 自定义节点名称>
# 安装依赖结束后将弹窗提示安装结果
comfyui_extension_depend_install_single() {
local install_msg
local depend_type=$1
local name=$2
name=$(basename "$(pwd)")
# 安装前的准备
download_mirror_select # 下载镜像源选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否安装 ${name} ${depend_type}依赖 ?"; then
enter_venv "${COMFYUI_ROOT_PATH}"
if [[ -f "install.py" ]] || [[ -f "requirements.txt" ]]; then
term_sd_echo "安装 ${name} ${depend_type}依赖"
install_msg="${install_msg}\n ${name}${depend_type}:\n" # 作为显示安装结果信息
fi
if [[ -f "install.py" ]]; then # 找到 install.py 文件
term_sd_try term_sd_python install.py
if [[ "$?" == 0 ]]; then # 记录退出状态
install_msg="${install_msg} run install.py: 成功 ✓\n"
else
install_msg="${install_msg} run install.py: 失败 ×\n"
fi
fi
if [[ -f "requirements.txt" ]]; then # 找到requirement.txt文件
install_python_package -r requirements.txt
if [[ "$?" == 0 ]]; then # 记录退出状态
install_msg="${install_msg} install requirements.txt: 成功 ✓\n"
else
install_msg="${install_msg} install requirements.txt: 失败 ×\n"
fi
fi
exit_venv
dialog --erase-on-exit \
--title "ComfyUI选项" \
--backtitle "ComfyUI ${depend_type}依赖安装结果" \
--ok-label "确认" \
--msgbox "当前 ${name} ${depend_type}依赖的安装情况\n${TERM_SD_DELIMITER}${install_msg}${TERM_SD_DELIMITER}" \
$(get_dialog_size)
fi
clean_install_config # 清理安装参数
}
# 插件/自定义节点依赖安装(自动)
# 使用:
# comfyui_extension_depend_install_auto <提示内容> <目录>
# COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE 变量用于返回安装依赖的信息
comfyui_extension_depend_install_auto() {
local depend_type=$1
local extension_name=$2
if [[ -f "$2/requirements.txt" ]] || [[ -f "$2/install.py" ]]; then
term_sd_echo "开始安装 ${extension_name} ${depend_type}依赖"
COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE="${COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE}\n\n${extension_name} ${depend_type}依赖安装:\n"
enter_venv "${COMFYUI_ROOT_PATH}"
cd "${extension_name}"
if [[ -f "install.py" ]]; then # 找到install.py文件
term_sd_try term_sd_python install.py
if [[ "$?" == 0 ]]; then # 记录退出状态
COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE="${COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE} run install.py: 成功 ✓\n"
else
COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE="${COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE} run install.py: 失败 ×\n"
fi
fi
if [[ -f "requirements.txt" ]]; then # 找到requirement.txt文件
install_python_package -r requirements.txt
if [[ "$?" == 0 ]]; then # 记录退出状态
COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE="${COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE} install requirements.txt: 成功 ✓\n"
else
COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE="${COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE} install requirements.txt: 失败 ×\n"
fi
fi
cd ..
exit_venv
fi
}
|
2301_81996401/term-sd
|
modules/comfyui_extension_depend_install.sh
|
Shell
|
agpl-3.0
| 7,145
|
#!/bin/bash
# ComfyUI 的扩展分为两种,一种是前端节点, 另一种是后端扩展(少见). 详见: https://github.com/comfyanonymous/ComfyUI/discussions/631
# 实际上插件非常少见, 更多的是自定义节点, 但是因为存在插件的文件夹, 所以保留了插件的管理功能
# ComfyUI 插件管理器
comfyui_extension_manager() {
local dialog_arg
if [[ ! -d "${COMFYUI_ROOT_PATH}"/web/extensions ]]; then
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件管理选项" \
--ok-label "确认" \
--msgbox "找不到 ComfyUI 插件目录, 请检查 ComfyUI 是否安装完整" \
$(get_dialog_size)
return 1
fi
while true; do
cd "${COMFYUI_ROOT_PATH}"/web/extensions # 回到最初路径
dialog_arg=$(dialog --erase-on-exit --notags \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择 ComfyUI 插件管理选项的功能" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 安装插件" \
"2" "> 管理插件" \
"3" "> 更新全部插件" \
"4" "> 安装全部插件依赖" \
3>&1 1>&2 2>&3 )
case "${dialog_arg}" in
1)
# 选择安装
comfyui_extension_install
;;
2)
# 选择管理
comfyui_extension_list
;;
3)
# 选择更新全部插件
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件管理" \
--yes-label "是" --no-label "否" \
--yesno "是否更新所有 ComfyUI 插件 ?" \
$(get_dialog_size)); then
update_all_extension
fi
;;
4)
# 选择安装全部插件依赖
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件管理" \
--yes-label "是" --no-label "否" \
--yesno "是否安装所有 ComfyUI 插件的依赖 ?" \
$(get_dialog_size)); then
comfyui_extension_depend_install "插件"
fi
;;
*)
break
;;
esac
done
}
# ComfyUI 插件安装
# 使用 COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE 全局变量临时储存安装信息
comfyui_extension_install() {
local repo_url
local name
repo_url=$(dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件安装选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "输入插件的 Github 地址或其他下载地址" \
$(get_dialog_size) \
3>&1 1>&2 2>&3)
if [[ ! -z "${repo_url}" ]]; then
name=$(basename "${repo_url}" | awk -F '.git' '{print $1}')
term_sd_echo "安装 ${name} 插件中"
if ! term_sd_is_git_repository_exist "${repo_url}"; then
term_sd_try git clone --recurse-submodules "${repo_url}" "${COMFYUI_ROOT_PATH}/web/extensions/${name}"
if [[ "$?" == 0 ]]; then
COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE="${name} 插件安装成功"
comfyui_extension_depend_install_auto "插件" "${name}"
else
COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE="${name} 插件安装失败"
fi
else
COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE="${name} 插件已存在"
fi
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件安装结果" \
--ok-label "确认" \
--msgbox "${COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE}" \
$(get_dialog_size)
unset COMFYUI_CUSTOM_NODE_INSTALL_DEP_MESSAGE
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件管理选项" \
--ok-label "确认" \
--msgbox "输入的 ComfyUI 插件安装地址为空" \
$(get_dialog_size)
fi
}
# 插件列表浏览器
# 将列出 <ComfyUI Path>/web/extensions 中所有的插件的文件夹
comfyui_extension_list() {
local extension_name
while true; do
cd "${COMFYUI_ROOT_PATH}"/web/extensions # 回到最初路径
get_dir_folder_list # 获取当前目录下的所有文件夹
if term_sd_is_bash_ver_lower; then # Bash 版本低于 4 时使用旧版列表显示方案
extension_name=$(dialog --erase-on-exit \
--ok-label "确认" --cancel-label "取消" \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件列表" \
--menu "使用上下键选择要操作的插件并回车确认" \
$(get_dialog_size_menu) \
"-->返回<--" "<---------" \
"${LOCAL_DIR_LIST}" \
3>&1 1>&2 2>&3)
else
extension_name=$(dialog --erase-on-exit \
--ok-label "确认" --cancel-label "取消" \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件列表" \
--menu "使用上下键选择要操作的插件并回车确认" \
$(get_dialog_size_menu) \
"-->返回<--" "<---------" \
"${LOCAL_DIR_LIST[@]}" \
3>&1 1>&2 2>&3)
fi
if [[ "$?" == 0 ]]; then
if [[ "${extension_name}" == "-->返回<--" ]]; then
break
elif [[ -d "${extension_name}" ]]; then # 选择文件夹
if [[ ! "${extension_name}" == "core" ]]; then # 排除掉core文件夹
cd "${extension_name}"
comfyui_extension_interface "${extension_name}"
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件管理" \
--ok-label "确认" \
--msgbox "当前的选择非 ComfyUI 插件, 请重新选择" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件管理" \
--ok-label "确认" \
--msgbox "当前的选择非 ComfyUI 插件, 请重新选择" \
$(get_dialog_size)
fi
else
break
fi
done
unset LOCAL_DIR_LIST
}
# 插件管理
# 使用:
# comfyui_extension_interface <插件的文件夹名>
comfyui_extension_interface() {
local dialog_arg
local extension_name=$1
while true; do
dialog_arg=$(dialog --erase-on-exit --notags \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择对 ${extension_name} 插件的管理功能\n当前更新源: $(git_remote_display)\n当前分支: $(git_branch_display)" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 更新" \
"2" "> 修复更新" \
"3" "> 安装依赖" \
"4" "> 版本切换" \
"5" "> 更新源切换" \
"6" "> 卸载" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
if is_git_repo; then
term_sd_echo "更新 ${extension_name} 插件中"
git_pull_repository
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件更新结果" \
--ok-label "确认" \
--msgbox "${extension_name} 插件更新成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件更新结果" \
--ok-label "确认" \
--msgbox "${extension_name} 插件更新失败" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件更新结果" \
--ok-label "确认" \
--msgbox "${extension_name} 插件非 Git 安装, 无法更新" \
$(get_dialog_size)
fi
;;
2)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件修复更新" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 ${extension_name} 插件更新 ?" \
$(get_dialog_size)); then
git_fix_pointer_offset
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件修复更新" \
--ok-label "确认" \
--msgbox "${extension_name} 插件修复更新完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件修复更新" \
--ok-label "确认" \
--msgbox "${extension_name} 插件非 Git 安装, 无法修复更新" \
$(get_dialog_size)
fi
;;
3)
# ComfyUI 并不像 SD WebUI 自动为插件安装依赖, 所以只能手动装
if (dialog --erase-on-exit \
--title "ComfyUI 选项" \
--backtitle "ComfyUI 插件依赖安装选项" \
--yes-label "是" --no-label "否" \
--yesno "是否安装 ${extension_name} 插件依赖 ?" \
$(get_dialog_size)); then
comfyui_extension_depend_install_single "插件" "${extension_name}"
else
term_sd_echo "取消安装 ${extension_name} 插件依赖"
fi
;;
4)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件版本切换" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 ${extension_name} 插件版本 ?" \
$(get_dialog_size)); then
git_ver_switch
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件版本切换" \
--ok-label "确认" \
--msgbox "${extension_name} 插件版本切换完成, 当前版本为: $(git_branch_display)" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件版本切换" \
--ok-label "确认" \
--msgbox "${extension_name}插件非 Git 安装, 无法进行版本切换" \
$(get_dialog_size)
fi
;;
5)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件版本切换" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 ${extension_name} 插件版本 ?" \
$(get_dialog_size)); then
git_remote_url_select_single
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件更新源切换" \
--ok-label "确认" \
--msgbox "${extension_name} 插件非 Git 安装, 无法进行更新源切换" \
$(get_dialog_size)
fi
;;
6)
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件删除选项" \
--yes-label "是" --no-label "否" \
--yesno "是否删除 ${extension_name} 插件 ?" \
$(get_dialog_size)); then
term_sd_echo "请再次确认是否删除 ${extension_name} 插件 (yes/no) ?"
term_sd_echo "警告: 该操作将永久删除 ${extension_name} 插件"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
yes|y|YES|Y)
term_sd_echo "删除 ${extension_name} 插件中"
cd ..
rm -rf "${COMFYUI_ROOT_PATH}/web/extensions/${extension_name}"
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 插件删除选项" \
--ok-label "确认" \
--msgbox "删除 ${extension_name} 插件完成" \
$(get_dialog_size)
break
;;
*)
term_sd_echo "取消删除 ${extension_name} 插件操作"
;;
esac
fi
;;
*)
break
;;
esac
done
}
|
2301_81996401/term-sd
|
modules/comfyui_extension_manager.sh
|
Shell
|
agpl-3.0
| 14,970
|
#!/bin/bash
# ComfyUI 启动脚本生成部分
# 启动参数保存在 <Start Path>/term-sd/config/comfyui-launch.conf
comfyui_launch_args_setting() {
local arg
local dialog_arg
local launch_args
local i
dialog_arg=$(dialog --erase-on-exit --notags \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--checklist "请选择 ComfyUI 启动参数, 确认之后将覆盖原有启动参数配置" \
$(get_dialog_size_menu) \
"1" "(listen) 开放远程连接" OFF \
"2" "(auto-launch) 启动 WebUI 完成后自动启动浏览器" OFF \
"3" "(disable-auto-launch) 禁用在启动 WebUI 完成后自动启动浏览器" OFF \
"4" "(cuda-malloc) 启用 CUDA 流顺序内存分配器 (Torch2.0+ 默认启用)" OFF \
"5" "(disable-cuda-malloc) 禁用 CUDA 流顺序内存分配器" OFF \
"6" "(dont-upcast-attention) 禁用向上注意力优化" OFF \
"7" "(force-fp32) 强制使用 FP32" OFF \
"8" "(force-fp16) 强制使用 FP16" OFF \
"9" "(bf16-unet) 使用 BF16 精度运行 UNet" OFF \
"10" "(fp16-vae) 使用 FP16 精度运行 VAE" OFF \
"11" "(fp32-vae) 使用 FP32 精度运行 VAE" OFF \
"12" "(bf16-vae) 使用 BF16 精度运行 VAE" OFF \
"13" "(disable-ipex-optimize) 禁用 IPEX 优化" OFF \
"14" "(preview-method none) 不使用图片预览" OFF \
"15" "(preview-method auto) 自动选择图片预览方式" OFF \
"16" "(preview-method latent2rgb) 使用 Latent2Rgb 图片预览" OFF \
"17" "(preview-method taesd) 使用 TAESD 图片预览" OFF \
"18" "(use-split-cross-attention) 使用 Split优化" OFF \
"19" "(use-quad-cross-attention) 使用 Quad 优化" OFF \
"20" "(use-pytorch-cross-attention) 使用 PyTorch 方案优化" OFF \
"21" "(disable-xformers) 禁用 xFormers 优化" OFF \
"22" "(gpu-only) 将所有模型, 文本编码器储存在 GPU 中" OFF \
"23" "(highvram) 不使用显存优化 (生图完成后将模型继续保存在显存中)" OFF \
"24" "(normalvram) 使用默认显存优化" OFF \
"25" "(lowvram) 使用显存优化 (将会降低生图速度)" OFF \
"26" "(novram) 使用显存优化 (将会大量降低生图速度)" OFF \
"27" "(cpu) 使用CPU进行生图" OFF \
"28" "(disable-smart-memory) 强制保持模型储存在显存中而不是自动卸载到内存中" OFF \
"29" "(dont-print-server) 禁用日志输出" OFF \
"30" "(quick-test-for-ci) 快速测试 CI" OFF \
"31" "(windows-standalone-build) 启用 Windows 独占功能" OFF \
"32" "(disable-metadata) 禁用在文件中保存提示元数据" OFF \
"33" "(fp8_e4m3fn-text-enc) 使用 FP8 精度 (e4m3fn)" OFF \
"34" "(fp8_e5m2-text-enc) 使用 FP8 精度 (e5m2)" OFF \
"35" "(multi-user) 启用多用户支持" OFF \
"36" "(verbose) 显示更多调试信息" OFF \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
for i in ${dialog_arg}; do
case "${i}" in
1)
arg="--listen"
;;
2)
arg="--auto-launch"
;;
3)
arg="--disable-auto-launch"
;;
4)
arg="--cuda-malloc"
;;
5)
arg="--disable-cuda-malloc"
;;
6)
arg="--dont-upcast-attention"
;;
7)
arg="--force-fp32"
;;
8)
arg="--force-fp16"
;;
9)
arg="--bf16-unet"
;;
10)
arg="--fp16-vae"
;;
11)
arg="--fp32-vae"
;;
12)
arg="--bf16-vae"
;;
13)
arg="--disable-ipex-optimize"
;;
14)
arg="--preview-method none"
;;
15)
arg="--preview-method auto"
;;
16)
arg="--preview-method latent2rgb"
;;
17)
arg="--preview-method taesd"
;;
18)
arg="--use-split-cross-attention"
;;
19)
arg="--use-quad-cross-attention"
;;
20)
arg="--use-pytorch-cross-attention"
;;
21)
arg="--disable-xformers"
;;
22)
arg="--gpu-only"
;;
23)
arg="--highvram"
;;
24)
arg="--normalvram"
;;
25)
arg="--lowvram"
;;
26)
arg="--novram"
;;
27)
arg="--cpu"
;;
28)
arg="--disable-smart-memory"
;;
29)
arg="--dont-print-server"
;;
30)
arg="--quick-test-for-ci"
;;
31)
arg="--windows-standalone-build"
;;
32)
arg="--disable-metadata"
;;
33)
arg="--fp8_e4m3fn-text-enc"
;;
34)
arg="--fp8_e5m2-text-enc"
;;
35)
arg="--multi-user"
;;
36)
arg="--verbose"
;;
esac
launch_args="${arg} ${launch_args}"
done
# 生成启动脚本
term_sd_echo "设置 ComfyUI 启动参数: ${launch_args}"
echo "main.py ${launch_args}" > "${START_PATH}"/term-sd/config/comfyui-launch.conf
else
term_sd_echo "取消设置 ComfyUI 启动参数"
fi
}
# ComfyUI 启动界面
comfyui_launch() {
local dialog_arg
local launch_args
add_comfyui_normal_launch_args # 没有启动参数时自动生成一个
while true; do
launch_args=$(cat "${START_PATH}"/term-sd/config/comfyui-launch.conf)
if is_use_venv; then
launch_args="python ${launch_args}"
else
launch_args=${TERM_SD_PYTHON_PATH}" ${launch_args}"
fi
dialog_arg=$(dialog --erase-on-exit --notags \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 启动选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择启动 ComfyUI / 修改 ComfyUI 启动参数\n当前启动参数: ${launch_args}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 配置预设启动参数" \
"3" "> 修改自定义启动参数" \
"4" "> 重置启动参数" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
term_sd_launch
;;
2)
comfyui_launch_args_setting
;;
3)
comfyui_launch_args_revise
;;
4)
restore_comfyui_launch_args
;;
*)
break
;;
esac
done
}
# ComfyUI 手动输入启动参数界面
# 启动修改界面时将从 <Strat Path>/term-sd/config/comfyui-launch.conf 中读取启动参数
# 可接着上次的启动参数进行修改
comfyui_launch_args_revise() {
local dialog_arg
local launch_args
launch_args=$(cat "${START_PATH}"/term-sd/config/comfyui-launch.conf | awk '{sub("main.py ","")}1')
dialog_arg=$(dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 自定义启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "请输入 ComfyUI 启动参数" \
$(get_dialog_size) \
"${launch_args}" \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
term_sd_echo "设置 ComfyUI 启动参数: ${dialog_arg}"
echo "main.py ${dialog_arg}" > "${START_PATH}"/term-sd/config/comfyui-launch.conf
else
term_sd_echo "取消修改 ComfyUI 启动参数"
fi
}
# 添加 ComfyUI 默认启动参数配置
add_comfyui_normal_launch_args() {
if [[ ! -f "${START_PATH}/term-sd/config/comfyui-launch.conf" ]]; then # 找不到启动配置时默认生成一个
echo "main.py --auto-launch --preview-method auto --disable-smart-memory" > "${START_PATH}"/term-sd/config/comfyui-launch.conf
fi
}
# 重置启动参数
restore_comfyui_launch_args() {
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 重置启动参数选项选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重置 ComfyUI 启动参数 ?" \
$(get_dialog_size)); then
term_sd_echo "重置 ComfyUI 启动参数"
rm -f "${START_PATH}"/term-sd/config/comfyui-launch.conf
add_comfyui_normal_launch_args
else
term_sd_echo "取消重置 ComfyUI 启动参数操作"
fi
}
|
2301_81996401/term-sd
|
modules/comfyui_launch.sh
|
Shell
|
agpl-3.0
| 9,919
|
#!/bin/bash
# ComfyUI 管理
# <ComfyUI>/web 目录已移除, 不再需要插件管理, 参考: https://github.com/comfyanonymous/ComfyUI/pull/7021
comfyui_manager() {
local dialog_arg
cd "${START_PATH}" # 回到最初路径
exit_venv # 确保进行下一步操作前已退出其他虚拟环境
if [[ -d "${COMFYUI_ROOT_PATH}" ]] && ! term_sd_is_dir_empty "${COMFYUI_ROOT_PATH}"; then
while true; do
cd "${COMFYUI_ROOT_PATH}"
dialog_arg=$(dialog --erase-on-exit --notags \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择 ComfyUI 管理选项的功能\n当前更新源: $(git_remote_display)\n当前分支: $(git_branch_display)" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 更新" \
"3" "> 修复更新" \
"4" "> 管理自定义节点" \
"6" "> 切换版本" \
"7" "> 更新源替换" \
"8" "> 更新依赖" \
"9" "> Python 软件包安装 / 重装 / 卸载" \
"10" "> 依赖库版本管理" \
"11" "> 重新安装 PyTorch" \
"12" "> 修复虚拟环境" \
"13" "> 重新构建虚拟环境" \
"14" "> 重新安装" \
"15" "> 卸载" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
comfyui_launch
;;
2)
if is_git_repo; then
term_sd_echo "更新 ComfyUI 中"
git_pull_repository
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 更新结果" \
--ok-label "确认" \
--msgbox "ComfyUI 更新成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 更新结果" \
--ok-label "确认" \
--msgbox "ComfyUI 更新失败" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 更新结果" \
--ok-label "确认" \
--msgbox "ComfyUI 非 Git 安装, 无法更新" \
$(get_dialog_size)
fi
;;
3)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 更新修复选项" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 ComfyUI 更新 ?" \
$(get_dialog_size)); then
git_fix_pointer_offset
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 修复更新" \
--ok-label "确认" \
--msgbox "ComfyUI 修复更新完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 更新修复选项" \
--ok-label "确认" \
--msgbox "ComfyUI 非 Git 安装, 无法修复更新" \
$(get_dialog_size)
fi
;;
4)
comfyui_custom_node_manager
;;
5)
# 已弃用
comfyui_extension_manager
;;
6)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 版本切换选项" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 ComfyUI 版本 ?" \
$(get_dialog_size)); then
git_ver_switch && \
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 版本切换" \
--ok-label "确认" \
--msgbox "ComfyUI 版本切换完成, 当前版本为: $(git_branch_display)" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 版本切换选项" \
--ok-label "确认" \
--msgbox "ComfyUI 非 Git 安装, 无法切换版本" \
$(get_dialog_size)
fi
;;
7)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 更新源切换选项" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 ComfyUI 更新源 ?" \
$(get_dialog_size)); then
comfyui_remote_revise
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 更新源切换选项" \
--ok-label "确认" \
--msgbox "ComfyUI 非 Git 安装, 无法切换更新源" \
$(get_dialog_size)
fi
;;
8)
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 依赖更新选项" \
--yes-label "是" --no-label "否" \
--yesno "是否更新 ComfyUI 的依赖 ?" \
$(get_dialog_size)); then
comfyui_update_depend
fi
;;
9)
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 的 Python 软件包安装 / 重装 / 卸载选项" \
--yes-label "是" --no-label "否" \
--yesno "是否进入 Python 软件包安装 / 重装 / 卸载选项 ?" \
$(get_dialog_size)); then
python_package_manager
fi
;;
10)
python_package_ver_backup_manager
;;
11)
pytorch_reinstall
;;
12)
if is_use_venv; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 虚拟环境修复选项" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 ComfyUI 的虚拟环境 ? " \
$(get_dialog_size)); then
fix_venv
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 虚拟环境修复选项" \
--ok-label "确认" \
--msgbox "ComfyUI 虚拟环境修复完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 虚拟环境修复选项" \
--ok-label "确认" \
--msgbox "虚拟环境功能已禁用, 无法使用该功能" \
$(get_dialog_size)
fi
;;
13)
if is_use_venv; then
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 虚拟环境重建选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重建 ComfyUI 的虚拟环境 ?" \
$(get_dialog_size)); then
comfyui_venv_rebuild
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 虚拟环境重建选项" \
--ok-label "确认" \
--msgbox "ComfyUI 虚拟环境重建完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 虚拟环境重建选项" \
--ok-label "确认" \
--msgbox "虚拟环境功能已禁用, 无法使用该功能" \
$(get_dialog_size)
fi
;;
14)
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 重新安装选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重新安装 ComfyUI ?" \
$(get_dialog_size)); then
cd "${START_PATH}"
rm -f "${START_PATH}/term-sd/task/comfyui_install.sh"
exit_venv
install_comfyui
break
fi
;;
15)
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 删除选项" \
--yes-label "是" --no-label "否" \
--yesno "是否删除 ComfyUI ?" \
$(get_dialog_size)); then
term_sd_echo "请再次确认是否删除 ComfyUI (yes/no) ?"
term_sd_echo "警告: 该操作将永久删除 ComfyUI"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
yes|y|YES|Y)
term_sd_echo "删除 ComfyUI 中"
exit_venv
cd ..
rm -rf "${COMFYUI_ROOT_PATH}"
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 删除选项" \
--ok-label "确认" \
--msgbox "删除 ComfyUI 完成" \
$(get_dialog_size)
break
;;
*)
term_sd_echo "取消删除操作"
;;
esac
else
term_sd_echo "取消删除操作"
fi
;;
*)
break
;;
esac
done
else
if (dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 安装选项" \
--yes-label "是" --no-label "否" \
--yesno "检测到当前未安装 ComfyUI , 是否进行安装 ?" \
$(get_dialog_size)); then
rm -f "${START_PATH}/term-sd/task/comfyui_install.sh"
install_comfyui
fi
fi
}
# ComfyUI 依赖更新功能
# 解决 ComfyUI 部分依赖过旧导致报错的问题
comfyui_update_depend() {
# 更新前的准备
download_mirror_select # 下载镜像源选择
pip_install_mode_select upgrade # 安装方式选择
if term_sd_install_confirm "是否更新 ComfyUI 依赖 ?"; then
term_sd_print_line "ComfyUI 依赖更新"
term_sd_echo "更新 ComfyUI 依赖中"
term_sd_tmp_disable_proxy
enter_venv
python_package_update "requirements.txt"
exit_venv
term_sd_tmp_enable_proxy
term_sd_echo "更新 ComfyUI 依赖结束"
term_sd_pause
else
term_sd_echo "取消更新 ComfyUI 依赖"
fi
clean_install_config # 清理安装参数
}
|
2301_81996401/term-sd
|
modules/comfyui_manager.sh
|
Shell
|
agpl-3.0
| 14,194
|
#!/bin/bash
# Fooocus 启动参数设置
# 设置的启动参数保存在 <Start Path>/term-sd/config/fooocus-launch.conf
fooocus_launch_args_setting() {
local arg
local dialog_arg
local launch_args
local i
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Fooocus 管理" \
--backtitle "Fooocus 启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--checklist "请选择 Fooocus 启动参数, 确认之后将覆盖原有启动参数配置" \
$(get_dialog_size_menu) \
"1" "(listen) 开放远程连接" OFF \
"2" "(disable-header-check) 禁用请求头部检查" OFF \
"3" "(in-browser) 启动后自动打开浏览器" OFF \
"4" "(disable-in-browser) 禁用自动打开浏览器" OFF \
"5" "(async-cuda-allocation) 启用 CUDA 流顺序内存分配器" OFF \
"6" "(disable-async-cuda-allocation) 禁用 CUDA 流顺序内存分配器" OFF \
"7" "(disable-attention-upcast) 使用向上采样法提高精度" OFF \
"8" "(all-in-fp32) 强制使用 FP32" OFF \
"9" "(all-in-fp16) 强制使用 FP16" OFF \
"10" "(unet-in-bf16) 使用 BF16 精度运行 UNet" OFF \
"11" "(unet-in-fp16) 使用 FP16 精度运行 UNet" OFF \
"12" "(unet-in-fp8-e4m3fn) 使用 FP8(e4m3fn) 精度运行 UNet" OFF \
"13" "(unet-in-fp8-e5m2) 使用 FP8(e5m2) 精度运行 UNet" OFF \
"14" "(vae-in-fp16) 使用 FP16 精度运行 VAE" OFF \
"15" "(vae-in-fp32) 使用 FP32 精度运行 VAE" OFF \
"16" "(vae-in-bf16) 使用 BF16 精度运行 VAE" OFF \
"17" "(clip-in-fp8-e4m3fn) 使用 FP8(e4m3fn) 精度运行文本编码器" OFF \
"18" "(clip-in-fp8-e5m2) 使用 FP8(e5m2) 精度运行文本编码器" OFF \
"19" "(clip-in-fp16) 使用 FP16精度运行文本编码器" OFF \
"20" "(clip-in-fp32) 使用 FP32精度运行文本编码器" OFF \
"21" "(directml) 使用 DirectML 作为后端" OFF \
"22" "(disable-ipex-hijack) 禁用 IPEX 修复" OFF \
"23" "(attention-split) 使用 Split 优化" OFF \
"24" "(attention-quad) 使用 Quad 优化" OFF \
"25" "(attention-pytorch) 使用 PyTorch 方案优化" OFF \
"26" "(disable-xformers) 禁用 xFormers 优化" OFF \
"27" "(always-gpu) 将所有模型, 文本编码器储存在 GPU 中" OFF \
"28" "(always-high-vram) 不使用显存优化" OFF \
"29" "(always-normal-vram) 使用默认显存优化" OFF \
"30" "(always-low-vram) 使用显存优化 (将会降低生图速度)" OFF \
"31" "(always-no-vram) 使用显存优化 (将会大量降低生图速度)" OFF \
"32" "(always-cpu) 使用 CPU 进行生图" OFF \
"33" "(always-offload-from-vram) 生图完成后将模型从显存中卸载" OFF \
"34" "(pytorch-deterministic) 将 PyTorch 配置为使用确定性算法" OFF \
"35" "(disable-server-log) 禁用服务端日志输出" OFF \
"36" "(debug-mode) 启用 Debug 模式" OFF \
"37" "(is-windows-embedded-python) 启用 Windows 独占功能" OFF \
"38" "(disable-server-info) 禁用服务端信息输出" OFF \
"39" "(language zh) 启用中文" OFF \
"40" "(theme dark) 使用黑暗主题" OFF \
"41" "(disable-image-log) 禁用将图像和日志写入硬盘" OFF \
"42" "(disable-analytics) 禁用 Gradio 分析" OFF \
"43" "(preset default) 使用默认模型预设" OFF \
"44" "(preset sai) 使用 SAI 模型预设" OFF \
"45" "(preset lcm) 使用 LCM 模型预设" OFF \
"46" "(preset anime) 使用 Anime 模型预设" OFF \
"47" "(preset realistic) 使用 Realistic 模型预设" OFF \
"48" "(preset term_sd) 使用 Term-SD 模型预设" OFF \
"49" "(share) 启用 Gradio 共享" OFF \
"50" "(disable-offload-from-vram) 禁用显存自动卸载" OFF \
"51" "(multi-user) 启用多用户支持" OFF \
"52" "(disable-image-log) 禁用保存图片日志" OFF \
"53" "(disable-analytics) 禁用 Gradio 分析" OFF \
"54" "(disable-metadata) 禁用保存生图信息到图片中" OFF \
"55" "(disable-preset-download) 禁用下载预设中的模型" OFF \
"56" "(enable-describe-uov-image) 为 uov 图像描述提示词" OFF \
"57" "(always-download-new-model) 总是下载最新的模型" ON \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
for i in ${dialog_arg}; do
case "${i}" in
1)
arg="--listen"
;;
2)
arg="--disable-header-check"
;;
3)
arg="--in-browser"
;;
4)
arg="--disable-in-browser"
;;
5)
arg="--async-cuda-allocation"
;;
6)
arg="--disable-async-cuda-allocation"
;;
7)
arg="--disable-attention-upcast"
;;
8)
arg="--all-in-fp32"
;;
9)
arg="--all-in-fp16"
;;
10)
arg="--unet-in-bf16"
;;
11)
arg="--unet-in-fp16"
;;
12)
arg="--unet-in-fp8-e4m3fn"
;;
13)
arg="--unet-in-fp8-e5m2"
;;
14)
arg="--vae-in-fp16"
;;
15)
arg="--vae-in-fp32"
;;
16)
arg="--vae-in-bf16"
;;
17)
arg="--clip-in-fp8-e4m3fn"
;;
18)
arg="--clip-in-fp8-e5m2"
;;
19)
arg="--clip-in-fp16"
;;
20)
arg="--clip-in-fp32"
;;
21)
arg="--directml"
;;
22)
arg="--disable-ipex-hijack"
;;
23)
arg="--attention-split"
;;
24)
arg="--attention-quad"
;;
25)
arg="--attention-pytorch"
;;
26)
arg="--disable-xformers"
;;
27)
arg="--always-gpu"
;;
28)
arg="--always-high-vram"
;;
29)
arg="--always-normal-vram"
;;
30)
arg="--always-low-vram"
;;
31)
arg="--always-no-vram"
;;
32)
arg="--always-cpu"
;;
33)
arg="--always-offload-from-vram"
;;
34)
arg="--pytorch-deterministic"
;;
35)
arg="--disable-server-log"
;;
36)
arg="--debug-mode"
;;
37)
arg="--is-windows-embedded-python"
;;
38)
arg="--disable-server-info"
;;
39)
arg="--language zh"
;;
40)
arg="--theme dark"
;;
41)
arg="--disable-image-log"
;;
42)
arg="--disable-analytics"
;;
43)
arg="--preset default"
;;
44)
arg="--preset sai"
;;
45)
arg="--preset lcm"
;;
46)
arg="--preset anime"
;;
47)
arg="--preset realistic"
;;
48)
arg="--preset term_sd"
;;
49)
arg="--share"
;;
50)
arg="--disable-offload-from-vram"
;;
51)
arg="--multi-user"
;;
52)
arg="--disable-image-log"
;;
53)
arg="--disable-analytics"
;;
54)
arg="--disable-metadata"
;;
55)
arg="--disable-preset-download"
;;
56)
arg="--enable-describe-uov-image"
;;
57)
arg="--always-download-new-model"
;;
esac
launch_args="${arg} ${launch_args}"
done
term_sd_echo "设置 Fooocus 启动参数: ${launch_args}"
echo "launch.py ${launch_args}" > "${START_PATH}"/term-sd/config/fooocus-launch.conf
else
term_sd_echo "取消 Fooocus 设置启动参数"
fi
}
# Fooocus 启动界面
fooocus_launch() {
local dialog_arg
local launch_args
add_fooocus_normal_launch_args
while true; do
launch_args=$(cat "${START_PATH}"/term-sd/config/fooocus-launch.conf)
if is_use_venv; then
launch_args="python ${launch_args}"
else
launch_args="${TERM_SD_PYTHON_PATH} ${launch_args}"
fi
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Fooocus 管理" \
--backtitle "Fooocus 启动选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择启动 Fooocus / 修改 Fooocus 启动参数\n当前启动参数: ${launch_args}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 配置预设启动参数" \
"3" "> 修改自定义启动参数" \
"4" "> 重置启动参数" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
term_sd_launch
;;
2)
fooocus_launch_args_setting
;;
3)
fooocus_manual_launch
;;
4)
restore_fooocus_launch_args
;;
*)
break
;;
esac
done
}
# Fooocus 修改启动参数功能
# 启动修改界面时将从 <Start Path>/term-sd/config/fooocus-launch.conf 中读取启动参数
# 可接着上次的启动参数进行修改
fooocus_manual_launch() {
local dialog_arg
local launch_args
launch_args=$(cat "${START_PATH}"/term-sd/config/fooocus-launch.conf | awk '{sub("launch.py ","")}1')
dialog_arg=$(dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 自定义启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "请输入 Fooocus 启动参数" \
$(get_dialog_size) \
"${launch_args}" \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
term_sd_echo "设置 Fooocus 启动参数: ${dialog_arg}"
echo "launch.py ${dialog_arg}" > "${START_PATH}"/term-sd/config/fooocus-launch.conf
else
term_sd_echo "取消修改 Fooocus 启动参数"
fi
}
# 添加 Fooocus 默认启动参数配置
add_fooocus_normal_launch_args() {
if [[ ! -f "${START_PATH}/term-sd/config/fooocus-launch.conf" ]]; then # 找不到启动配置时默认生成一个
echo "launch.py --language zh --preset term_sd --disable-offload-from-vram --disable-analytics --always-download-new-model" > "${START_PATH}"/term-sd/config/fooocus-launch.conf
fi
}
# 重置启动参数
restore_fooocus_launch_args() {
if (dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 重置启动参数选项选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重置 Fooocus 启动参数 ?" \
$(get_dialog_size)); then
term_sd_echo "重置 Fooocus 启动参数"
rm -f "${START_PATH}"/term-sd/config/fooocus-launch.conf
add_fooocus_normal_launch_args
else
term_sd_echo "取消重置 Fooocus 启动参数操作"
fi
}
|
2301_81996401/term-sd
|
modules/fooocus_launch.sh
|
Shell
|
agpl-3.0
| 13,134
|
#!/bin/bash
# Fooocus 管理界面
fooocus_manager() {
local dialog_arg
cd "${START_PATH}" # 回到最初路径
exit_venv # 确保进行下一步操作前已退出其他虚拟环境
if [[ -d "${FOOOCUS_ROOT_PATH}" ]] && ! term_sd_is_dir_empty "${FOOOCUS_ROOT_PATH}"; then
while true; do
cd "${FOOOCUS_ROOT_PATH}"
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Fooocus 管理" \
--backtitle "Fooocus 管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择 Fooocus 管理选项的功能\n当前更新源: $(git_remote_display)\n当前分支: $(git_branch_display)" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 更新" \
"3" "> 修复更新" \
"4" "> 切换版本" \
"5" "> 更新源替换" \
"6" "> 更新依赖" \
"7" "> Python 软件包安装 / 重装 / 卸载" \
"8" "> 依赖库版本管理" \
"9" "> 重新安装 PyTorch" \
"10" "> 修复虚拟环境" \
"11" "> 重新构建虚拟环境" \
"12" "> 重新安装" \
"13" "> 卸载" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
fooocus_launch
;;
2)
if is_git_repo; then
term_sd_echo "更新 Fooocus 中"
git_pull_repository
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 更新结果" \
--ok-label "确认" \
--msgbox "Fooocus 更新成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 更新结果" \
--ok-label "确认" \
--msgbox "Fooocus 更新失败" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 更新结果" \
--ok-label "确认" \
--msgbox "Fooocus 非 Git 安装, 无法更新" \
$(get_dialog_size)
fi
;;
3)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 更新修复选项" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 Fooocus 更新 ?" \
$(get_dialog_size)); then
git_fix_pointer_offset
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 更新修复选项" \
--ok-label "确认" \
--msgbox "Fooocus 修复更新完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 更新修复选项" \
--ok-label "确认" \
--msgbox "Fooocus 非 Git 安装, 无法修复更新" \
$(get_dialog_size)
fi
;;
4)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 版本切换选项" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 Fooocus 版本 ?" \
$(get_dialog_size)); then
git_ver_switch && \
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 版本切换" \
--ok-label "确认" \
--msgbox "Fooocus 版本切换完成, 当前版本为: $(git_branch_display)" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 版本切换选项" \
--ok-label "确认" \
--msgbox "Fooocus 非 Git 安装, 无法修复更新" \
$(get_dialog_size)
fi
;;
5)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 更新源切换选项" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 Fooocus 更新源 ?" \
$(get_dialog_size)); then
fooocus_remote_revise
fi
else
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 更新源切换选项" \
--ok-label "确认" \
--msgbox "Fooocus 非 Git 安装, 无法切换更新源" \
$(get_dialog_size)
fi
;;
6)
if (dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 依赖更新选项" \
--yes-label "是" --no-label "否" \
--yesno "是否更新 Fooocus 的依赖 ?" \
$(get_dialog_size)); then
fooocus_update_depend
fi
;;
7)
if (dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 的 Python 软件包安装 / 重装 / 卸载选项" \
--yes-label "是" --no-label "否" \
--yesno "是否进入 Python 软件包安装 / 重装 / 卸载选项 ?" \
$(get_dialog_size)); then
python_package_manager
fi
;;
8)
python_package_ver_backup_manager
;;
9)
pytorch_reinstall
;;
10)
if is_use_venv; then
if (dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 虚拟环境修复选项" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 Fooocus 的虚拟环境 ?" \
$(get_dialog_size)); then
fix_venv
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 虚拟环境修复选项" \
--ok-label "确认" \
--msgbox "Fooocus 虚拟环境修复完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 虚拟环境修复选项" \
--ok-label "确认" \
--msgbox "虚拟环境功能已禁用, 无法使用该功能" \
$(get_dialog_size)
fi
;;
11)
if is_use_venv; then
if (dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 虚拟环境重建选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重建 Fooocus 的虚拟环境 ?" \
$(get_dialog_size)); then
fooocus_venv_rebuild
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 虚拟环境重建选项" \
--ok-label "确认" \
--msgbox "Fooocus 虚拟环境重建完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 虚拟环境重建选项" \
--ok-label "确认" \
--msgbox "虚拟环境功能已禁用, 无法使用该功能" \
$(get_dialog_size)
fi
;;
12)
if (dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 重新安装选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重新安装 Fooocus ?" \
$(get_dialog_size)); then
cd "${START_PATH}"
rm -f "${START_PATH}/term-sd/task/fooocus_install.sh"
exit_venv
install_fooocus
break
fi
;;
13)
if (dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 删除选项" \
--yes-label "是" --no-label "否" \
--yesno "是否删除 Fooocus ?" \
$(get_dialog_size)); then
term_sd_echo "请再次确认是否删除 Fooocus (yes/no) ?"
term_sd_echo "警告: 该操作将永久删除 Fooocus"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
yes|y|YES|Y)
term_sd_echo "删除 Fooocus 中"
exit_venv
cd ..
rm -rf "${FOOOCUS_ROOT_PATH}"
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 删除选项" \
--ok-label "确认" \
--msgbox "删除 Fooocus 完成" \
$(get_dialog_size)
break
;;
*)
term_sd_echo "取消删除操作"
;;
esac
fi
;;
*)
break
;;
esac
done
else
if (dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 安装选项" \
--yes-label "是" --no-label "否" \
--yesno "检测到当前未安装 Fooocus , 是否进行安装 ?" \
$(get_dialog_size)); then
rm -f "${START_PATH}/term-sd/task/fooocus_install.sh"
install_fooocus
fi
fi
}
# Fooocus 依赖更新
fooocus_update_depend() {
# 更新前的准备
download_mirror_select # 下载镜像源选择
pip_install_mode_select upgrade # 安装方式选择
if term_sd_install_confirm "是否更新 Fooocus 依赖 ?"; then
term_sd_print_line "Fooocus 依赖更新"
term_sd_echo "更新 Fooocus 依赖中"
term_sd_tmp_disable_proxy
enter_venv
python_package_update "requirements_versions.txt"
exit_venv
term_sd_tmp_enable_proxy
term_sd_echo "更新 Fooocus 依赖结束"
term_sd_pause
fi
clean_install_config # 清理安装参数
}
|
2301_81996401/term-sd
|
modules/fooocus_manager.sh
|
Shell
|
agpl-3.0
| 13,643
|
#!/bin/bash
# modelscope下载链接格式(旧版)
# https://modelscope.cn/api/v1/models/作者/仓库/repo?Revision=分支名&FilePath=文件名
# https://modelscope.cn/api/v1/models/作者/仓库/repo?Revision=分支名&FilePath=文件夹/文件名
# modelscope模型下载
# 使用格式:
# get_modelscope_model 作者/仓库/仓库分支/仓库文件路径/文件名 本地下载路径
# get_modelscope_model 作者/仓库/仓库分支/文件名 本地下载路径
# 例:
# get_modelscope_model licyks/sd-model/master/sd_1.5/v1-5-pruned-emaonly.safetensors ./stable-diffusion-webui/models/Stable-diffusion
# get_modelscope_model licyks/controlnet_v1.1/master/t2iadapter_zoedepth_sd15v1.pth ./stable-diffusion-webui/
get_modelscope_model() {
local url=$1 # 链接
local path=$2 # 下载路径
local name=$3 # 要保存的名称
local aria2_tmp_path # Aria2 缓存文件
local file_path # 下载到本地的文件
local modelscope_user # ModelScope 用户名
local modelscope_model_name # ModelScope 仓库名
local modelscope_model_branch # ModelScope 仓库分支
local modelscope_model_path # ModelScope 仓库文件路径
# 处理 ModelScope 链接
modelscope_user=$(echo ${url} | awk '{gsub(/[/]/, " ")}1' | awk '{print $1}')
modelscope_model_name=$(echo ${url} | awk '{gsub(/[/]/, " ")}1' | awk '{print $2}')
modelscope_model_branch=$(echo ${url} | awk '{gsub(/[/]/, " ")}1' | awk '{print $3}')
modelscope_model_path=$(echo ${url} | awk '{sub("'${modelscope_user}/${modelscope_model_name}/${modelscope_model_branch}/'","")}1')
url="https://modelscope.cn/models/${modelscope_user}/${modelscope_model_name}/resolve/${modelscope_model_branch}/${modelscope_model_path}"
if [[ -z "${path}" ]]; then # 下载路径为空时
path=$(pwd)
name=$(basename "${url}")
elif [[ -z "${name}" ]]; then # 要保存的名称为空时
# 去除下载路径中末尾的 / 字符
path=$(awk '{ if (substr($0, length($0), 1) == "/") { print substr($0, 1, length($0) - 1) } else { print $0 } }' <<< ${path})
name=$(basename "${url}")
else
# 去除下载路径中末尾的 / 字符
path=$(awk '{ if (substr($0, length($0), 1) == "/") { print substr($0, 1, length($0) - 1) } else { print $0 } }' <<< ${path})
fi
aria2_tmp_path="${path}/${name}.aria2"
file_path="${path}/${name}"
if term_sd_is_debug; then
term_sd_echo "url: ${url}"
term_sd_echo "name: ${name}"
term_sd_echo "path: ${path}"
term_sd_echo "aria2_tmp_path: ${aria2_tmp_path}"
term_sd_echo "file_path: ${file_path}"
term_sd_echo "modelscope_user: ${modelscope_user}"
term_sd_echo "modelscope_model_name: ${modelscope_model_name}"
term_sd_echo "modelscope_model_branch: ${modelscope_model_branch}"
term_sd_echo "modelscope_model_path: ${modelscope_model_path}"
term_sd_echo "ARIA2_MULTI_THREAD: ${ARIA2_MULTI_THREAD}"
term_sd_echo "cmd: aria2c --file-allocation=none --summary-interval=0 --console-log-level=error -s 64 -c -x ${ARIA2_MULTI_THREAD} -k 1M ${url} -d ${path} -o ${name}"
fi
if [[ ! -f "${file_path}" ]]; then
term_sd_echo "下载 ${name} 中, 路径: ${file_path}"
term_sd_try aria2c --file-allocation=none --summary-interval=0 --console-log-level=error -s 64 -c -x "${ARIA2_MULTI_THREAD}" -k 1M "${url}" -d "${path}" -o "${name}"
else
if [[ -f "${aria2_tmp_path}" ]]; then
term_sd_echo "恢复下载 ${name} 中, 路径: ${file_path}"
term_sd_try aria2c --file-allocation=none --summary-interval=0 --console-log-level=error -s 64 -c -x "${ARIA2_MULTI_THREAD}" -k 1M "${url}" -d "${path}" -o "${name}"
else
term_sd_echo "${name} 文件已存在, 路径: ${file_path}"
fi
fi
}
|
2301_81996401/term-sd
|
modules/get_modelscope_model.sh
|
Shell
|
agpl-3.0
| 3,868
|
# 读取注册表配置
$internet_setting = Get-ItemProperty -Path "HKCU:\Software\Microsoft\Windows\CurrentVersion\Internet Settings"
$proxy_addr = $($internet_setting.ProxyServer)
# 提取代理地址
if (($proxy_addr -match "http=(.*?);") -or ($proxy_addr -match "https=(.*?);")) {
$proxy_value = $matches[1]
# 去除 http / https 前缀
$proxy_value = $proxy_value.ToString().Replace("http://", "").Replace("https://", "")
$proxy_value = "http://${proxy_value}"
} elseif ($proxy_addr -match "socks=(.*)") {
$proxy_value = $matches[1]
# 去除 socks 前缀
$proxy_value = $proxy_value.ToString().Replace("http://", "").Replace("https://", "")
$proxy_value = "socks://${proxy_value}"
} else {
$proxy_value = "http://${proxy_addr}"
}
if ($internet_setting.ProxyEnable -eq 1) {
Write-Host $proxy_value
}
|
2301_81996401/term-sd
|
modules/get_windows_proxy_config.ps1
|
PowerShell
|
agpl-3.0
| 849
|
#!/bin/bash
# Term-SD 初始化模块
term_sd_init() {
local sum=$(( $(ls "${START_PATH}"/term-sd/modules/*.sh | wc -w) - 1 )) # 需要加载的模块数量
local count=1
local module_name
local i
for i in "${START_PATH}"/term-sd/modules/*.sh; do
[[ "${i}" == "${START_PATH}/term-sd/modules/init.sh" ]] && continue
module_name=${i#${START_PATH}/term-sd/modules/}
module_name=${module_name%.sh}
printf "[\033[33m$(date "+%Y-%m-%d %H:%M:%S")\033[0m][\033[36mTerm-SD\033[0m]\033[36m::\033[0m [${count}/${sum}] 加载: ${module_name} \r"
count=$(( $count + 1 ))
. "${i}"
done
printf "[\033[33m$(date "+%Y-%m-%d %H:%M:%S")\033[0m][\033[36mTerm-SD\033[0m]\033[36m::\033[0m 初始化 Term-SD 完成 \n"
term_sd_print_line
}
# Term-SD 初始化模块(带进度条)
term_sd_init_new() {
local sum=$(( $(ls "${START_PATH}"/term-sd/modules/*.sh | wc -w) - 1 )) # 需要加载的模块数量
local count=1
local bar_length=$(( SHELL_WIDTH - 50 )) # 初始进度条的总长度
local i
for i in "${START_PATH}"/term-sd/modules/*.sh; do
[[ "${i}" == "${START_PATH}/term-sd/modules/init.sh" ]] && continue # 避免重新初始化 init.sh 脚本
term_sd_process_bar "${bar_length}" "${count}" "${sum}" # 输出进度条
count=$(( count + 1 ))
. "${i}" # 加载模块
done
term_sd_echo "初始化 Term-SD 完成"
term_sd_print_line
}
# 进度条生成功能(开了只会降低加载速度)
# 使用:
# term_sd_process_bar <进度条总长度> <已完成进度> <总进度>
term_sd_process_bar() {
local count=$2
local sum=$3
local mark
local bar_length
local bar_display='█' # 已完成的进度显示效果
local bar
local bar_length_sum=$1
local i
mark=$(echo $(awk 'BEGIN {print '$count' / '$sum' * 100 }') | awk -F'.' '{print $1}') # 加载进度百分比
bar_length=$(echo $(awk 'BEGIN {print '$count' / '$sum' * '$bar_length_sum' }') | awk -F '.' '{print $1}') # 进度条已完成的实时长度
for i in $(seq 1 ${bar_length_sum}); do # 这个循环将空的进度条填上一堆空格
if [[ "${i}" -gt "${bar_length}" ]]; then # 更换进度条的内容
bar_display=' '
fi
bar="${bar}${bar_display}" # 一开始是空的, 通过循环填上一堆空格, 然后逐渐减少空格数量, 增加方块符号的数量
done
printf "[\033[33m$(date "+%Y-%m-%d %H:%M:%S")\033[0m][\033[36mTerm-SD\033[0m]\033[36m::\033[0m 加载模块中|${bar}| ${mark}%%\r"
[[ "${count}" == "${sum}" ]] && echo
}
# 无进度显示的初始化功能(增加进度显示只会降低加载速度)
term_sd_init_no_bar() {
local i
for i in "${START_PATH}"/term-sd/modules/*.sh; do
[[ "${i}" == "${START_PATH}/term-sd/modules/init.sh" ]] && continue
. "${i}"
done
term_sd_echo "初始化 Term-SD 完成"
term_sd_print_line
}
# 初始化功能
if [[ -f "${START_PATH}/term-sd/config/term-sd-bar.conf" ]]; then
case "$(cat "${START_PATH}/term-sd/config/term-sd-bar.conf")" in
none)
term_sd_init_no_bar
;;
new)
term_sd_init_new
;;
*)
term_sd_init
;;
esac
else
term_sd_init
fi
|
2301_81996401/term-sd
|
modules/init.sh
|
Shell
|
agpl-3.0
| 3,360
|
#!/bin/bash
# 安装 ComfyUI 的功能
# 使用 COMFYUI_EXTENSION_INSTALL_LIST 全局变量读取要安装的 ComfyUI 插件
# 使用 COMFYUI_CUSTOM_NODE_INSTALL_LIST 全局变量读取要安装的 ComfyUI 自定义节点
# 使用 COMFYUI_DOWNLOAD_MODEL_LIST 全局变量读取要下载的模型
install_comfyui() {
local cmd_sum
local cmd_point
local i
if [[ -f "${START_PATH}/term-sd/task/comfyui_install.sh" ]]; then # 检测到有未完成的安装任务时直接执行安装任务
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/comfyui_install.sh" | wc -l) + 1 )) # 统计命令行数
term_sd_print_line "ComfyUI 安装"
for (( cmd_point=1; cmd_point <= cmd_sum; cmd_point++ )); do
term_sd_echo "ComfyUI 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/comfyui_install.sh" "${cmd_point}" # 执行安装命令
if [[ ! "$?" == 0 ]]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 安装结果" \
--ok-label "确认" \
--msgbox "ComfyUI 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "ComfyUI 安装结束"
rm -f "${START_PATH}/term-sd/task/comfyui_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 安装结果" \
--ok-label "确认" \
--msgbox "ComfyUI 安装结束, 选择确定进入管理界面" \
$(get_dialog_size)
comfyui_manager # 进入管理界面
else
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
# comfyui_extension_install_select # 插件选择
comfyui_custom_node_install_select # 自定义节点选择
comfyui_download_model_select # 模型选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否安装 ComfUI ?"; then
term_sd_print_line "ComfyUI 安装"
term_sd_echo "生成安装任务中"
term_sd_set_install_env_value >> "${START_PATH}/term-sd/task/comfyui_install.sh" # 环境变量
cat "${START_PATH}/term-sd/install/comfyui/comfyui_core.sh" >> "${START_PATH}/term-sd/task/comfyui_install.sh" # 核心组件
# 启用代理
echo "__term_sd_task_sys term_sd_tmp_enable_proxy" >> "${START_PATH}/term-sd/task/comfyui_install.sh"
# 读取安装插件命令
if [[ ! -z "${COMFYUI_EXTENSION_INSTALL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"安装插件中\"" >> "${START_PATH}/term-sd/task/comfyui_install.sh"
# 读取安装插件命令列表
for i in ${COMFYUI_EXTENSION_INSTALL_LIST}; do
cat "${START_PATH}/term-sd/install/comfyui/comfyui_extension.sh" | grep -w ${i} | awk '{sub(" ON "," ") ; sub(" OFF "," ")}1' >> "${START_PATH}/term-sd/task/comfyui_install.sh" # 插件
done
fi
# 读取安装自定义节点命令
if [[ ! -z "${COMFYUI_CUSTOM_NODE_INSTALL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"安装自定义节点中\"" >> "${START_PATH}/term-sd/task/comfyui_install.sh"
# 读取安装自定义节点列表
for i in ${COMFYUI_CUSTOM_NODE_INSTALL_LIST}; do
cat "${START_PATH}/term-sd/install/comfyui/comfyui_custom_node.sh" | grep -w ${i} | awk '{sub(" ON "," ") ; sub(" OFF "," ")}1' >> "${START_PATH}/term-sd/task/comfyui_install.sh" # 插件
done
fi
# 取消代理
echo "__term_sd_task_sys term_sd_tmp_disable_proxy" >> "${START_PATH}/term-sd/task/comfyui_install.sh"
# 读取模型下载命令
if [[ ! -z "${COMFYUI_DOWNLOAD_MODEL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"下载模型中\"" >> "${START_PATH}/term-sd/task/comfyui_install.sh"
if is_use_modelscope_src; then
# 读取模型
for i in ${COMFYUI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/comfyui/comfyui_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/comfyui_install.sh" # 插件所需的模型
done
# 读取扩展的模型
for i in ${COMFYUI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/comfyui/comfyui_custom_node_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/comfyui_install.sh" # 自定义节点所需的模型
done
else
# 恢复代理
echo "__term_sd_task_sys term_sd_tmp_enable_proxy" >> "${START_PATH}/term-sd/task/comfyui_install.sh"
# 读取模型
for i in ${COMFYUI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/comfyui/comfyui_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/comfyui_install.sh" # 插件所需的模型
done
# 读取扩展的模型
for i in ${COMFYUI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/comfyui/comfyui_custom_node_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/comfyui_install.sh" # 自定义节点所需的模型
done
fi
fi
unset COMFYUI_EXTENSION_INSTALL_LIST
unset COMFYUI_CUSTOM_NODE_INSTALL_LIST
unset COMFYUI_DOWNLOAD_MODEL_LIST
term_sd_echo "任务队列生成完成"
term_sd_echo "开始安装 ComfyUI"
# 执行安装命令
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/comfyui_install.sh" | wc -l) + 1 )) # 统计命令行数
for (( cmd_point=1; cmd_point <= cmd_sum; cmd_point++ )); do
term_sd_echo "ComfyUI 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/comfyui_install.sh" "${cmd_point}" # 执行安装命令
if [[ ! "$?" == 0 ]]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 安装结果" \
--ok-label "确认" \
--msgbox "ComfyUI 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "ComfyUI 安装结束"
rm -f "${START_PATH}/term-sd/task/comfyui_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "ComfyUI 管理" \
--backtitle "ComfyUI 安装结果" \
--ok-label "确认" \
--msgbox "ComfyUI 安装结束, 选择确定进入管理界面" \
$(get_dialog_size)
comfyui_manager # 进入管理界面
else
unset COMFYUI_EXTENSION_INSTALL_LIST
unset COMFYUI_CUSTOM_NODE_INSTALL_LIST
unset COMFYUI_DOWNLOAD_MODEL_LIST
clean_install_config # 清理安装参数
fi
fi
}
# ComfyUI 插件选择
# 将选择的 ComfyUI 插件保存在 COMFYUI_EXTENSION_INSTALL_LIST 全局变量
comfyui_extension_install_select() {
COMFYUI_EXTENSION_INSTALL_LIST=$(dialog --erase-on-exit --notags \
--title "ComfyUI 安装" \
--backtitle "ComfyUI 插件安装选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要安装的 ComfyUI 插件" \
$(get_dialog_size_menu) \
$(cat "${START_PATH}/term-sd/install/comfyui/dialog_comfyui_extension.sh") \
3>&1 1>&2 2>&3)
}
# ComfyUI 自定义节点选择
# 将选择的 ComfyUI 自定义节点保存在 COMFYUI_CUSTOM_NODE_INSTALL_LIST 全局变量中
comfyui_custom_node_install_select() {
COMFYUI_CUSTOM_NODE_INSTALL_LIST=$(dialog --erase-on-exit --notags \
--title "ComfyUI 安装" \
--backtitle "ComfyUI 自定义节点安装选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要安装的 ComfyUI 自定义节点" \
$(get_dialog_size_menu) \
$(cat "${START_PATH}/term-sd/install/comfyui/dialog_comfyui_custom_node.sh") \
3>&1 1>&2 2>&3)
}
# 模型选择
# 使用 COMFYUI_CUSTOM_NODE_INSTALL_LIST 全局变量读取 ComfyUI 自定义节点对应需要下载的模型
# 将选择的模型保存在 COMFYUI_DOWNLOAD_MODEL_LIST 全局变量中
comfyui_download_model_select() {
local model_list_file
local dialog_list_file
local model_list
local i
# 插件模型列表选择
if is_use_modelscope_src; then
model_list_file="comfyui_custom_node_ms_model.sh"
dialog_list_file="dialog_comfyui_ms_model.sh"
else
model_list_file="comfyui_custom_node_hf_model.sh"
dialog_list_file="dialog_comfyui_hf_model.sh"
fi
term_sd_echo "生成模型选择列表中"
# 查找插件对应模型的编号
for i in ${COMFYUI_CUSTOM_NODE_INSTALL_LIST}; do
model_list="${model_list} $(cat "${START_PATH}"/term-sd/install/comfyui/${model_list_file} | grep -w ${i} | awk 'NR==1{if ($NF!="") {print $1 " " $(NF-1) " " $NF} }')"
done
# 模型选择(包含基础模型和插件的模型)
COMFYUI_DOWNLOAD_MODEL_LIST=$(dialog --erase-on-exit --notags \
--title "ComfyUI 安装" \
--backtitle "ComfyUI 模型下载选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要下载的 ComfyUI 模型\n注:\n1、模型后面括号内数字为模型的大小\n2、需要根据自己的需求勾选需要下载的模型" \
$(get_dialog_size_menu) \
"_null_" "=====基础模型选择=====" ON \
$(cat "${START_PATH}/term-sd/install/comfyui/${dialog_list_file}") \
"_null_" "=====插件模型选择=====" ON \
${model_list} \
3>&1 1>&2 2>&3)
}
# 写入 ComfyUI 配置文件
# 保存在 <ComfyUI Path>/user/default/comfy.settings.json 中
set_comfyui_normal_config() {
term_sd_echo "写入 ComfyUI 默认配置中"
term_sd_mkdir "${COMFYUI_ROOT_PATH}"/user/default
cp -f "${START_PATH}/term-sd/install/comfyui/comfy.settings.json" "${COMFYUI_ROOT_PATH}"/user/default/comfy.settings.json
}
|
2301_81996401/term-sd
|
modules/install_comfyui.sh
|
Shell
|
agpl-3.0
| 12,237
|
#!/bin/bash
# Fooocus 安装功能
# 使用 FOOOCUS_DOWNLOAD_MODEL_LIST 全局变量读取要下载的模型
install_fooocus() {
local cmd_sum
local cmd_point
local i
if [ -f "${START_PATH}/term-sd/task/fooocus_install.sh" ]; then # 检测到有未完成的安装任务时直接执行安装任务
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/fooocus_install.sh" | wc -l) + 1 )) # 统计命令行数
term_sd_print_line "Fooocus 安装"
for (( cmd_point = 1; cmd_point <= cmd_sum; cmd_point++ )); do
term_sd_echo "Fooocus 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/fooocus_install.sh" "${cmd_point}"
if [[ ! "$?" == 0 ]]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 安装结果" \
--ok-label "确认" \
--msgbox "Fooocus 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "Fooocus 安装结束"
rm -f "${START_PATH}/term-sd/task/fooocus_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 安装结果" \
--ok-label "确认" \
--msgbox "Fooocus 安装结束, 选择确定进入管理界面" \
$(get_dialog_size)
fooocus_manager # 进入管理界面
else # 生成安装任务并执行安装任务
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
fooocus_download_model_select # 模型选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否安装 Fooocus ?"; then
term_sd_print_line "Fooocus 安装"
term_sd_echo "生成安装任务中"
term_sd_set_install_env_value >> "${START_PATH}/term-sd/task/fooocus_install.sh" # 环境变量
cat "${START_PATH}/term-sd/install/fooocus/fooocus_core.sh" >> "${START_PATH}/term-sd/task/fooocus_install.sh" # 核心组件
# 模型下载
if [[ ! -z "${FOOOCUS_DOWNLOAD_MODEL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"下载模型中\"" >> "${START_PATH}/term-sd/task/fooocus_install.sh"
if is_use_modelscope_src; then
# 读取模型
for i in ${FOOOCUS_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/fooocus/fooocus_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/fooocus_install.sh" # 插件所需的模型
done
else
# 恢复代理
echo "__term_sd_task_sys term_sd_tmp_enable_proxy" >> "${START_PATH}/term-sd/task/fooocus_install.sh"
for i in ${FOOOCUS_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/fooocus/fooocus_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/fooocus_install.sh" # 插件所需的模型
done
fi
fi
unset FOOOCUS_DOWNLOAD_MODEL_LIST
term_sd_echo "任务队列生成完成"
term_sd_echo "开始安装 Fooocus"
# 执行安装命令
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/fooocus_install.sh" | wc -l) + 1 )) # 统计命令行数
for (( cmd_point = 1; cmd_point <= cmd_sum; cmd_point++ )); do
term_sd_echo "Fooocus 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/fooocus_install.sh" "${cmd_point}"
if [[ ! $? = 0 ]]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 安装结果" \
--ok-label "确认" \
--msgbox "Fooocus 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "Fooocus 安装结束"
rm -f "${START_PATH}/term-sd/task/fooocus_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "Fooocus 管理" \
--backtitle "Fooocus 安装结果" \
--ok-label "确认" \
--msgbox "Fooocus 安装结束, 选择确定进入管理界面" \
$(get_dialog_size)
fooocus_manager # 进入管理界面
else
unset FOOOCUS_DOWNLOAD_MODEL_LIST
clean_install_config # 清理安装参数
fi
fi
}
# 模型选择
# 将选择的模型保存在 FOOOCUS_DOWNLOAD_MODEL_LIST 变量中
fooocus_download_model_select() {
local dialog_list_file
term_sd_echo "生成模型选择列表中"
if is_use_modelscope_src; then
dialog_list_file="dialog_fooocus_ms_model.sh"
else
dialog_list_file="dialog_fooocus_hf_model.sh"
fi
# 模型选择
FOOOCUS_DOWNLOAD_MODEL_LIST=$(dialog --erase-on-exit --notags \
--title "Fooocus 安装" \
--backtitle "Fooocus 模型下载选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要下载的 Fooocus 模型\n注:\n1、模型后面括号内数字为模型的大小\n2、需要根据自己的需求勾选需要下载的模型" \
$(get_dialog_size_menu) \
"_null_" "=====基础模型选择=====" ON \
$(cat "${START_PATH}/term-sd/install/fooocus/${dialog_list_file}") \
3>&1 1>&2 2>&3)
}
# Fooocus 预设文件
# 在启动 Fooocus 时 将加载该预设文件并应用
# 预设存放于 <Fooocus Path>/presets 中
set_fooocus_preset() {
term_sd_echo "写入 Fooocus 风格预设文件中"
cp -f "${START_PATH}/term-sd/install/fooocus/preset_term_sd.json" "${FOOOCUS_ROOT_PATH}"/presets/term_sd.json
}
# Fooocus 翻译文件
# 翻译文件存放于 <Fooocus Path>/language 中
set_fooocus_lang_config() {
term_sd_echo "写入 Fooocus 翻译文件中"
cp -f "${START_PATH}/term-sd/install/fooocus/lang_config_zh.json" "${FOOOCUS_ROOT_PATH}"/language/zh.json
}
|
2301_81996401/term-sd
|
modules/install_fooocus.sh
|
Shell
|
agpl-3.0
| 7,888
|
#!/bin/bash
# InvokeAI 安装功能
# 使用 INVOKEAI_INSTALL_CUSTOM_NODE_LIST 读取要安装的自定义节点
# 使用 INVOKEAI_DOWNLOAD_MODEL_LIST 读取要下载的模型
install_invokeai() {
local cmd_sum
local cmd_point
local i
if [ -f "${START_PATH}/term-sd/task/invokeai_install.sh" ]; then # 检测到有未完成的安装任务时直接执行安装任务
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/invokeai_install.sh" | wc -l) + 1 )) # 统计命令行数
term_sd_print_line "InvokeAI 安装"
for (( cmd_point=1; cmd_point <= cmd_sum; cmd_point++ )); do
term_sd_echo "InvokeAI 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/invokeai_install.sh" "${cmd_point}"
if [ ! $? = 0 ]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 安装结果" \
--ok-label "确认" \
--msgbox "InvokeAI 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "InvokeAI 安装结束"
rm -f "${START_PATH}/term-sd/task/invokeai_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 安装结果" \
--ok-label "确认" \
--msgbox "InvokeAI 安装结束, 选择确定进入管理界面" \
$(get_dialog_size)
invokeai_manager # 进入管理界面
else # 生成安装任务并执行安装任务
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_type_select # PyTorch 版本选择
invokeai_custom_node_install_select # 自定义节点选择
invokeai_download_model_select # 模型选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否安装 InvokeAI ?"; then
term_sd_print_line "InvokeAI 安装"
term_sd_echo "生成安装任务中"
term_sd_set_install_env_value >> "${START_PATH}/term-sd/task/invokeai_install.sh" # 环境变量
cat "${START_PATH}/term-sd/install/invokeai/invokeai_core.sh" >> "${START_PATH}/term-sd/task/invokeai_install.sh" # 核心组件
# 启用代理
echo "__term_sd_task_sys term_sd_tmp_enable_proxy" >> "${START_PATH}/term-sd/task/invokeai_install.sh"
# 读取安装自定义节点命令
if [[ ! -z "${INVOKEAI_INSTALL_CUSTOM_NODE_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"安装自定义节点中\"" >> "${START_PATH}/term-sd/task/invokeai_install.sh"
# 读取安装自定义节点命令列表
for i in ${INVOKEAI_INSTALL_CUSTOM_NODE_LIST}; do
cat "${START_PATH}/term-sd/install/invokeai/invokeai_custom_node.sh" | grep -w ${i} | awk '{sub(" ON "," ") ; sub(" OFF "," ")}1' >> "${START_PATH}/term-sd/task/invokeai_install.sh" # 自定义节点
done
fi
# 取消代理
echo "__term_sd_task_sys term_sd_tmp_disable_proxy" >> "${START_PATH}/term-sd/task/invokeai_install.sh"
# 模型下载
if [[ ! -z "${INVOKEAI_DOWNLOAD_MODEL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"下载模型中\"" >> "${START_PATH}/term-sd/task/invokeai_install.sh"
if is_use_modelscope_src; then
# 读取模型
for i in ${INVOKEAI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/invokeai/invokeai_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/invokeai_install.sh" # 自定义节点所需的模型
done
# 读取自定义节点的模型
for i in ${INVOKEAI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/invokeai/invokeai_custom_node_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/invokeai_install.sh" # 自定义节点所需的模型
done
else
# 恢复代理
echo "__term_sd_task_sys term_sd_tmp_enable_proxy" >> "${START_PATH}/term-sd/task/invokeai_install.sh"
# 读取模型
for i in ${INVOKEAI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/invokeai/invokeai_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/invokeai_install.sh" # 自定义节点所需的模型
done
# 读取自定义节点的模型
for i in ${INVOKEAI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/invokeai/invokeai_custom_node_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/invokeai_install.sh" # 自定义节点所需的模型
done
fi
fi
unset INVOKEAI_DOWNLOAD_MODEL_LIST
unset INVOKEAI_INSTALL_CUSTOM_NODE_LIST
term_sd_echo "任务队列生成完成"
term_sd_echo "开始安装 InvokeAI"
# 执行命令
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/invokeai_install.sh" | wc -l) + 1 )) # 统计命令行数
for ((cmd_point=1; cmd_point <= cmd_sum; cmd_point++)); do
term_sd_echo "InvokeAI 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/invokeai_install.sh" "${cmd_point}"
if [[ ! "$?" == 0 ]]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 安装结果" \
--ok-label "确认" \
--msgbox "InvokeAI 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "InvokeAI 安装结束"
rm -f "${START_PATH}/term-sd/task/invokeai_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 安装结果" \
--ok-label "确认" \
--msgbox "InvokeAI 安装结束, 选择确定进入管理界面" \
$(get_dialog_size)
invokeai_manager # 进入管理界面
else
unset INVOKEAI_DOWNLOAD_MODEL_LIST
unset INVOKEAI_INSTALL_CUSTOM_NODE_LIST
clean_install_config # 清理安装参数
fi
fi
}
# 自定义节点选择
# 将选择的自定义节点保存在 INVOKEAI_INSTALL_CUSTOM_NODE_LIST 全局变量中
invokeai_custom_node_install_select() {
INVOKEAI_INSTALL_CUSTOM_NODE_LIST=$(dialog --erase-on-exit --notags \
--title "InvokeAI 安装" \
--backtitle "InvokeAI 自定义节点安装选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要安装的 InvokeAI 自定义节点" \
$(get_dialog_size_menu) \
$(cat "${START_PATH}/term-sd/install/invokeai/dialog_invokeai_custom_node.sh") \
3>&1 1>&2 2>&3)
}
# 模型选择
# 将选择的模型保存在 INVOKEAI_DOWNLOAD_MODEL_LIST 全局变量中
invokeai_download_model_select() {
local dialog_list_file
local model_list
local invokeai_model_list_file
local i
term_sd_echo "生成模型选择列表中"
if is_use_modelscope_src; then
dialog_list_file="dialog_invokeai_ms_model.sh"
invokeai_model_list_file="invokeai_custom_node_ms_model.sh"
else
dialog_list_file="dialog_invokeai_hf_model.sh"
invokeai_model_list_file="invokeai_custom_node_hf_model.sh"
fi
# 查找自定义节点对应模型的编号
for i in ${INVOKEAI_INSTALL_CUSTOM_NODE_LIST}; do
model_list="${model_list} $(cat "${START_PATH}"/term-sd/install/invokeai/${invokeai_model_list_file} | grep -w ${i} | awk 'NR==1{if ($NF!="") {print $1 " " $(NF-1) " " $NF} }')"
done
# 模型选择
INVOKEAI_DOWNLOAD_MODEL_LIST=$(dialog --erase-on-exit --notags \
--title "InvokeAI 安装" \
--backtitle "InvokeAI 模型下载选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要下载的 InvokeAI 模型\n注:\n1、模型后面括号内数字为模型的大小, 未有括号标注的模型大小均小于 0.1m\n2、不建议使用 Term-SD 下载 InvokeAI 的模型, 建议使用 InvokeAI 自带的模型管理器下载模型" \
$(get_dialog_size_menu) \
"_null_" "=====基础模型选择=====" ON \
$(cat "${START_PATH}/term-sd/install/invokeai/${dialog_list_file}") \
"_null_" "=====自定义节点模型选择=====" ON \
${model_list} \
3>&1 1>&2 2>&3)
}
# 安装 PyPatchMatch (仅限 Windows 系统)
install_pypatchmatch_for_windows() {
local pypatchmatch_path=$(term_sd_python "${START_PATH}/term-sd/python_modules/get_pypatchmatch_path.py")
if is_windows_platform && [[ ! "${pypatchmatch_path}" == "None" ]]; then
term_sd_echo "下载 PyPatchMatch 中"
if is_use_modelscope_src; then
get_modelscope_model licyks/invokeai-core-model/master/pypatchmatch/libpatchmatch_windows_amd64.dll "${pypatchmatch_path}" libpatchmatch_windows_amd64.dll
get_modelscope_model licyks/invokeai-core-model/master/pypatchmatch/opencv_world460.dll "${pypatchmatch_path}" opencv_world460.dll
else
aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/pypatchmatch/libpatchmatch_windows_amd64.dll "${pypatchmatch_path}" libpatchmatch_windows_amd64.dll
aria2_download https://huggingface.co/licyk/invokeai-core-model/resolve/main/pypatchmatch/opencv_world460.dll "${pypatchmatch_path}" opencv_world460.dll
fi
fi
}
|
2301_81996401/term-sd
|
modules/install_invokeai.sh
|
Shell
|
agpl-3.0
| 11,588
|
#!/bin/bash
# kohya_ss 安装功能
# 使用 KOHYA_SS_DOWNLOAD_MODEL_LIST 全局变量读取要下载的模型
install_kohya_ss() {
local cmd_sum
local cmd_point
local i
if [ -f "${START_PATH}/term-sd/task/kohya_ss_install.sh" ]; then # 检测到有未完成的安装任务时直接执行安装任务
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/kohya_ss_install.sh" | wc -l) + 1 )) # 统计命令行数
term_sd_print_line "kohya_ss 安装"
for (( cmd_point = 1; cmd_point <= cmd_sum; cmd_point++ )); do
term_sd_echo "kohya_ss 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/kohya_ss_install.sh" "${cmd_point}"
if [[ ! "$?" == 0 ]]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 安装结果" \
--ok-label "确认" \
--msgbox "kohya_ss 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "kohya_ss 安装结束"
rm -f "${START_PATH}/term-sd/task/kohya_ss_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 安装结果" \
--ok-label "确认" \
--msgbox "kohya_ss 安装结束, 选择确定进入管理界面" \
$(get_dialog_size)
kohya_ss_manager # 进入管理界面
else # 生成安装任务并执行安装任务
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
kohya_ss_download_model_select # 模型选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否安装 kohya_ss ?"; then
term_sd_print_line "kohya_ss 安装"
term_sd_echo "生成安装任务中"
term_sd_set_install_env_value >> "${START_PATH}/term-sd/task/kohya_ss_install.sh" # 环境变量
cat "${START_PATH}/term-sd/install/kohya_ss/kohya_ss_core.sh" >> "${START_PATH}/term-sd/task/kohya_ss_install.sh" # 核心组件
# 模型下载
if [[ ! -z "${KOHYA_SS_DOWNLOAD_MODEL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"下载模型中\"" >> "${START_PATH}/term-sd/task/kohya_ss_install.sh"
if is_use_modelscope_src; then
# 读取模型
for i in ${KOHYA_SS_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/kohya_ss/kohya_ss_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/kohya_ss_install.sh" # 插件所需的模型
done
else
# 恢复代理
echo "__term_sd_task_sys term_sd_tmp_enable_proxy" >> "${START_PATH}/term-sd/task/kohya_ss_install.sh"
for i in ${KOHYA_SS_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/kohya_ss/kohya_ss_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/kohya_ss_install.sh" # 插件所需的模型
done
fi
fi
unset KOHYA_SS_DOWNLOAD_MODEL_LIST
term_sd_echo "任务队列生成完成"
term_sd_echo "开始安装 kohya_ss"
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/kohya_ss_install.sh" | wc -l) + 1 )) # 统计命令行数
for ((cmd_point=1; cmd_point <= cmd_sum; cmd_point++)); do
term_sd_echo "kohya_ss 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/kohya_ss_install.sh" "${cmd_point}"
if [[ ! "$?" == 0 ]]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 安装结果" \
--ok-label "确认" \
--msgbox "kohya_ss 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "kohya_ss 安装结束"
rm -f "${START_PATH}/term-sd/task/kohya_ss_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 安装结果" \
--ok-label "确认" \
--msgbox "kohya_ss 安装结束, 选择确定进入管理界面" \
$(get_dialog_size)
kohya_ss_manager # 进入管理界面
else
unset KOHYA_SS_DOWNLOAD_MODEL_LIST
clean_install_config # 清理安装参数
fi
fi
}
# 模型选择
# 将选择的模型保存在 KOHYA_SS_DOWNLOAD_MODEL_LIST 全局变量中
kohya_ss_download_model_select() {
local dialog_list_file
term_sd_echo "生成模型选择列表中"
if is_use_modelscope_src; then
dialog_list_file="dialog_kohya_ss_ms_model.sh"
else
dialog_list_file="dialog_kohya_ss_hf_model.sh"
fi
# 模型选择
KOHYA_SS_DOWNLOAD_MODEL_LIST=$(dialog --erase-on-exit --notags \
--title "kohya_ss 安装" \
--backtitle "kohya_ss 模型下载选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要下载的 kohya_ss 模型\n注:\n1、模型后面括号内数字为模型的大小\n2、需要根据自己的需求勾选需要下载的模型" \
$(get_dialog_size_menu) \
"_null_" "=====基础模型选择=====" ON \
$(cat "${START_PATH}/term-sd/install/kohya_ss/${dialog_list_file}") \
3>&1 1>&2 2>&3)
}
|
2301_81996401/term-sd
|
modules/install_kohya_ss.sh
|
Shell
|
agpl-3.0
| 7,331
|
#!/bin/bash
# lora-scripts 安装功能
# 使用 LORA_SCRIPTS_DOWNLOAD_MODEL_LIST 全局变量读取需要安装的模型
install_lora_scripts() {
local cmd_sum
local cmd_point
local i
if [[ -f "${START_PATH}/term-sd/task/lora_scripts_install.sh" ]]; then # 检测到有未完成的安装任务时直接执行安装任务
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/lora_scripts_install.sh" | wc -l) + 1 )) # 统计命令行数
term_sd_print_line "lora-scripts 安装"
for (( cmd_point=1; cmd_point <= cmd_sum; cmd_point++ )); do
term_sd_echo "lora-script 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/lora_scripts_install.sh" "${cmd_point}"
if [[ ! "$?" == 0 ]]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 安装结果" \
--ok-label "确认" \
--msgbox "lora-scripts 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "lora-scripts 安装结束"
rm -f "${START_PATH}/term-sd/task/lora_scripts_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 安装结果" \
--ok-label "确认" \
--msgbox "lora-scripts 安装结束, 选择确定进入管理界面" \
$(get_dialog_size)
lora_scripts_manager # 进入管理界面
else # 生成安装任务并执行安装任务
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
lora_scripts_download_model_select # 模型选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否安装 lora-scripts ?"; then
term_sd_print_line "lora-scripts 安装"
term_sd_echo "生成安装任务中"
term_sd_set_install_env_value >> "${START_PATH}/term-sd/task/lora_scripts_install.sh" # 环境变量
cat "${START_PATH}/term-sd/install/lora_scripts/lora_scripts_core.sh" >> "${START_PATH}/term-sd/task/lora_scripts_install.sh" # 核心组件
# 模型下载
if [[ ! -z "${LORA_SCRIPTS_DOWNLOAD_MODEL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"下载模型中\"" >> "${START_PATH}/term-sd/task/lora_scripts_install.sh"
if is_use_modelscope_src; then
# 读取模型
for i in ${LORA_SCRIPTS_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/lora_scripts/lora_scripts_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/lora_scripts_install.sh" # 插件所需的模型
done
else
# 恢复代理
echo "__term_sd_task_sys term_sd_tmp_enable_proxy" >> "${START_PATH}/term-sd/task/lora_scripts_install.sh"
for i in ${LORA_SCRIPTS_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/lora_scripts/lora_scripts_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/lora_scripts_install.sh" # 插件所需的模型
done
fi
fi
unset LORA_SCRIPTS_DOWNLOAD_MODEL_LIST
term_sd_echo "任务队列生成完成"
term_sd_echo "开始安装 lora-scripts"
# 执行命令
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/lora_scripts_install.sh" | wc -l) + 1 )) # 统计命令行数
for (( cmd_point=1; cmd_point <= cmd_sum; cmd_point++ )); do
term_sd_echo "lora-scripts 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/lora_scripts_install.sh" "${cmd_point}"
if [[ ! "$?" == 0 ]]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 安装结果" \
--ok-label "确认" \
--msgbox "lora-scripts 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "lora-scripts 安装结束"
rm -f "${START_PATH}/term-sd/task/lora_scripts_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 安装结果" \
--ok-label "确认" \
--msgbox "lora-scripts 安装结束, 选择确定进入管理界面" \
$(get_dialog_size)
lora_scripts_manager # 进入管理界面
else
unset LORA_SCRIPTS_DOWNLOAD_MODEL_LIST
clean_install_config # 清理安装参数
fi
fi
}
# 模型选择
# 将选择的模型保存在 LORA_SCRIPTS_DOWNLOAD_MODEL_LIST 全局变量中
lora_scripts_download_model_select() {
local dialog_list_file
term_sd_echo "生成模型选择列表中"
if is_use_modelscope_src; then
dialog_list_file="dialog_lora_scripts_ms_model.sh"
else
dialog_list_file="dialog_lora_scripts_hf_model.sh"
fi
# 模型选择
LORA_SCRIPTS_DOWNLOAD_MODEL_LIST=$(dialog --erase-on-exit --notags \
--title "lora-scripts 安装" \
--backtitle "lora-scripts 模型下载选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要下载的 lora-scripts 模型\n注:\n1、模型后面括号内数字为模型的大小\n2、需要根据自己的需求勾选需要下载的模型" \
$(get_dialog_size_menu) \
"_null_" "=====基础模型选择=====" ON \
$(cat "${START_PATH}/term-sd/install/lora_scripts/${dialog_list_file}") \
3>&1 1>&2 2>&3)
}
|
2301_81996401/term-sd
|
modules/install_lora_scripts.sh
|
Shell
|
agpl-3.0
| 7,598
|
#!/bin/bash
# 安装前镜像选择
# 该函数需要使用 TERM_SD_PIP_INDEX_URL_ARG, TERM_SD_PIP_EXTRA_INDEX_URL_ARG, TERM_SD_PIP_FIND_LINKS_ARG
# TERM_SD_UV_INDEX_URL_ARG, TERM_SD_UV_EXTRA_INDEX_URL_ARG, TERM_SD_UV_FIND_LINKS_ARG 变量
# 用于设置其他参数
# 选择后将设置以下变量:
# PIP_INDEX_MIRROR, PIP_EXTRA_INDEX_MIRROR, PIP_FIND_LINKS_MIRROR
# UV_INDEX_MIRROR, UV_EXTRA_INDEX_MIRROR, UV_FIND_LINKS_MIRROR
# USE_MODELSCOPE_MODEL_SRC, GITHUB_MIRROR, GITHUB_MIRROR_NAME
# USE_PIP_MIRROR, TERM_SD_ENABLE_ONLY_PROXY
download_mirror_select() {
local dialog_arg
local auto_select_github_mirror=0
local use_env_pip_mirror=0
local use_global_github_mirror=0
local use_global_pip_mirror=0
local i
PIP_INDEX_MIRROR="--index-url https://pypi.python.org/simple"
UV_INDEX_MIRROR="--default-index https://pypi.python.org/simple"
unset PIP_EXTRA_INDEX_MIRROR
unset UV_EXTRA_INDEX_MIRROR
PIP_FIND_LINKS_MIRROR="--find-links https://download.pytorch.org/whl/torch_stable.html"
UV_FIND_LINKS_MIRROR="--find-links https://download.pytorch.org/whl/torch_stable.html"
USE_PIP_MIRROR=0
TERM_SD_ENABLE_ONLY_PROXY=0
USE_MODELSCOPE_MODEL_SRC=0
GITHUB_MIRROR="https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="官方源 (github.com)"
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Term-SD" \
--backtitle "安装镜像选项" \
--title "Term-SD" \
--ok-label "确认" --no-cancel \
--checklist "请选择镜像, 注:\n1. 当同时启用多个 Github 镜像源时, 优先选择最下面的 Github 镜像源; 勾选 \"Github 镜像源自动选择\" 时, 将覆盖手动设置的 Github 镜像源\n2. 启用全局镜像源后, 优先使用设置中的镜像源\n3. 如果需要保持安装全程使用代理, 需要将 \"Huggingface / Github 下载源独占代理\" 关闭\n4. 有些 Python 软件包的下载需要代理, 需要将 \"Huggingface / Github 下载源独占代理\" 关闭\n5. 通常情况下保持默认即可" \
$(get_dialog_size_menu) \
"1" "启用 PyPI 镜像源 (使用 PyPI 国内镜像源下载 Python 软件包)" OFF \
"2" "使用全局 PyPI 镜像源配置 (使用 Term-SD 设置中配置的 PyPI 镜像源)" ON \
"3" "使用 ModelScope 模型下载源 (将 HuggingFace 下载源改为 ModelScope 下载源)" ON \
"4" "Huggingface / Github 下载源独占代理 (仅在下载 Huggingface / Github 上的文件时启用代理)" OFF \
"5" "使用全局 Github 镜像源配置 (当设置了全局 Github 镜像源时禁用 Github 镜像自动选择)" ON \
"6" "Github 镜像源自动选择 (测试可用的镜像源并选择自动选择)" ON \
"7" "启用 Github 镜像源 1 (使用 ghfast.top 镜像站下载 Github 上的源码)" OFF \
"8" "启用 Github 镜像源 2 (使用 mirror.ghproxy.com 镜像站下载 Github 上的源码)" OFF \
"9" "启用 Github 镜像源 3 (使用 gitclone.com 镜像站下载 Github 上的源码)" OFF \
"10" "启用 Github 镜像源 4 (使用 gh-proxy.com 镜像站下载 Github 上的源码)" OFF \
"11" "启用 Github 镜像源 5 (使用 ghps.cc 镜像站下载 Github 上的源码)" OFF \
"12" "启用 Github 镜像源 6 (使用 gh.idayer.com 镜像站下载 Github 上的源码)" OFF \
"13" "启用 Github 镜像源 7 (使用 ghproxy.net 镜像站下载 Github 上的源码)" OFF \
"14" "启用 Github 镜像源 8 (使用 gh.api.99988866.xyz 镜像站下载 Github 上的源码)" OFF \
"15" "启用 Github 镜像源 9 (使用 ghproxy.1888866.xyz 镜像站下载 Github 上的源码)" OFF \
"16" "启用 Github 镜像源 10 (使用 slink.ltd 镜像站下载 Github 上的源码)" OFF \
"17" "启用 Github 镜像源 11 (使用 github.boki.moe 镜像站下载 Github 上的源码)" OFF \
"18" "启用 Github 镜像源 12 (使用 github.moeyy.xyz 镜像站下载 Github 上的源码)" OFF \
"19" "启用 Github 镜像源 13 (使用 gh-proxy.net 镜像站下载 Github 上的源码)" OFF \
"20" "启用 Github 镜像源 14 (使用 gh-proxy.ygxz.in 镜像站下载 Github 上的源码)" OFF \
"21" "启用 Github 镜像源 15 (使用 wget.la 镜像站下载 Github 上的源码)" OFF \
"22" "启用 Github 镜像源 16 (使用 kkgithub.com 镜像站下载 Github 上的源码)" OFF \
3>&1 1>&2 2>&3)
for i in ${dialog_arg}; do
case "${i}" in
1)
USE_PIP_MIRROR=1
PIP_INDEX_MIRROR=$TERM_SD_PIP_INDEX_URL_ARG
PIP_EXTRA_INDEX_MIRROR=$TERM_SD_PIP_EXTRA_INDEX_URL_ARG
PIP_FIND_LINKS_MIRROR=$TERM_SD_PIP_FIND_LINKS_ARG
UV_INDEX_MIRROR=$TERM_SD_UV_INDEX_URL_ARG
UV_EXTRA_INDEX_MIRROR=$TERM_SD_UV_EXTRA_INDEX_URL_ARG
UV_FIND_LINKS_MIRROR=$TERM_SD_UV_FIND_LINKS_ARG
;;
2)
use_global_pip_mirror=1
;;
3)
USE_MODELSCOPE_MODEL_SRC=1
;;
4)
TERM_SD_ENABLE_ONLY_PROXY=1
;;
5)
if [[ -f "${START_PATH}/term-sd/config/set-global-github-mirror.conf" ]]; then
use_global_github_mirror=1
fi
;;
6)
auto_select_github_mirror=1
;;
7)
GITHUB_MIRROR="https://ghfast.top/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 1 (ghfast.top)"
;;
8)
GITHUB_MIRROR="https://mirror.ghproxy.com/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 2 (mirror.ghproxy.com)"
;;
9)
GITHUB_MIRROR="https://gitclone.com/github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 3 (gitclone.com)"
;;
10)
GITHUB_MIRROR="https://gh-proxy.com/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 4 (gh-proxy.com)"
;;
11)
GITHUB_MIRROR="https://ghps.cc/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 5 (ghps.cc)"
;;
12)
GITHUB_MIRROR="https://gh.idayer.com/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 6 (gh.idayer.com)"
;;
13)
GITHUB_MIRROR="https://ghproxy.net/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 7 (ghproxy.net)"
;;
14)
GITHUB_MIRROR="https://gh.api.99988866.xyz/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 8 (gh.api.99988866.xyz)"
;;
15)
GITHUB_MIRROR="https://ghproxy.1888866.xyz/github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 9 (ghproxy.1888866.xyz)"
;;
16)
GITHUB_MIRROR="https://slink.ltd/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 10 (slink.ltd)"
;;
17)
GITHUB_MIRROR="https://github.boki.moe/github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 11 (github.boki.moe)"
;;
18)
GITHUB_MIRROR="https://github.moeyy.xyz/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 12 (github.moeyy.xyz)"
;;
19)
GITHUB_MIRROR="https://gh-proxy.net/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 13 (gh-proxy.net)"
;;
20)
GITHUB_MIRROR="https://gh-proxy.ygxz.in/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 14 (gh-proxy.ygxz.in)"
;;
21)
GITHUB_MIRROR="https://wget.la/https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 15 (wget.la)"
;;
22)
GITHUB_MIRROR="https://kkgithub.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="镜像源 16 (kkgithub.com)"
;;
esac
done
if [[ "${use_global_pip_mirror}" == 1 ]]; then
if [[ ! -z "${PIP_INDEX_URL}" ]]; then # 确保存在镜像源
use_env_pip_mirror=1
# 已弃用
# elif [ ! -z "$(term_sd_pip config list | grep -E "global.index-url")" ] && [ ! -z "$(term_sd_pip config list | grep -E "global.find-links")" ]; then
# use_env_pip_mirror=1
else
use_env_pip_mirror=0
fi
if [[ "${use_env_pip_mirror}" == 1 ]]; then
term_sd_echo "使用全局 PyPI 镜像源配置"
unset PIP_INDEX_MIRROR
unset PIP_EXTRA_INDEX_MIRROR
unset PIP_FIND_LINKS_MIRROR
unset UV_INDEX_MIRROR
unset UV_EXTRA_INDEX_MIRROR
unset UV_FIND_LINKS_MIRROR
if [[ ! "${PIP_INDEX_URL}" == "https://pypi.python.org/simple" ]]; then
term_sd_echo "使用 PyPI 镜像源"
USE_PIP_MIRROR=1
elif [[ "${PIP_INDEX_URL}" == "https://pypi.python.org/simple" ]]; then
term_sd_echo "使用 PyPI 官方源"
USE_PIP_MIRROR=0
# 已弃用
# elif term_sd_pip config list | grep -E "global.index-url" | grep "https://pypi.python.org/simple" &> /dev/null; then
# term_sd_echo "使用 PyPI 官方源"
# USE_PIP_MIRROR=0
else
term_sd_echo "使用 PyPI 镜像源"
USE_PIP_MIRROR=1
fi
else
term_sd_echo "未设置任何镜像源，默认使用 PyPI 国内镜像源"
USE_PIP_MIRROR=1
PIP_INDEX_MIRROR=$TERM_SD_PIP_INDEX_URL_ARG
PIP_EXTRA_INDEX_MIRROR=$TERM_SD_PIP_EXTRA_INDEX_URL_ARG
PIP_FIND_LINKS_MIRROR=$TERM_SD_PIP_FIND_LINKS_ARG
UV_INDEX_MIRROR=$TERM_SD_UV_INDEX_URL_ARG
UV_EXTRA_INDEX_MIRROR=$TERM_SD_UV_EXTRA_INDEX_URL_ARG
UV_FIND_LINKS_MIRROR=$TERM_SD_UV_FIND_LINKS_ARG
fi
fi
if [[ "${auto_select_github_mirror}" == 1 ]]; then # 测试可用的镜像源
if [[ "${use_global_github_mirror}" == 1 ]]; then
term_sd_echo "使用全局 Github 镜像源"
GITHUB_MIRROR="https://github.com/term_sd_git_user/term_sd_git_repo"
GITHUB_MIRROR_NAME="全局镜像源 ($(cat "${START_PATH}/term-sd/config/set-global-github-mirror.conf" | awk '{sub("/https://github.com","") sub("/github.com","")}1'))"
else
term_sd_echo "测试可用的 Github 镜像源中"
github_mirror=$(github_mirror_test)
GITHUB_MIRROR_NAME="镜像源 ($(echo ${github_mirror} | awk '{sub("https://","")}1' | awk -F '/' '{print$NR}'))"
term_sd_echo "镜像源测试结束, 镜像源选择: ${GITHUB_MIRROR_NAME}"
fi
fi
}
# PyTorch 安装版本选择
# 选择后设置 INSTALL_PYTORCH_VERSION 全局变量保存 PyTorch 版本信息
# 设置 INSTALL_XFORMERS_VERSION 全局变量保存 xFormers 版本信息
# PYTORCH_TYPE 保存使用的 PyTorch 镜像源种类, 如果为空则使用默认的镜像源
pytorch_version_select() {
local dialog_arg
unset INSTALL_PYTORCH_VERSION
unset INSTALL_XFORMERS_VERSION
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Term-SD" \
--backtitle "PyTorch 安装版本选项" \
--ok-label "确认" --no-cancel \
--menu "请选择要安装的 PyTorch 版本, 注:\n1. Nvidia 显卡选择 CUDA 的版本\n2. AMD 显卡选择 ROCm(Linux) / DirectML(Windows) 版本\n3. Intel 显卡选择 IPEX Arc(独显) / Core Ultra(核显) / Intel XPU\n4. Apple M 系列芯片选择无特殊标识版本\n5. 使用 CPU 运算选择 CPU 版本\n6. 标记为 Linux 的版本只能在 Linux 上安装\n当前 PyTorch 版本: $(get_pytorch_version)\n当前 xFormers 版本: $(get_xformers_version)" \
$(get_dialog_size_menu) \
"118" "> Torch 2.8.0 (CUDA 12.6) + xFormers 0.0.32.post2" \
"117" "> Torch 2.8.0 (CUDA 12.8) + xFormers 0.0.32.post2" \
"116" "> Torch 2.8.0 (CUDA 12.9) + xFormers 0.0.32.post2" \
"115" "> Torch 2.8.0 (Intel XPU)" \
"114" "> Torch 2.8.0 (ROCm 6.3)" \
"113" "> Torch 2.8.0 (ROCm 6.4) + xFormers 0.0.32.post2" \
"112" "> Torch 2.8.0 (CPU)" \
"111" "> Torch 2.8.0" \
"110" "> Torch 2.7.1 (CUDA 11.8) + xFormers 0.0.31.post1 (Linux)" \
"109" "> Torch 2.7.1 (CUDA 12.6) + xFormers 0.0.31.post1" \
"108" "> Torch 2.7.1 (CUDA 12.8) + xFormers 0.0.31.post1" \
"107" "> Torch 2.7.1 (Intel XPU)" \
"106" "> Torch 2.7.1 (ROCm 6.2.4) + xFormers 0.0.31.post1 (Linux)" \
"105" "> Torch 2.7.1 (ROCm 6.3) + xFormers 0.0.31.post1 (Linux)" \
"104" "> Torch 2.7.1 (CPU)" \
"103" "> Torch 2.7.1" \
"102" "> Torch 2.7.0 (CUDA 11.8) + xFormers 0.0.30 (Linux)" \
"101" "> Torch 2.7.0 (CUDA 12.6) + xFormers 0.0.30" \
"100" "> Torch 2.7.0 (CUDA 12.8) + xFormers 0.0.30" \
"99" "> Torch 2.7.0 (Intel XPU)" \
"98" "> Torch 2.7.0 (ROCm 6.2.4) + xFormers 0.0.30 (Linux)" \
"97" "> Torch 2.7.0 (ROCm 6.3) + xFormers 0.0.30 (Linux)" \
"96" "> Torch 2.7.0 (CPU)" \
"95" "> Torch 2.7.0" \
"94" "> Torch 2.6.0 (CUDA 11.8) + xFormers 0.0.29.post3 (Linux)" \
"93" "> Torch 2.6.0 (CUDA 12.4) + xFormers 0.0.29.post3" \
"92" "> Torch 2.6.0 (CUDA 12.6) + xFormers 0.0.29.post3" \
"91" "> Torch 2.6.0 (Intel XPU)" \
"90" "> Torch 2.6.0 (ROCm 6.1) + xFormers 0.0.29.post3 (Linux)" \
"89" "> Torch 2.6.0 (ROCm 6.2.4) + xFormers 0.0.29.post3 (Linux)" \
"88" "> Torch 2.6.0 (CPU)" \
"87" "> Torch 2.6.0" \
"86" "> Torch 2.5.1 (CUDA 11.8) + xFormers 0.0.28.post3 (Linux)" \
"85" "> Torch 2.5.1 (CUDA 12.1) + xFormers 0.0.28.post3 (Linux)" \
"84" "> Torch 2.5.1 (CUDA 12.4) + xFormers 0.0.28.post3" \
"83" "> Torch 2.5.1 (ROCm 6.1) + xFormers 0.0.28.post3 (Linux)" \
"82" "> Torch 2.5.1 (ROCm 6.2) (Linux)" \
"81" "> Torch 2.5.1 (CPU)" \
"80" "> Torch 2.5.1" \
"79" "> Torch 2.5.0 (CUDA 11.8) + xFormers 0.0.28.post2 (Linux)" \
"78" "> Torch 2.5.0 (CUDA 12.1) + xFormers 0.0.28.post2 (Linux)" \
"77" "> Torch 2.5.0 (CUDA 12.4) + xFormers 0.0.28.post2" \
"76" "> Torch 2.5.0 (ROCm 6.1) + xFormers 0.0.28.post2 (Linux)" \
"75" "> Torch 2.5.0 (ROCm 6.2) (Linux)" \
"74" "> Torch 2.5.0 (CPU)" \
"73" "> Torch 2.5.0" \
"72" "> Torch 2.4.1 (CUDA 11.8) + xFormers 0.0.28.post1 (Linux)" \
"71" "> Torch 2.4.1 (CUDA 12.1) + xFormers 0.0.28.post1 (Linux)" \
"70" "> Torch 2.4.1 (CUDA 12.4) + xFormers 0.0.28.post1" \
"69" "> Torch 2.4.1 (ROCm 6.1) + xFormers 0.0.28.post1 (Linux)" \
"68" "> Torch 2.4.1 (CPU)" \
"67" "> Torch 2.4.1" \
"66" "> Torch 2.4.0 (CUDA 11.8) + xFormers 0.0.27.post2" \
"65" "> Torch 2.4.0 (CUDA 12.1) + xFormers 0.0.27.post2" \
"64" "> Torch 2.4.0 (CUDA 12.4)" \
"63" "> Torch 2.4.0 (ROCm 6.0) (Linux)" \
"62" "> Torch 2.4.0 (CPU)" \
"61" "> Torch 2.4.0" \
"60" "> Torch 2.3.1 (CUDA 11.8) + xFormers 0.0.27" \
"59" "> Torch 2.3.1 (CUDA 12.1) + xFormers 0.0.27" \
"58" "> Torch 2.3.1 (ROCm 6.0) (Linux)" \
"57" "> Torch 2.3.1 (DirectML)" \
"56" "> Torch 2.3.1 (CPU)" \
"55" "> Torch 2.3.1" \
"54" "> Torch 2.3.0 (CUDA 11.8) + xFormers 0.0.26.post1" \
"53" "> Torch 2.3.0 (CUDA 12.1) + xFormers 0.0.26.post1" \
"52" "> Torch 2.3.0 (ROCm 6.0) (Linux)" \
"51" "> Torch 2.3.0 (CPU)" \
"50" "> Torch 2.3.0" \
"49" "> Torch 2.2.2 (CUDA 11.8) + xFormers 0.0.25.post1" \
"48" "> Torch 2.2.2 (CUDA 12.1) + xFormers 0.0.25.post1" \
"47" "> Torch 2.2.2 (ROCm 5.7) (Linux)" \
"46" "> Torch 2.2.2 (CPU)" \
"45" "> Torch 2.2.2" \
"44" "> Torch 2.2.1 (CUDA 11.8) + xFormers 0.0.25" \
"43" "> Torch 2.2.1 (CUDA 12.1) + xFormers 0.0.25" \
"42" "> Torch 2.2.1 (ROCm 5.7) (Linux)" \
"41" "> Torch 2.2.1 (DirectML)" \
"40" "> Torch 2.2.1 (CPU)" \
"39" "> Torch 2.2.1" \
"38" "> Torch 2.2.0 (CUDA 11.8) + xFormers 0.0.24" \
"37" "> Torch 2.2.0 (CUDA 12.1) + xFormers 0.0.24" \
"36" "> Torch 2.2.0 (ROCm 5.7) (Linux)" \
"35" "> Torch 2.2.0 (CPU)" \
"34" "> Torch 2.2.0" \
"33" "> Torch 2.1.2 (CUDA 11.8) + xFormers 0.0.23.post1" \
"32" "> Torch 2.1.2 (CUDA 12.1) + xFormers 0.0.23.post1" \
"31" "> Torch 2.1.2 (ROCm 5.6) (Linux)" \
"30" "> Torch 2.1.2 (CPU)" \
"29" "> Torch 2.1.2" \
"28" "> Torch 2.1.1 (CUDA 11.8) + xFormers 0.0.23" \
"27" "> Torch 2.1.1 (CUDA 12.1) + xFormers 0.0.23" \
"26" "> Torch 2.1.1 (ROCm 5.6) (Linux)" \
"25" "> Torch 2.1.1 (CPU)" \
"24" "> Torch 2.1.1" \
"23" "> Torch 2.1.0 (Intel Arc)" \
"22" "> Torch 2.1.0 (Intel Core Ultra)" \
"21" "> Torch 2.1.0 (ROCm 5.6) (Linux)" \
"20" "> Torch 2.1.0 (CPU)" \
"19" "> Torch 2.1.0" \
"18" "> Torch 2.0.1 (CUDA 11.8) + xFormers 0.0.22" \
"17" "> Torch 2.0.1 (ROCm 5.4.2) (Linux)" \
"16" "> Torch 2.0.1 (CPU)" \
"15" "> Torch 2.0.1" \
"14" "> Torch 2.0.0 (CUDA 11.8) + xFormers 0.0.18" \
"13" "> Torch 2.0.0 (Intel Arc)" \
"12" "> Torch 2.0.0 (DirectML)" \
"11" "> Torch 2.0.0 (CPU)" \
"10" "> Torch 2.0.0" \
"9" "> Torch 1.13.1 (CUDA 11.7) + xFormers 0.0.16" \
"8" "> Torch 1.13.1 (DirectML)" \
"7" "> Torch 1.13.1 (CPU)" \
"6" "> Torch 1.13.1" \
"5" "> Torch 1.12.1 (CUDA 11.3) + xFormers 0.0.14" \
"4" "> Torch 1.12.1 (CPU)" \
"3" "> Torch 1.12.1" \
"2" "> Torch + xFormers" \
"1" "> Torch" \
"0" "> 跳过安装 PyTorch" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
0)
unset INSTALL_PYTORCH_VERSION
unset INSTALL_XFORMERS_VERSION
;;
1)
INSTALL_PYTORCH_VERSION="torch torchvision torchaudio"
;;
2)
INSTALL_PYTORCH_VERSION="torch torchvision torchaudio"
INSTALL_XFORMERS_VERSION="xformers"
;;
3)
INSTALL_PYTORCH_VERSION="torch==1.12.1 torchvision==0.13.1 torchaudio==1.12.1"
;;
4)
INSTALL_PYTORCH_VERSION="torch==1.12.1+cpu torchvision==0.13.1+cpu torchaudio==1.12.1+cpu"
PYTORCH_TYPE="cpu"
;;
5)
INSTALL_PYTORCH_VERSION="torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==1.12.1+cu113"
INSTALL_XFORMERS_VERSION="xformers==0.0.14"
;;
6)
INSTALL_PYTORCH_VERSION="torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1"
;;
7)
INSTALL_PYTORCH_VERSION="torch==1.13.1+cpu torchvision==0.14.1+cpu torchaudio==0.13.1+cpu"
PYTORCH_TYPE="cpu"
;;
8)
INSTALL_PYTORCH_VERSION="torch==1.13.1 torchvision==0.14.1 torch-directml==0.1.13.1.dev230413"
;;
9)
INSTALL_PYTORCH_VERSION="torch==1.13.1+cu117 torchvision==0.14.1+cu117 torchaudio==0.13.1+cu117"
;;
10)
INSTALL_PYTORCH_VERSION="torch==2.0.0 torchvision==0.15.1 torchaudio==2.0.0"
;;
11)
INSTALL_PYTORCH_VERSION="torch==2.0.0+cpu torchvision==0.15.1+cpu torchaudio==2.0.0+cpu"
PYTORCH_TYPE="cpu"
;;
12)
INSTALL_PYTORCH_VERSION="torch==2.0.0 torchvision==0.15.1 torch-directml==0.2.0.dev230426"
;;
13)
INSTALL_PYTORCH_VERSION="torch(ipex_Arc) 2.0.0"
PYTORCH_TYPE="ipex_legacy_arc"
;;
14)
INSTALL_PYTORCH_VERSION="torch==2.0.0+cu118 torchvision==0.15.1+cu118 torchaudio==2.0.0+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.18"
;;
15)
INSTALL_PYTORCH_VERSION="torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.1"
;;
16)
INSTALL_PYTORCH_VERSION="torch==2.0.1+cpu torchvision==0.15.2+cpu torchaudio==2.0.1+cpu"
PYTORCH_TYPE="cpu"
;;
17)
INSTALL_PYTORCH_VERSION="torch==2.0.1+rocm5.4.2 torchvision==0.15.2+rocm5.4.2 torchaudio==2.0.1+rocm5.4.2"
;;
18)
INSTALL_PYTORCH_VERSION="torch==2.0.1+cu118 torchvision==0.15.2+cu118 torchaudio==2.0.1+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.22"
;;
19)
INSTALL_PYTORCH_VERSION="torch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0"
;;
20)
INSTALL_PYTORCH_VERSION="torch==2.1.0+cpu torchvision==0.16.0+cpu torchaudio==2.1.0+cpu"
PYTORCH_TYPE="cpu"
;;
21)
INSTALL_PYTORCH_VERSION="torch==2.1.0+rocm5.6 torchvision==0.16.0+rocm5.6 torchaudio==2.1.0+rocm5.6"
;;
22)
INSTALL_PYTORCH_VERSION="torch(ipex_Core_Ultra) 2.1.0"
PYTORCH_TYPE="ipex_legacy_core_ultra"
;;
23)
INSTALL_PYTORCH_VERSION="torch(ipex_Arc) 2.1.0"
PYTORCH_TYPE="ipex_legacy_arc"
;;
24)
INSTALL_PYTORCH_VERSION="torch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1"
;;
25)
INSTALL_PYTORCH_VERSION="torch==2.1.1+cpu torchvision==0.16.1+cpu torchaudio==2.1.1+cpu"
PYTORCH_TYPE="cpu"
;;
26)
INSTALL_PYTORCH_VERSION="torch==2.1.1+rocm5.6 torchvision==0.16.1+rocm5.6 torchaudio==2.1.1+rocm5.6"
;;
27)
INSTALL_PYTORCH_VERSION="torch==2.1.1+cu121 torchvision==0.16.1+cu121 torchaudio==2.1.1+cu121"
INSTALL_XFORMERS_VERSION="xformers==0.0.23"
;;
28)
INSTALL_PYTORCH_VERSION="torch==2.1.1+cu118 torchvision==0.16.1+cu118 torchaudio==2.1.1+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.23+cu118"
PYTORCH_TYPE="cu118"
;;
29)
INSTALL_PYTORCH_VERSION="torch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2"
;;
30)
INSTALL_PYTORCH_VERSION="torch==2.1.2+cpu torchvision==0.16.2+cpu torchaudio==2.1.2+cpu"
PYTORCH_TYPE="cpu"
;;
31)
INSTALL_PYTORCH_VERSION="torch==2.1.2+rocm5.6 torchvision==0.16.2+rocm5.6 torchaudio==2.1.2+rocm5.6"
;;
32)
INSTALL_PYTORCH_VERSION="torch==2.1.2+cu121 torchvision==0.16.2+cu121 torchaudio==2.1.2+cu121"
INSTALL_XFORMERS_VERSION="xformers==0.0.23.post1"
PYTORCH_TYPE="cu121"
;;
33)
INSTALL_PYTORCH_VERSION="torch==2.1.2+cu118 torchvision==0.16.2+cu118 torchaudio==2.1.2+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.23.post1+cu118"
PYTORCH_TYPE="cu118"
;;
34)
INSTALL_PYTORCH_VERSION="torch==2.2.0 torchvision==0.17.0 torchaudio==2.2.0"
;;
35)
INSTALL_PYTORCH_VERSION="torch==2.2.0+cpu torchvision==0.17.0+cpu torchaudio==2.2.0+cpu"
PYTORCH_TYPE="cpu"
;;
36)
INSTALL_PYTORCH_VERSION="torch==2.2.0+rocm5.7 torchvision==0.17.0+rocm5.7 torchaudio==2.2.0+rocm5.7"
;;
37)
INSTALL_PYTORCH_VERSION="torch==2.2.0+cu121 torchvision==0.17.0+cu121 torchaudio==2.2.0+cu121"
INSTALL_XFORMERS_VERSION="xformers==0.0.24"
PYTORCH_TYPE="cu121"
;;
38)
INSTALL_PYTORCH_VERSION="torch==2.2.0+cu118 torchvision==0.17.0+cu118 torchaudio==2.2.0+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.24+cu118"
PYTORCH_TYPE="cu118"
;;
39)
INSTALL_PYTORCH_VERSION="torch==2.2.1 torchvision==0.17.1 torchaudio==2.2.1"
;;
40)
INSTALL_PYTORCH_VERSION="torch==2.2.1+cpu torchvision==0.17.1+cpu torchaudio==2.2.1+cpu"
PYTORCH_TYPE="cpu"
;;
41)
INSTALL_PYTORCH_VERSION="torch==2.2.1 torchvision==0.17.1 torch-directml==0.2.1.dev240521"
;;
42)
INSTALL_PYTORCH_VERSION="torch==2.2.1+rocm5.7 torchvision==0.17.1+rocm5.7 torchaudio==2.2.1+rocm5.7"
;;
43)
INSTALL_PYTORCH_VERSION="torch==2.2.1+cu121 torchvision==0.17.1+cu121 torchaudio==2.2.1+cu121"
INSTALL_XFORMERS_VERSION="xformers==0.0.25"
PYTORCH_TYPE="cu121"
;;
44)
INSTALL_PYTORCH_VERSION="torch==2.2.1+cu118 torchvision==0.17.1+cu118 torchaudio==2.2.1+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.25+cu118"
PYTORCH_TYPE="cu118"
;;
45)
INSTALL_PYTORCH_VERSION="torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2"
;;
46)
INSTALL_PYTORCH_VERSION="torch==2.2.2+cpu torchvision==0.17.2+cpu torchaudio==2.2.2+cpu"
PYTORCH_TYPE="cpu"
;;
47)
INSTALL_PYTORCH_VERSION="torch==2.2.2+rocm5.7 torchvision==0.17.2+rocm5.7 torchaudio==2.2.2+rocm5.7"
;;
48)
INSTALL_PYTORCH_VERSION="torch==2.2.2+cu121 torchvision==0.17.2+cu121 torchaudio==2.2.2+cu121"
INSTALL_XFORMERS_VERSION="xformers==0.0.25.post1"
PYTORCH_TYPE="cu121"
;;
49)
INSTALL_PYTORCH_VERSION="torch==2.2.2+cu118 torchvision==0.17.2+cu118 torchaudio==2.2.2+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.25.post1+cu118"
PYTORCH_TYPE="cu118"
;;
50)
INSTALL_PYTORCH_VERSION="torch==2.3.0 torchvision==0.18.0 torchaudio==2.3.0"
;;
51)
INSTALL_PYTORCH_VERSION="torch==2.3.0+cpu torchvision==0.18.0+cpu torchaudio==2.3.0+cpu"
PYTORCH_TYPE="cpu"
;;
52)
INSTALL_PYTORCH_VERSION="torch==2.3.0+rocm6.0 torchvision==0.18.0+rocm6.0 torchaudio==2.3.0+rocm6.0"
;;
53)
INSTALL_PYTORCH_VERSION="torch==2.3.0+cu121 torchvision==0.18.0+cu121 torchaudio==2.3.0+cu121"
INSTALL_XFORMERS_VERSION="xformers==0.0.26.post1"
PYTORCH_TYPE="cu121"
;;
54)
INSTALL_PYTORCH_VERSION="torch==2.3.0+cu118 torchvision==0.18.0+cu118 torchaudio==2.3.0+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.26.post1+cu118"
PYTORCH_TYPE="cu118"
;;
55)
INSTALL_PYTORCH_VERSION="torch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1"
;;
56)
INSTALL_PYTORCH_VERSION="torch==2.3.1+cpu torchvision==0.18.1+cpu torchaudio==2.3.1+cpu"
PYTORCH_TYPE="cpu"
;;
57)
INSTALL_PYTORCH_VERSION="torch==2.3.1 torchvision==0.18.1 torch-directml==0.2.3.dev240715"
;;
58)
INSTALL_PYTORCH_VERSION="torch==2.3.1+rocm6.0 torchvision==0.18.1+rocm6.0 torchaudio==2.3.1+rocm6.0"
;;
59)
INSTALL_PYTORCH_VERSION="torch==2.3.1+cu121 torchvision==0.18.1+cu121 torchaudio==2.3.1+cu121"
INSTALL_XFORMERS_VERSION="xformers==0.0.27"
PYTORCH_TYPE="cu121"
;;
60)
INSTALL_PYTORCH_VERSION="torch==2.3.1+cu118 torchvision==0.18.1+cu118 torchaudio==2.3.1+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.27+cu118"
PYTORCH_TYPE="cu118"
;;
61)
INSTALL_PYTORCH_VERSION="torch==2.4.0 torchvision==0.19.0 torchaudio==2.4.0"
;;
62)
INSTALL_PYTORCH_VERSION="torch==2.4.0+cpu torchvision==0.19.0+cpu torchaudio==2.4.0+cpu"
PYTORCH_TYPE="cpu"
;;
63)
INSTALL_PYTORCH_VERSION="torch==2.4.0+rocm6.0 torchvision==0.19.0+rocm6.0 torchaudio==2.4.0+rocm6.0"
;;
64)
INSTALL_PYTORCH_VERSION="torch==2.4.0+cu124 torchvision==0.19.0+cu124 torchaudio==2.4.0+cu124"
PYTORCH_TYPE="cu124"
;;
65)
INSTALL_PYTORCH_VERSION="torch==2.4.0+cu121 torchvision==0.19.0+cu121 torchaudio==2.4.0+cu121"
INSTALL_XFORMERS_VERSION="xformers==0.0.27.post2"
PYTORCH_TYPE="cu121"
;;
66)
INSTALL_PYTORCH_VERSION="torch==2.4.0+cu118 torchvision==0.19.0+cu118 torchaudio==2.4.0+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.27.post2+cu118"
PYTORCH_TYPE="cu118"
;;
67)
INSTALL_PYTORCH_VERSION="torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1"
;;
68)
INSTALL_PYTORCH_VERSION="torch==2.4.1+cpu torchvision==0.19.1+cpu torchaudio==2.4.1+cpu"
PYTORCH_TYPE="cpu"
;;
69)
INSTALL_PYTORCH_VERSION="torch==2.4.1+rocm6.1 torchvision==0.19.1+rocm6.1 torchaudio==2.4.1+rocm6.1"
INSTALL_XFORMERS_VERSION="xformers===0.0.28.post1"
PYTORCH_TYPE="rocm61"
;;
70)
INSTALL_PYTORCH_VERSION="torch==2.4.1+cu124 torchvision==0.19.1+cu124 torchaudio==2.4.1+cu124"
INSTALL_XFORMERS_VERSION="xformers===0.0.28.post1"
PYTORCH_TYPE="cu124"
;;
71)
INSTALL_PYTORCH_VERSION="torch==2.4.1+cu121 torchvision==0.19.1+cu121 torchaudio==2.4.1+cu121"
INSTALL_XFORMERS_VERSION="xformers===0.0.28.post1"
PYTORCH_TYPE="cu121"
;;
72)
INSTALL_PYTORCH_VERSION="torch==2.4.1+cu118 torchvision==0.19.1+cu118 torchaudio==2.4.1+cu118"
INSTALL_XFORMERS_VERSION="xformers===0.0.28.post1"
PYTORCH_TYPE="cu118"
;;
73)
INSTALL_PYTORCH_VERSION="torch==2.5.0 torchvision==0.20.0 torchaudio==2.5.0"
;;
74)
INSTALL_PYTORCH_VERSION="torch==2.5.0+cpu torchvision==0.20.0+cpu torchaudio==2.5.0+cpu"
PYTORCH_TYPE="cpu"
;;
75)
INSTALL_PYTORCH_VERSION="torch==2.5.0+rocm6.2 torchvision==0.20.0+rocm6.2 torchaudio==2.5.0+rocm6.2"
PYTORCH_TYPE="rocm62"
;;
76)
INSTALL_PYTORCH_VERSION="torch==2.5.0+rocm6.1 torchvision==0.20.0+rocm6.1 torchaudio==2.5.0+rocm6.1"
INSTALL_XFORMERS_VERSION="xformers==0.0.28.post2"
PYTORCH_TYPE="rocm61"
;;
77)
INSTALL_PYTORCH_VERSION="torch==2.5.0+cu124 torchvision==0.20.0+cu124 torchaudio==2.5.0+cu124"
INSTALL_XFORMERS_VERSION="xformers==0.0.28.post2"
PYTORCH_TYPE="cu124"
;;
78)
INSTALL_PYTORCH_VERSION="torch==2.5.0+cu121 torchvision==0.20.0+cu121 torchaudio==2.5.0+cu121"
INSTALL_XFORMERS_VERSION="xformers==0.0.28.post2"
PYTORCH_TYPE="cu121"
;;
79)
INSTALL_PYTORCH_VERSION="torch==2.5.0+cu118 torchvision==0.20.0+cu118 torchaudio==2.5.0+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.28.post2"
PYTORCH_TYPE="cu118"
;;
80)
INSTALL_PYTORCH_VERSION="torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1"
;;
81)
INSTALL_PYTORCH_VERSION="torch==2.5.1+cpu torchvision==0.20.1+cpu torchaudio==2.5.1+cpu"
PYTORCH_TYPE="cpu"
;;
82)
INSTALL_PYTORCH_VERSION="torch==2.5.1+rocm6.2 torchvision==0.20.1+rocm6.2 torchaudio==2.5.1+rocm6.2"
PYTORCH_TYPE="rocm62"
;;
83)
INSTALL_PYTORCH_VERSION="torch==2.5.1+rocm6.1 torchvision==0.20.1+rocm6.1 torchaudio==2.5.1+rocm6.1"
INSTALL_XFORMERS_VERSION="xformers==0.0.28.post3"
PYTORCH_TYPE="rocm61"
;;
84)
INSTALL_PYTORCH_VERSION="torch==2.5.1+cu124 torchvision==0.20.1+cu124 torchaudio==2.5.1+cu124"
INSTALL_XFORMERS_VERSION="xformers==0.0.28.post3"
PYTORCH_TYPE="cu124"
;;
85)
INSTALL_PYTORCH_VERSION="torch==2.5.1+cu121 torchvision==0.20.1+cu121 torchaudio==2.5.1+cu121"
INSTALL_XFORMERS_VERSION="xformers==0.0.28.post3"
PYTORCH_TYPE="cu121"
;;
86)
INSTALL_PYTORCH_VERSION="torch==2.5.1+cu118 torchvision==0.20.1+cu118 torchaudio==2.5.1+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.28.post3"
PYTORCH_TYPE="cu118"
;;
87)
INSTALL_PYTORCH_VERSION="torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0"
;;
88)
INSTALL_PYTORCH_VERSION="torch==2.6.0+cpu torchvision==0.21.0+cpu torchaudio==2.6.0+cpu"
PYTORCH_TYPE="cpu"
;;
89)
INSTALL_PYTORCH_VERSION="torch==2.6.0+rocm6.2.4 torchvision==0.21.0+rocm6.2.4 torchaudio==2.6.0+rocm6.2.4"
INSTALL_XFORMERS_VERSION="xformers==0.0.29.post3"
PYTORCH_TYPE="rocm624"
;;
90)
INSTALL_PYTORCH_VERSION="torch==2.6.0+rocm6.1 torchvision==0.21.0+rocm6.1 torchaudio==2.6.0+rocm6.1"
INSTALL_XFORMERS_VERSION="xformers==0.0.29.post3"
PYTORCH_TYPE="rocm61"
;;
91)
INSTALL_PYTORCH_VERSION="torch==2.6.0+xpu torchvision==0.21.0+xpu torchaudio==2.6.0+xpu"
PYTORCH_TYPE="xpu"
;;
92)
INSTALL_PYTORCH_VERSION="torch==2.6.0+cu126 torchvision==0.21.0+cu126 torchaudio==2.6.0+cu126"
INSTALL_XFORMERS_VERSION="xformers==0.0.29.post3"
PYTORCH_TYPE="cu126"
;;
93)
INSTALL_PYTORCH_VERSION="torch==2.6.0+cu124 torchvision==0.21.0+cu124 torchaudio==2.6.0+cu124"
INSTALL_XFORMERS_VERSION="xformers==0.0.29.post3"
PYTORCH_TYPE="cu124"
;;
94)
INSTALL_PYTORCH_VERSION="torch==2.6.0+cu118 torchvision==0.21.0+cu118 torchaudio==2.6.0+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.29.post3"
PYTORCH_TYPE="cu118"
;;
95)
INSTALL_PYTORCH_VERSION="torch==2.7.0 torchvision==0.22.0 torchaudio==2.7.0"
;;
96)
INSTALL_PYTORCH_VERSION="torch==2.7.0+cpu torchvision==0.22.0+cpu torchaudio==2.7.0+cpu"
PYTORCH_TYPE="cpu"
;;
97)
INSTALL_PYTORCH_VERSION="torch==2.7.0+rocm6.3 torchvision==0.22.0+rocm6.3 torchaudio==2.7.0+rocm6.3"
INSTALL_XFORMERS_VERSION="xformers==0.0.30"
PYTORCH_TYPE="rocm63"
;;
98)
INSTALL_PYTORCH_VERSION="torch==2.7.0+rocm6.2.4 torchvision==0.22.0+rocm6.2.4 torchaudio==2.7.0+rocm6.2.4"
INSTALL_XFORMERS_VERSION="xformers==0.0.30"
PYTORCH_TYPE="rocm624"
;;
99)
INSTALL_PYTORCH_VERSION="torch==2.7.0+xpu torchvision==0.22.0+xpu torchaudio==2.7.0+xpu"
PYTORCH_TYPE="xpu"
;;
100)
INSTALL_PYTORCH_VERSION="torch==2.7.0+cu128 torchvision==0.22.0+cu128 torchaudio==2.7.0+cu128"
INSTALL_XFORMERS_VERSION="xformers==0.0.30"
PYTORCH_TYPE="cu128"
;;
101)
INSTALL_PYTORCH_VERSION="torch==2.7.0+cu126 torchvision==0.22.0+cu126 torchaudio==2.7.0+cu126"
INSTALL_XFORMERS_VERSION="xformers==0.0.30"
PYTORCH_TYPE="cu126"
;;
102)
INSTALL_PYTORCH_VERSION="torch==2.7.0+cu118 torchvision==0.22.0+cu118 torchaudio==2.7.0+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.30"
PYTORCH_TYPE="cu118"
;;
103)
INSTALL_PYTORCH_VERSION="torch==2.7.1 torchvision==0.22.1 torchaudio==2.7.1"
;;
104)
INSTALL_PYTORCH_VERSION="torch==2.7.1+cpu torchvision==0.22.1+cpu torchaudio==2.7.1+cpu"
PYTORCH_TYPE="cpu"
;;
105)
INSTALL_PYTORCH_VERSION="torch==2.7.1+rocm6.3 torchvision==0.22.1+rocm6.3 torchaudio==2.7.1+rocm6.3"
INSTALL_XFORMERS_VERSION="xformers==0.0.31.post1"
PYTORCH_TYPE="rocm63"
;;
106)
INSTALL_PYTORCH_VERSION="torch==2.7.1+rocm6.2.4 torchvision==0.22.1+rocm6.2.4 torchaudio==2.7.1+rocm6.2.4"
INSTALL_XFORMERS_VERSION="xformers==0.0.31.post1"
PYTORCH_TYPE="rocm624"
;;
107)
INSTALL_PYTORCH_VERSION="torch==2.7.1+xpu torchvision==0.22.1+xpu torchaudio==2.7.1+xpu"
PYTORCH_TYPE="xpu"
;;
108)
INSTALL_PYTORCH_VERSION="torch==2.7.1+cu128 torchvision==0.22.1+cu128 torchaudio==2.7.1+cu128"
INSTALL_XFORMERS_VERSION="xformers==0.0.31.post1"
PYTORCH_TYPE="cu128"
;;
109)
INSTALL_PYTORCH_VERSION="torch==2.7.1+cu126 torchvision==0.22.1+cu126 torchaudio==2.7.1+cu126"
INSTALL_XFORMERS_VERSION="xformers==0.0.31.post1"
PYTORCH_TYPE="cu126"
;;
110)
INSTALL_PYTORCH_VERSION="torch==2.7.1+cu118 torchvision==0.22.1+cu118 torchaudio==2.7.1+cu118"
INSTALL_XFORMERS_VERSION="xformers==0.0.31.post1"
PYTORCH_TYPE="cu118"
;;
111)
INSTALL_PYTORCH_VERSION="torch==2.8.0 torchvision==0.23.0 torchaudio==2.8.0"
;;
112)
INSTALL_PYTORCH_VERSION="torch==2.8.0+cpu torchvision==0.23.0+cpu torchaudio==2.8.0+cpu"
PYTORCH_TYPE="cpu"
;;
113)
INSTALL_PYTORCH_VERSION="torch==2.8.0+rocm6.4 torchvision==0.23.0+rocm6.4 torchaudio==2.8.0+rocm6.4"
INSTALL_XFORMERS_VERSION="xformers==0.0.32.post2"
PYTORCH_TYPE="rocm64"
;;
114)
INSTALL_PYTORCH_VERSION="torch==2.8.0+rocm6.3 torchvision==0.23.0+rocm6.3 torchaudio==2.8.0+rocm6.3"
PYTORCH_TYPE="rocm63"
;;
115)
INSTALL_PYTORCH_VERSION="torch==2.8.0+xpu torchvision==0.23.0+xpu torchaudio==2.8.0+xpu"
PYTORCH_TYPE="xpu"
;;
116)
INSTALL_PYTORCH_VERSION="torch==2.8.0+cu129 torchvision==0.23.0+cu129 torchaudio==2.8.0+cu129"
INSTALL_XFORMERS_VERSION="xformers==0.0.32.post2"
PYTORCH_TYPE="cu129"
;;
117)
INSTALL_PYTORCH_VERSION="torch==2.8.0+cu128 torchvision==0.23.0+cu128 torchaudio==2.8.0+cu128"
INSTALL_XFORMERS_VERSION="xformers==0.0.32.post2"
PYTORCH_TYPE="cu128"
;;
118)
INSTALL_PYTORCH_VERSION="torch==2.8.0+cu126 torchvision==0.23.0+cu126 torchaudio==2.8.0+cu126"
INSTALL_XFORMERS_VERSION="xformers==0.0.32.post2"
PYTORCH_TYPE="cu126"
;;
esac
}
# PyTorch 类型选择
# 设置 PYTORCH_TYPE 全局变量指定 PyTorch 类型
# 注:
# 指定的 PYTORCH_TYPE 类型为大致类型, 无法被 install_pytorch 直接使用
pytorch_type_select() {
local dialog_arg
unset PYTORCH_TYPE
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Term-SD" \
--backtitle "PyTorch 安装版本选项" \
--ok-label "确认" --no-cancel \
--menu "请选择要安装的 PyTorch 类型\n当前 PyTorch 版本: $(get_pytorch_version)\n当前 xFormers 版本: $(get_xformers_version)" \
$(get_dialog_size_menu) \
"1" "CUDA (Nvidia 显卡)" \
"2" "ROCm (AMD 显卡)" \
"3" "XPU (Intel 显卡)" \
"4" "CPU (使用 CPU)" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
PYTORCH_TYPE="cuda"
;;
2)
PYTORCH_TYPE="rocm"
;;
3)
PYTORCH_TYPE="xpu"
;;
4)
PYTORCH_TYPE="cpu"
;;
*)
term_sd_echo "未选择 PyTorch 类型, 默认选择 cuda 类型"
PYTORCH_TYPE="cuda"
;;
esac
}
# 设置 Pip 的安装模式
# 选择后设置 PIP_UPDATE_PACKAGE_ARG, PIP_USE_PEP517_ARG, PIP_FORCE_REINSTALL_ARG, PIP_BREAK_SYSTEM_PACKAGE_ARG 全局变量
# 使用:
# pip_install_mode_select <要默认启用的参数>
# 参数对应的选项:
# upgrade: 更新软件包 (--upgrade)
# pep517: 标准构建安装 (--use-pep517)
# force_reinstall: 强制重新安装 (--force-reinstall)
# break_system_package: 强制使用 Pip 安装 (--break-system-packages)
pip_install_mode_select() {
local dialog_arg
local i
local use_upgrade="OFF"
local use_pep517="OFF"
local use_force_reinstall="OFF"
local use_break_system_package="OFF"
unset PIP_UPDATE_PACKAGE_ARG
unset PIP_USE_PEP517_ARG
unset PIP_FORCE_REINSTALL_ARG
unset PIP_BREAK_SYSTEM_PACKAGE_ARG
# 界面预设
for i in $@; do
case "${i}" in
upgrade)
use_upgrade="ON"
;;
pep517)
use_pep517="ON"
;;
force_reinstall)
use_force_reinstall="ON"
;;
break_system_package)
use_break_system_package="ON"
;;
esac
done
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Term-SD" \
--backtitle "Pip 安装模式选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择 Pip 安装方式, 注:\n1. 安装时更新软件包\n2. 标准构建安装可解决一些报错问题, 但速度较慢\n3. 软件包存在时将重新安装\n4. 忽略系统警告强制使用 Pip 安装软件包" \
$(get_dialog_size_menu) \
"1" "> 更新软件包 (--upgrade)" "${use_upgrade}" \
"2" "> 标准构建安装 (--use-pep517)" "${use_pep517}" \
"3" "> 强制重新安装 (--force-reinstall)" "${use_force_reinstall}" \
"4" "> 强制使用 Pip 安装 (--break-system-packages)" "${use_break_system_package}" \
3>&1 1>&2 2>&3)
for i in ${dialog_arg}; do
case "${i}" in
1)
PIP_UPDATE_PACKAGE_ARG="--upgrade"
;;
2)
PIP_USE_PEP517_ARG="--use-pep517"
;;
3)
PIP_FORCE_REINSTALL_ARG="--force-reinstall"
;;
4)
PIP_BREAK_SYSTEM_PACKAGE_ARG="--break-system-packages"
;;
esac
done
}
# 安装前确认界面
# 加参数可修改提示内容
# 使用:
# term_sd_install_confirm <提示内容>
term_sd_install_confirm() {
local input_text=$@
local use_pip_info
local use_github_mirror_info
local enable_only_proxy_info
local use_modelscope_src_info
local pytorch_ver_info
local xformers_ver_info
local use_break_system_package_info
local use_pep517_info
local use_force_reinstall_info
local use_upgrade_info
local use_prefer_binary_info
if is_use_pip_mirror; then
use_pip_info="启用"
else
use_pip_info="禁用"
fi
use_github_mirror_info=$GITHUB_MIRROR_NAME
if is_use_modelscope_src; then
use_modelscope_src_info="启用"
else
use_modelscope_src_info="禁用"
fi
if is_use_only_proxy; then
enable_only_proxy_info="启用"
else
enable_only_proxy_info="禁用"
fi
if [[ ! -z "${PIP_BREAK_SYSTEM_PACKAGE_ARG}" ]]; then
use_break_system_package_info="启用"
else
use_break_system_package_info="禁用"
fi
if [[ ! -z "${INSTALL_PYTORCH_VERSION}" ]]; then
pytorch_ver_info=$INSTALL_PYTORCH_VERSION
else
pytorch_ver_info="无"
fi
if [[ ! -z "${INSTALL_XFORMERS_VERSION}" ]]; then
xformers_ver_info=$INSTALL_XFORMERS_VERSION
else
xformers_ver_info="无"
fi
if [[ ! -z "${PIP_USE_PEP517_ARG}" ]]; then
use_pep517_info="标准构建安装 (--use-pep517)"
else
use_pep517_info="常规安装 (setup.py)"
fi
if [[ ! -z "${PIP_FORCE_REINSTALL_ARG}" ]]; then
use_force_reinstall_info="启用"
else
use_force_reinstall_info="禁用"
fi
if [[ ! -z "${PIP_UPDATE_PACKAGE_ARG}" ]]; then
use_upgrade_info="启用"
else
use_upgrade_info="禁用"
fi
if (dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "安装确认选项" \
--yes-label "是" --no-label "否" \
--yesno "$@\n
PyPI 镜像源: ${use_pip_info}\n
Github 镜像: ${use_github_mirror_info}\n
Huggingface / Github 下载源独占代理: ${enable_only_proxy_info}\n
使用 ModelScope 模型下载源: ${use_modelscope_src_info}\n
强制使用 Pip: ${use_break_system_package_info}\n
PyTorch 版本: ${pytorch_ver_info}\n
xFormers 版本: ${xformers_ver_info}\n
Pip 安装方式: ${use_pep517_info}\n
Pip 强制重装: ${use_force_reinstall_info}\n
Pip 更新软件包: ${use_upgrade_info}\
" $(get_dialog_size)); then
term_sd_echo "确认进行安装"
return 0
else
term_sd_echo "取消安装"
return 1
fi
}
# Github 镜像源测试
# 镜像源不保证都可用, 已知 gitclone.com 提供的镜像克隆不完整, 易出现问题
# 测试完成后将输出可用的 Github 镜像源格式
github_mirror_test() {
# 镜像源列表
local mirror_list=$GITHUB_MIRROR_LIST
local git_req
local i
local HTTP_PROXY
local HTTPS_PROXY
HTTP_PROXY= # 临时清除配置好的代理,防止干扰测试
HTTPS_PROXY=
[ -d "${START_PATH}/term-sd/task/github_mirror_test" ] && rm -rf "${START_PATH}/term-sd/task/github_mirror_test" &> /dev/null
for i in ${mirror_list}; do
git clone $(git_format_repository_url ${i} https://github.com/licyk/empty) "${START_PATH}/term-sd/task/github_mirror_test" --depth=1 &> /dev/null # 测试镜像源是否正常连接
git_req=$?
rm -rf "${START_PATH}/term-sd/task/github_mirror_test" &> /dev/null
if [[ ${git_req} == 0 ]]; then
echo ${i}
return
fi
done
echo "https://github.com/term_sd_git_user/term_sd_git_repo"
}
# 清理安装完成后留下的参数
# 每次执行完安装任务后需要执行该函数清理参数
clean_install_config() {
if term_sd_is_debug; then
term_sd_echo "待清理的用于安装的变量:"
term_sd_echo "PIP_INDEX_MIRROR: ${PIP_INDEX_MIRROR}"
term_sd_echo "PIP_EXTRA_INDEX_MIRROR: ${PIP_EXTRA_INDEX_MIRROR}"
term_sd_echo "PIP_FIND_LINKS_MIRROR: ${PIP_FIND_LINKS_MIRROR}"
term_sd_echo "UV_INDEX_MIRROR: ${UV_INDEX_MIRROR}"
term_sd_echo "UV_EXTRA_INDEX_MIRROR: ${UV_EXTRA_INDEX_MIRROR}"
term_sd_echo "UV_FIND_LINKS_MIRROR: ${UV_FIND_LINKS_MIRROR}"
term_sd_echo "USE_PIP_MIRROR: ${USE_PIP_MIRROR}"
term_sd_echo "PIP_BREAK_SYSTEM_PACKAGE_ARG: ${PIP_BREAK_SYSTEM_PACKAGE_ARG}"
term_sd_echo "TERM_SD_ENABLE_ONLY_PROXY: ${TERM_SD_ENABLE_ONLY_PROXY}"
term_sd_echo "USE_MODELSCOPE_MODEL_SRC: ${USE_MODELSCOPE_MODEL_SRC}"
term_sd_echo "GITHUB_MIRROR: ${GITHUB_MIRROR}"
term_sd_echo "GITHUB_MIRROR_NAME: ${GITHUB_MIRROR_NAME}"
term_sd_echo "INSTALL_PYTORCH_VERSION: ${INSTALL_PYTORCH_VERSION}"
term_sd_echo "INSTALL_XFORMERS_VERSION: ${INSTALL_XFORMERS_VERSION}"
term_sd_echo "PIP_USE_PEP517_ARG: ${PIP_USE_PEP517_ARG}"
term_sd_echo "PIP_FORCE_REINSTALL_ARG: ${PIP_FORCE_REINSTALL_ARG}"
term_sd_echo "PIP_UPDATE_PACKAGE_ARG: ${PIP_UPDATE_PACKAGE_ARG}"
term_sd_echo "PYTORCH_TYPE: ${PYTORCH_TYPE}"
term_sd_echo "SD_WEBUI_REPO: ${SD_WEBUI_REPO}"
term_sd_echo "SD_WEBUI_BRANCH: ${SD_WEBUI_BRANCH}"
fi
unset PIP_INDEX_MIRROR # 指定 PyPI 镜像源的参数
unset PIP_EXTRA_INDEX_MIRROR
unset PIP_FIND_LINKS_MIRROR
unset UV_INDEX_MIRROR
unset UV_EXTRA_INDEX_MIRROR
unset UV_FIND_LINKS_MIRROR
unset USE_PIP_MIRROR # 是否启用 Pip 镜像
unset PIP_BREAK_SYSTEM_PACKAGE_ARG # 是否在 Pip 使用 --break-system-package 参数
unset TERM_SD_ENABLE_ONLY_PROXY # 是否启用 Github / HuggingFace 独占代理功能
unset USE_MODELSCOPE_MODEL_SRC # 是否使用 ModelScope 模型站下载模型
unset GITHUB_MIRROR # Github 镜像的格式, 如: "https://github.com/term_sd_git_user/term_sd_git_repo", 需进行处理后才能使用
unset GITHUB_MIRROR_NAME # 展示 Github 镜像源的名称
unset INSTALL_PYTORCH_VERSION # 要安装的 PyTorch 版本
unset INSTALL_XFORMERS_VERSION # 要安装的 xFormers 版本
unset PIP_USE_PEP517_ARG # 是否在 Pip 使用 --use-pep517 参数
unset PIP_FORCE_REINSTALL_ARG # 是否在 Pip 使用 --force-reinstall 参数
unset PIP_UPDATE_PACKAGE_ARG # 是否更新软件包, 使用 --upgrade 参数
unset PYTORCH_TYPE # PyTorch 种类, 用于切换 PyTorch 镜像源
unset SD_WEBUI_REPO # SD WebUI 远程源地址, 用于安装 SD WebUI 时选择要安装的分支
unset SD_WEBUI_BRANCH # SD WebUI 分支, 用于安装 SD WebUI 时选择要切换成的分支
}
# 如果启用了 PyPI 镜像源, 则返回0
is_use_pip_mirror() {
if [[ "${USE_PIP_MIRROR}" == 1 ]]; then
return 0
else
return 1
fi
}
# 如果启用了 Github / HuggingFace 独占代理, 则返回0
is_use_only_proxy() {
if [[ "${TERM_SD_ENABLE_ONLY_PROXY}" == 1 ]]; then
return 0
else
return 1
fi
}
# 如果使用了 ModelScope 模型下载源, 则返回0
is_use_modelscope_src() {
if [[ "${USE_MODELSCOPE_MODEL_SRC}" == 1 ]]; then
return 0
else
return 1
fi
}
|
2301_81996401/term-sd
|
modules/install_prepare.sh
|
Shell
|
agpl-3.0
| 50,694
|
#!/bin/bash
# PyTorch 重装功能
pytorch_reinstall() {
if (dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "PyTorch 重装选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重新安装 PyTorch ?" \
$(get_dialog_size)); then
# 安装前的准备
enter_venv
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否重新安装 PyTorch ?"; then
# 开始安装 PyTorch
term_sd_print_line "PyTorch 安装"
term_sd_tmp_disable_proxy
install_pytorch
term_sd_tmp_enable_proxy
clean_install_config # 清理安装参数
term_sd_echo "PyTorch 安装结束"
term_sd_pause
else
clean_install_config # 清理安装参数
fi
exit_venv
fi
}
# PyTorch 安装
# 使用 INSTALL_PYTORCH_VERSION 全局变量读取需要安装的 PyTorch 版本
# 使用 PYTORCH_TYPE 判断 PyTorch 种类, 用于切换 PyTorch 镜像源
install_pytorch() {
if [[ ! -z "${INSTALL_PYTORCH_VERSION}" ]]; then
# 检测是否使用 PyTorch IPEX Legacy 版本
case "${PYTORCH_TYPE}" in
ipex_legacy_arc|ipex_legacy_core_ultra)
process_pytorch_ipex_legacy
;;
*)
process_pytorch
;;
esac
else
term_sd_echo "未指定 PyTorch 版本, 跳过安装"
fi
}
# 处理 PyTorch IPEX 的安装
# 使用 INSTALL_PYTORCH_VERSION 全局变量读取需要安装的 PyTorch 版本
# 使用 PYTORCH_TYPE 判断 PyTorch 种类, 用于切换 PyTorch 镜像源
# 接受 Pip 参数:
# PIP_INDEX_MIRROR PIP_EXTRA_INDEX_MIRROR PIP_FIND_LINKS_MIRROR
# UV_INDEX_MIRROR UV_EXTRA_INDEX_MIRROR UV_FIND_LINKS_MIRROR
# PIP_BREAK_SYSTEM_PACKAGE_ARG PIP_USE_PEP517_ARG PIP_FORCE_REINSTALL_ARG
# PIP_UPDATE_PACKAGE_ARG
process_pytorch_ipex_legacy() {
local torch_ipex_ver
local torch_ipex_ver_info
local ipex_type
local torch_ver
local ipex_win_url="--find-links https://licyk.github.io/t/pypi/index.html"
local ipex_url_cn="--extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/cn"
local ipex_url_us="--extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us"
local ipex_win_url_uv="--find-links https://licyk.github.io/t/pypi/index.html"
local ipex_url_cn_uv="--index https://pytorch-extension.intel.com/release-whl/stable/xpu/cn"
local ipex_url_us_uv="--index https://pytorch-extension.intel.com/release-whl/stable/xpu/us"
if [[ "${PYTORCH_TYPE}" == "ipex_legacy_core_ultra" ]]; then
ipex_type="Core_Ultra"
elif [[ "${PYTORCH_TYPE}" == "ipex_legacy_arc" ]]; then
ipex_type="Arc"
else
ipex_type="Core_Ultra"
fi
case "${PYTORCH_TYPE}" in
ipex_legacy_arc|ipex_legacy_core_ultra)
torch_ipex_ver=$(awk '{print $2}' <<< ${INSTALL_PYTORCH_VERSION})
torch_ipex_ver_info="PyTorch $(awk '{print $2}' <<< ${INSTALL_PYTORCH_VERSION}) (IPEX ${ipex_type})"
;;
esac
torch_ver=$INSTALL_PYTORCH_VERSION
term_sd_echo "将要安装的 PyTorch 版本组合:"
term_sd_echo "PyTorch: ${torch_ipex_ver_info}"
term_sd_echo "开始安装 PyTorch"
case "${PYTORCH_TYPE}" in
ipex_legacy_arc|ipex_legacy_core_ultra)
if is_windows_platform; then
# Windows 平台
# IPEX(Windows): https://arc.nuullll.com/resource/
case "${torch_ipex_ver}" in
2.0.0)
if term_sd_is_use_uv; then
install_python_package torch==2.0.0a0+gite9ebda2 torchvision==0.15.2a0+fa99a53 intel_extension_for_pytorch==2.0.110+gitc6ea20b ${ipex_win_url_uv}
else
install_python_package torch==2.0.0a0+gite9ebda2 torchvision==0.15.2a0+fa99a53 intel_extension_for_pytorch==2.0.110+gitc6ea20b ${ipex_win_url} --no-warn-conflicts
fi
;;
2.1.0)
if [[ "${ipex_type}" == "Core_Ultra" ]]; then # 核显
if term_sd_is_use_uv; then
install_python_package torch==2.1.0a0+git7bcf7da torchvision==0.16.0+fbb4cc5 torchaudio==2.1.0+6ea1133 intel_extension_for_pytorch==2.1.20+git4849f3b ${ipex_win_url_uv}
else
install_python_package torch==2.1.0a0+git7bcf7da torchvision==0.16.0+fbb4cc5 torchaudio==2.1.0+6ea1133 intel_extension_for_pytorch==2.1.20+git4849f3b ${ipex_win_url} --no-warn-conflicts
fi
else # 独显
if term_sd_is_use_uv; then
install_python_package torch==2.1.0a0+cxx11.abi torchvision==0.16.0a0+cxx11.abi torchaudio==2.1.0a0+cxx11.abi intel_extension_for_pytorch==2.1.10+xpu ${ipex_win_url_uv}
else
install_python_package torch==2.1.0a0+cxx11.abi torchvision==0.16.0a0+cxx11.abi torchaudio==2.1.0a0+cxx11.abi intel_extension_for_pytorch==2.1.10+xpu ${ipex_win_url} --no-warn-conflicts
fi
fi
;;
esac
else
# 其他平台
# IPEX: https://intel.github.io/intel-extension-for-pytorch/#installation
if is_use_pip_mirror; then # 国内镜像
case "${torch_ipex_ver}" in
2.0.0)
if term_sd_is_use_uv; then
install_python_package torch==2.0.1a0 torchvision==0.15.2a0 intel-extension-for-pytorch==2.0.120+xpu ${ipex_url_cn_uv}
else
install_python_package torch==2.0.1a0 torchvision==0.15.2a0 intel-extension-for-pytorch==2.0.120+xpu ${ipex_url_cn} --no-warn-conflicts
fi
;;
2.1.0)
if term_sd_is_use_uv; then
install_python_package torch==2.1.0.post0 torchvision==0.16.0.post0 torchaudio==2.1.0.post0 intel-extension-for-pytorch==2.1.20 ${ipex_url_cn_uv}
else
install_python_package torch==2.1.0.post0 torchvision==0.16.0.post0 torchaudio==2.1.0.post0 intel-extension-for-pytorch==2.1.20 ${ipex_url_cn} --no-warn-conflicts
fi
;;
esac
else
case "${torch_ipex_ver}" in
2.0.0)
if term_sd_is_use_uv; then
install_python_package torch==2.0.1a0 torchvision==0.15.2a0 intel-extension-for-pytorch==2.0.120+xpu ${ipex_url_us_uv}
else
install_python_package torch==2.0.1a0 torchvision==0.15.2a0 intel-extension-for-pytorch==2.0.120+xpu ${ipex_url_us} --no-warn-conflicts
fi
;;
2.1.0)
if term_sd_is_use_uv; then
install_python_package torch==2.1.0.post0 torchvision==0.16.0.post0 torchaudio==2.1.0.post0 intel-extension-for-pytorch==2.1.20 ${ipex_url_us_uv}
else
install_python_package torch==2.1.0.post0 torchvision==0.16.0.post0 torchaudio==2.1.0.post0 intel-extension-for-pytorch==2.1.20 ${ipex_url_us} --no-warn-conflicts
fi
;;
esac
fi
fi
;;
esac
if [[ "$?" == 0 ]]; then
term_sd_echo "PyTorch 安装成功"
else
term_sd_echo "PyTorch 安装失败"
return 1
fi
}
# 处理 PyTorch 的安装
# 使用 INSTALL_PYTORCH_VERSION 全局变量读取需要安装的 PyTorch 版本
# 使用 INSTALL_XFORMERS_VERSION 全局变量读取需要安装的 xFormers 版本
# 使用 PYTORCH_TYPE 判断 PyTorch 种类, 用于切换 PyTorch 镜像源
# 接受 Pip 参数:
# PIP_INDEX_MIRROR PIP_EXTRA_INDEX_MIRROR PIP_FIND_LINKS_MIRROR
# UV_INDEX_MIRROR UV_EXTRA_INDEX_MIRROR UV_FIND_LINKS_MIRROR
# PIP_BREAK_SYSTEM_PACKAGE_ARG PIP_USE_PEP517_ARG PIP_FORCE_REINSTALL_ARG
# PIP_UPDATE_PACKAGE_ARG
process_pytorch() {
local torch_ver
local xformers_ver
local pypi_index_url
local pypi_extra_index_url
local pypi_find_links_url
local with_pypi_mirror_env_value=0
torch_ver=$INSTALL_PYTORCH_VERSION
xformers_ver=$INSTALL_XFORMERS_VERSION
term_sd_echo "将要安装的 PyTorch 版本组合:"
term_sd_echo "PyTorch: ${torch_ver}"
term_sd_echo "xFormers: $([[ ! -z "${xformers_ver}" ]] && echo ${xformers_ver} || echo "无")"
# 配置 PyTorch 镜像源
if is_use_pip_mirror; then # 镜像源
case "${PYTORCH_TYPE}" in
cu129)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/cu129"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cu128)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/cu128"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cu126)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/cu126"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cu124)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/cu124"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cu121)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/cu121"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cu118)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/cu118"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
rocm61)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/rocm6.1"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
rocm62)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/rocm6.2"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
rocm624)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/rocm6.2.4"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
rocm63)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/rocm6.3"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
rocm64)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/rocm6.4"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
xpu)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/xpu"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cpu)
pypi_index_url="https://mirror.nju.edu.cn/pytorch/whl/cpu"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
other)
pypi_index_url="https://download.pytorch.org/whl"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
*)
true
;;
esac
else # 官方源
case "${PYTORCH_TYPE}" in
cu129)
pypi_index_url="https://download.pytorch.org/whl/cu129"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cu128)
pypi_index_url="https://download.pytorch.org/whl/cu128"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cu126)
pypi_index_url="https://download.pytorch.org/whl/cu126"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cu124)
pypi_index_url="https://download.pytorch.org/whl/cu124"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cu121)
pypi_index_url="https://download.pytorch.org/whl/cu121"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cu118)
pypi_index_url="https://download.pytorch.org/whl/cu118"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
rocm61)
pypi_index_url="https://download.pytorch.org/whl/rocm6.1"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
rocm62)
pypi_index_url="https://download.pytorch.org/whl/rocm6.2"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
rocm624)
pypi_index_url="https://download.pytorch.org/whl/rocm6.2.4"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
rocm63)
pypi_index_url="https://download.pytorch.org/whl/rocm6.3"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
rocm64)
pypi_index_url="https://download.pytorch.org/whl/rocm6.4"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
xpu)
pypi_index_url="https://download.pytorch.org/whl/xpu"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
cpu)
pypi_index_url="https://download.pytorch.org/whl/cpu"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
other)
pypi_index_url="https://download.pytorch.org/whl"
pypi_extra_index_url=""
pypi_find_links_url=""
with_pypi_mirror_env_value=1
;;
*)
true
;;
esac
fi
# 安装 PyTorch
term_sd_echo "开始安装 PyTorch"
if [[ "${with_pypi_mirror_env_value}" == 1 ]]; then
# 使用临时镜像源环境变量进行安装
if term_sd_is_use_uv; then
UV_DEFAULT_INDEX=$pypi_index_url \
UV_INDEX=$pypi_extra_index_url \
UV_FIND_LINKS=$pypi_find_links_url \
term_sd_try term_sd_uv_install ${torch_ver} \
${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG}
if check_uv_install_failed_and_warning; then
PIP_INDEX_URL=$pypi_index_url \
PIP_EXTRA_INDEX_URL=$pypi_extra_index_url \
PIP_FIND_LINKS=$pypi_find_links_url \
term_sd_try term_sd_pip install ${torch_ver} \
${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_USE_PEP517_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG} --no-warn-conflicts
fi
else
PIP_INDEX_URL=$pypi_index_url \
PIP_EXTRA_INDEX_URL=$pypi_extra_index_url \
PIP_FIND_LINKS=$pypi_find_links_url \
term_sd_try term_sd_pip install ${torch_ver} \
${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_USE_PEP517_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG} --no-warn-conflicts
fi
else
if term_sd_is_use_uv; then
term_sd_try term_sd_uv_install ${torch_ver} \
${UV_INDEX_MIRROR} ${UV_EXTRA_INDEX_MIRROR} ${UV_FIND_LINKS_MIRROR} ${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG}
if check_uv_install_failed_and_warning; then
term_sd_try term_sd_pip install ${torch_ver} \
${PIP_INDEX_MIRROR} ${PIP_EXTRA_INDEX_MIRROR} ${PIP_FIND_LINKS_MIRROR} ${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_USE_PEP517_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG} --no-warn-conflicts
fi
else
term_sd_try term_sd_pip install ${torch_ver} \
${PIP_INDEX_MIRROR} ${PIP_EXTRA_INDEX_MIRROR} ${PIP_FIND_LINKS_MIRROR} ${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_USE_PEP517_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG} --no-warn-conflicts
fi
fi
if [[ "$?" == 0 ]]; then
term_sd_echo "PyTorch 安装成功"
else
term_sd_echo "PyTorch 安装失败, 未进行安装 xFormers"
return 1
fi
# 安装 xFormers
if [[ ! -z "${xformers_ver}" ]]; then
if get_python_env_pkg | grep -q xformers; then # 将原有的 xFormers 卸载
term_sd_echo "卸载原有版本的 xFormers"
term_sd_try term_sd_pip uninstall xformers -y
fi
term_sd_echo "开始安装 xFormers"
if [[ "${with_pypi_mirror_env_value}" == 1 ]]; then
# 使用临时镜像源环境变量进行安装
if term_sd_is_use_uv; then
UV_DEFAULT_INDEX=$pypi_index_url \
UV_INDEX=$pypi_extra_index_url \
UV_FIND_LINKS=$pypi_find_links_url \
term_sd_try term_sd_uv_install ${xformers_ver} \
${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG} --no-deps
if check_uv_install_failed_and_warning; then
PIP_INDEX_URL=$pypi_index_url \
PIP_EXTRA_INDEX_URL=$pypi_extra_index_url \
PIP_FIND_LINKS=$pypi_find_links_url \
term_sd_try term_sd_pip install ${xformers_ver} \
${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_USE_PEP517_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG} --no-warn-conflicts --no-deps
fi
else
PIP_INDEX_URL=$pypi_index_url \
PIP_EXTRA_INDEX_URL=$pypi_extra_index_url \
PIP_FIND_LINKS=$pypi_find_links_url \
term_sd_try term_sd_pip install ${xformers_ver} \
${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_USE_PEP517_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG} --no-warn-conflicts --no-deps
fi
else
if term_sd_is_use_uv; then
term_sd_try term_sd_uv_install ${xformers_ver} \
${UV_INDEX_MIRROR} ${UV_EXTRA_INDEX_MIRROR} ${UV_FIND_LINKS_MIRROR} ${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG} --no-deps
if check_uv_install_failed_and_warning; then
term_sd_try term_sd_pip install ${xformers_ver} \
${PIP_INDEX_MIRROR} ${PIP_EXTRA_INDEX_MIRROR} ${PIP_FIND_LINKS_MIRROR} ${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_USE_PEP517_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG} --no-warn-conflicts --no-deps
fi
else
term_sd_try term_sd_pip install ${xformers_ver} \
${PIP_INDEX_MIRROR} ${PIP_EXTRA_INDEX_MIRROR} ${PIP_FIND_LINKS_MIRROR} ${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_USE_PEP517_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG} --no-warn-conflicts --no-deps
fi
fi
else
return 0
fi
if [[ "$?" == 0 ]]; then
term_sd_echo "xFormers 安装成功"
else
term_sd_echo "xFormers 安装失败"
return 1
fi
}
|
2301_81996401/term-sd
|
modules/install_pytorch.sh
|
Shell
|
agpl-3.0
| 21,443
|
#!/bin/bash
# SD WebUI 安装
# 使用 SD_WEBUI_INSTALL_EXTENSION_LIST 全局变量读取需要安装的 SD WebUI 插件
# 使用 SD_WEBUI_DOWNLOAD_MODEL_LIST 全局变量读取需要下载的模型
install_sd_webui() {
local cmd_sum
local cmd_point
local i
if [[ -f "${START_PATH}/term-sd/task/sd_webui_install.sh" ]]; then # 检测到有未完成的安装任务时直接执行安装任务
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/sd_webui_install.sh" | wc -l) + 1 )) # 统计命令行数
term_sd_print_line "Stable-Diffusion-WebUI 安装"
for (( cmd_point=1; cmd_point <= cmd_sum; cmd_point++ )); do
term_sd_echo "Stable-Diffusion-WebUI 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/sd_webui_install.sh" "${cmd_point}"
if [[ ! "$?" == 0 ]]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 安装结果" \
--ok-label "确认" \
--msgbox "Stable-Diffusion-WebUI 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "Stable-Diffusion-WebUI 安装结束"
rm -f "${START_PATH}/term-sd/task/sd_webui_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 安装结果" \
--ok-label "确认" \
--msgbox "Stable-Diffusion-WebUI 安装结束, 选择确定进入管理界面" \
$(get_dialog_size)
sd_webui_manager # 进入管理界面
else # 生成安装任务并执行安装任务
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
select_install_sd_webui_branch # 分支选择
sd_webui_extension_install_select # 插件选择
sd_webui_download_model_select # 模型选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否安装 Stable-Diffusion-WebUI ?"; then
term_sd_print_line "Stable-Diffusion-WebUI 安装"
term_sd_echo "生成安装任务中"
term_sd_set_install_env_value >> "${START_PATH}/term-sd/task/sd_webui_install.sh" # 环境变量
cat "${START_PATH}/term-sd/install/sd_webui/sd_webui_core.sh" >> "${START_PATH}/term-sd/task/sd_webui_install.sh" # 核心组件
echo "__term_sd_task_sys term_sd_tmp_enable_proxy" >> "${START_PATH}/term-sd/task/sd_webui_install.sh"
# 读取插件安装命令
if [[ ! -z "${SD_WEBUI_INSTALL_EXTENSION_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"安装插件中\"" >> "${START_PATH}/term-sd/task/sd_webui_install.sh"
# 从插件列表读取插件安装命令
for i in ${SD_WEBUI_INSTALL_EXTENSION_LIST}; do
cat "${START_PATH}/term-sd/install/sd_webui/sd_webui_extension.sh" | grep -w ${i} | awk '{sub(" ON "," ") ; sub(" OFF "," ")}1' >> "${START_PATH}/term-sd/task/sd_webui_install.sh" # 插件
done
fi
echo "__term_sd_task_sys term_sd_tmp_disable_proxy" >> "${START_PATH}/term-sd/task/sd_webui_install.sh"
# 读取模型下载命令
if [[ ! -z "${SD_WEBUI_DOWNLOAD_MODEL_LIST}" ]]; then
echo "__term_sd_task_sys term_sd_echo \"下载模型中\"" >> "${START_PATH}/term-sd/task/sd_webui_install.sh"
if is_use_modelscope_src; then
# 读取模型
for i in ${SD_WEBUI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/sd_webui/sd_webui_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/sd_webui_install.sh" # 插件所需的模型
done
# 读取插件的模型
for i in ${SD_WEBUI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/sd_webui/sd_webui_extension_ms_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/sd_webui_install.sh" # 插件所需的模型
done
else
# 恢复代理
echo "__term_sd_task_sys term_sd_tmp_enable_proxy" >> "${START_PATH}/term-sd/task/sd_webui_install.sh"
# 读取模型
for i in ${SD_WEBUI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/sd_webui/sd_webui_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/sd_webui_install.sh" # 插件所需的模型
done
# 读取插件的模型
for i in ${SD_WEBUI_DOWNLOAD_MODEL_LIST}; do
cat "${START_PATH}/term-sd/install/sd_webui/sd_webui_extension_hf_model.sh" | grep -w ${i} >> "${START_PATH}/term-sd/task/sd_webui_install.sh" # 插件所需的模型
done
fi
fi
unset SD_WEBUI_INSTALL_EXTENSION_LIST
unset SD_WEBUI_DOWNLOAD_MODEL_LIST
term_sd_echo "任务队列生成完成"
term_sd_echo "开始安装 Stable-Diffusion-WebUI"
# 执行安装命令
cmd_sum=$(( $(cat "${START_PATH}/term-sd/task/sd_webui_install.sh" | wc -l) + 1 )) # 统计命令行数
for ((cmd_point=1; cmd_point <= cmd_sum; cmd_point++)); do
term_sd_echo "Stable-Diffusion-WebUI 安装进度: [${cmd_point}/${cmd_sum}]"
term_sd_exec_cmd "${START_PATH}/term-sd/task/sd_webui_install.sh" "${cmd_point}"
if [[ ! "$?" == 0 ]]; then
if term_sd_is_use_strict_install_mode; then
term_sd_echo "安装命令执行失败, 终止安装程序, 请检查控制台输出的报错信息"
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_pause
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 安装结果" \
--ok-label "确认" \
--msgbox "Stable-Diffusion-WebUI 安装进程执行失败, 请重试" \
$(get_dialog_size)
return 1
else
term_sd_echo "忽略执行失败的命令"
term_sd_echo "提示: 忽略执行失败的命令可能会导致安装不完整或者缺失文件"
fi
fi
done
term_sd_tmp_enable_proxy # 恢复代理
clean_install_config # 清理安装参数
term_sd_echo "Stable-Diffusion-WebUI 安装结束"
rm -f "${START_PATH}/term-sd/task/sd_webui_install.sh" # 删除任务文件
term_sd_print_line
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 安装结果" \
--ok-label "确认" \
--msgbox "Stable-Diffusion-WebUI 安装结束, 选择确定进入管理界面\n注: 初次启动 Stable-Diffusion-WebUI 时将会进行一次依赖完整性检查, 耗时较久" \
$(get_dialog_size)
sd_webui_manager # 进入管理界面
else
unset SD_WEBUI_INSTALL_EXTENSION_LIST
unset SD_WEBUI_DOWNLOAD_MODEL_LIST
clean_install_config # 清理安装参数
fi
fi
}
# 插件选择
# 将选择的插件保存在 SD_WEBUI_INSTALL_EXTENSION_LIST 全局变量中
sd_webui_extension_install_select() {
SD_WEBUI_INSTALL_EXTENSION_LIST=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 安装" \
--backtitle "Stable-Diffusion-WebUI 插件安装选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要安装的 Stable-Diffusion-WebUI 插件" \
$(get_dialog_size_menu) \
$(cat "${START_PATH}/term-sd/install/sd_webui/dialog_sd_webui_extension.sh") \
3>&1 1>&2 2>&3)
}
# 模型选择
# 将选择的模型保存在 SD_WEBUI_DOWNLOAD_MODEL_LIST 全局变量中
sd_webui_download_model_select() {
local dialog_list_file
local model_list
local sd_webui_model_list_file
local i
# 插件模型列表选择
if is_use_modelscope_src; then
dialog_list_file="sd_webui_extension_ms_model.sh"
sd_webui_model_list_file="dialog_sd_webui_ms_model.sh"
else
dialog_list_file="sd_webui_extension_hf_model.sh"
sd_webui_model_list_file="dialog_sd_webui_hf_model.sh"
fi
term_sd_echo "生成模型选择列表中"
# 查找插件对应模型的编号
for i in ${SD_WEBUI_INSTALL_EXTENSION_LIST}; do
model_list="${model_list} $(cat "${START_PATH}"/term-sd/install/sd_webui/${dialog_list_file} | grep -w ${i} | awk 'NR==1{if ($NF!="") {print $1 " " $(NF-1) " " $NF} }')"
done
# 模型选择(包含基础模型和插件的模型)
SD_WEBUI_DOWNLOAD_MODEL_LIST=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 安装" \
--backtitle "Stable-Diffusion-WebUI 模型下载选项" \
--ok-label "确认" --no-cancel \
--checklist "请选择需要下载的 Stable-Diffusion-WebUI 模型\n注:\n1、模型后面括号内数字为模型的大小\n2、需要根据自己的需求勾选需要下载的模型" \
$(get_dialog_size_menu) \
"_null_" "=====基础模型选择=====" ON \
$(cat "${START_PATH}/term-sd/install/sd_webui/${sd_webui_model_list_file}") \
"_null_" "=====插件模型选择=====" ON \
${model_list} \
3>&1 1>&2 2>&3)
}
# 写入 SD WebUI 配置文件
# 保存在 <SD WebUI Path>/config.json 中
set_sd_webui_normal_config() {
term_sd_echo "写入 Stable-Diffusion-WebUI 默认配置中"
cp -f "${START_PATH}/term-sd/install/sd_webui/sd_webui_config.json" "${SD_WEBUI_ROOT_PATH}"/config.json
}
# SD WebUI 分支选择
# 通过 SD_WEBUI_REPO 全局变量设置 SD WebUI 分支的 Git 链接
# 通过 SD_WEBUI_BRANCH 设置要切换到的 SD WebUI 分支
select_install_sd_webui_branch() {
local dialog_arg
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 安装" \
--backtitle "Stable-Diffusion-WebUI 分支选择选项" \
--ok-label "确认" --no-cancel \
--menu "请选择要安装的 Stable-Diffusion-WebUI 分支, 注:\n1. 推荐使用 AUTOMATIC1111 - Stable-Diffusion-WebUI 分支, 稳定性较高\n2.如果有 FLUX 模型的需求或者更好的显存优化, 可选择 lllyasviel - Stable-Diffusion-WebUI-Forge 分支, 但该分支可能会导致部分插件不兼容\n3. Panchovix - stable-diffusion-webui-reForge 分支基于 lllyasviel - Stable-Diffusion-WebUI-Forge 分支, 使用 Gradio3 前端, 对插件的兼容性好一些\n4、Haoming02 - Stable-Diffusion-WebUI-Forge-Classic 分支基于 lllyasviel - Stable-Diffusion-WebUI-Forge 分支, 更轻量" \
$(get_dialog_size_menu) \
"1" "> AUTOMATIC1111 - Stable-Diffusion-WebUI 主分支" \
"2" "> AUTOMATIC1111 - Stable-Diffusion-WebUI 测试分支" \
"3" "> lllyasviel - Stable-Diffusion-WebUI-Forge 分支" \
"4" "> Panchovix - Stable-Diffusion-WebUI-reForge 主分支" \
"5" "> Panchovix - Stable-Diffusion-WebUI-reForge 测试分支" \
"6" "> Haoming02 - Stable-Diffusion-WebUI-Forge-Classic 分支" \
"7" "> Haoming02 - Stable-Diffusion-WebUI-Forge-Neo 分支" \
"8" "> lshqqytiger - Stable-Diffusion-WebUI-AMDGPU 分支" \
"9" "> vladmandic - SD.NEXT 主分支" \
"10" "> vladmandic - SD.NEXT 测试分支" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
SD_WEBUI_REPO="https://github.com/AUTOMATIC1111/stable-diffusion-webui"
SD_WEBUI_BRANCH="master"
;;
2)
SD_WEBUI_REPO="https://github.com/AUTOMATIC1111/stable-diffusion-webui"
SD_WEBUI_BRANCH="dev"
;;
3)
SD_WEBUI_REPO="https://github.com/lllyasviel/stable-diffusion-webui-forge"
SD_WEBUI_BRANCH="main"
;;
4)
SD_WEBUI_REPO="https://github.com/Panchovix/stable-diffusion-webui-reForge"
SD_WEBUI_BRANCH="main"
;;
5)
SD_WEBUI_REPO="https://github.com/Panchovix/stable-diffusion-webui-reForge"
SD_WEBUI_BRANCH="dev_upstream"
;;
6)
SD_WEBUI_REPO="https://github.com/Haoming02/sd-webui-forge-classic"
SD_WEBUI_BRANCH="classic"
;;
7)
SD_WEBUI_REPO="https://github.com/Haoming02/sd-webui-forge-classic"
SD_WEBUI_BRANCH="neo"
;;
8)
SD_WEBUI_REPO="https://github.com/lshqqytiger/stable-diffusion-webui-amdgpu"
SD_WEBUI_BRANCH="master"
;;
9)
SD_WEBUI_REPO="https://github.com/vladmandic/sdnext"
SD_WEBUI_BRANCH="master"
;;
10)
SD_WEBUI_REPO="https://github.com/vladmandic/sdnext"
SD_WEBUI_BRANCH="dev"
;;
*)
SD_WEBUI_REPO="https://github.com/AUTOMATIC1111/stable-diffusion-webui"
SD_WEBUI_BRANCH="master"
;;
esac
if term_sd_is_debug; then
term_sd_echo "SD WebUI 远程地址: ${SD_WEBUI_REPO}"
term_sd_echo "SD WebUI 分支: ${SD_WEBUI_BRANCH}"
fi
}
# 切换 SD WebUI 的分支
# 使用:
# switch_sd_webui_branch <SD WebUI 的分支>
switch_sd_webui_branch() {
local branch=$@
term_sd_echo "检查 Stable-Diffusion-WebUI 子模块状态"
if [[ ! -z "$(git -C "${SD_WEBUI_ROOT_PATH}" submodule status)" ]]; then # 检测是否有子模块
term_sd_echo "初始化 Git 子模块"
use_submodules="--recurse-submodules"
git -C "${SD_WEBUI_ROOT_PATH}" submodule update --init --recursive || return 1
else
term_sd_echo "禁用 Git 子模块"
use_submodules=""
git -C "${SD_WEBUI_ROOT_PATH}" submodule deinit --all -f || return 1
fi
term_sd_echo "切换 Stable-Diffusion-WebUI 分支至 ${branch}"
git -C "${SD_WEBUI_ROOT_PATH}" checkout "${branch}" ${use_submodules} || return 1
}
# 安装 SD WebUI 的依赖
install_sd_webui_requirement() {
local requirement
if [[ -f "${SD_WEBUI_ROOT_PATH}/requirements_versions.txt" ]]; then # SD WebUI / SD WebUI Forge
requirement="${SD_WEBUI_ROOT_PATH}/requirements_versions.txt"
elif [[ -f "${SD_WEBUI_ROOT_PATH}/requirements.txt" ]]; then # SD.Next
requirement="${SD_WEBUI_ROOT_PATH}/requirements.txt"
else
requirement="${SD_WEBUI_ROOT_PATH}/requirements_versions.txt"
fi
if term_sd_is_debug; then
term_sd_echo "requirement path: ${requirement}"
fi
install_python_package -r "${requirement}"
}
# 安装 SD WEbUI 组件
install_sd_webui_component() {
term_sd_echo "安装 Stable Diffusion WebUI 组件中"
case "${SD_WEBUI_REPO}" in
*stable-diffusion-webui|*stable-diffusion-webui-reForge|*stable-diffusion-webui-amdgpu)
git_clone_repository https://github.com/salesforce/BLIP "${SD_WEBUI_ROOT_PATH}"/repositories BLIP || return 1
git_clone_repository https://github.com/Stability-AI/stablediffusion "${SD_WEBUI_ROOT_PATH}"/repositories stable-diffusion-stability-ai || return 1
git_clone_repository https://github.com/Stability-AI/generative-models "${SD_WEBUI_ROOT_PATH}"/repositories generative-models || return 1
git_clone_repository https://github.com/crowsonkb/k-diffusion "${SD_WEBUI_ROOT_PATH}"/repositories k-diffusion || return 1
git_clone_repository https://github.com/AUTOMATIC1111/stable-diffusion-webui-assets "${SD_WEBUI_ROOT_PATH}"/repositories stable-diffusion-webui-assets || return 1
;;
*automatic)
git_clone_repository https://github.com/salesforce/BLIP "${SD_WEBUI_ROOT_PATH}"/repositories blip || return 1
git_clone_repository https://github.com/Stability-AI/stablediffusion "${SD_WEBUI_ROOT_PATH}"/repositories stable-diffusion-stability-ai || return 1
git_clone_repository https://github.com/Stability-AI/generative-models "${SD_WEBUI_ROOT_PATH}"/repositories generative-models || return 1
git_clone_repository https://github.com/crowsonkb/k-diffusion "${SD_WEBUI_ROOT_PATH}"/repositories k-diffusion || return 1
git_clone_repository https://github.com/AUTOMATIC1111/stable-diffusion-webui-assets "${SD_WEBUI_ROOT_PATH}"/repositories stable-diffusion-webui-assets || return 1
;;
*stable-diffusion-webui-forge)
git_clone_repository https://github.com/salesforce/BLIP "${SD_WEBUI_ROOT_PATH}"/repositories BLIP || return 1
git_clone_repository https://github.com/Stability-AI/stablediffusion "${SD_WEBUI_ROOT_PATH}"/repositories stable-diffusion-stability-ai || return 1
git_clone_repository https://github.com/Stability-AI/generative-models "${SD_WEBUI_ROOT_PATH}"/repositories generative-models || return 1
git_clone_repository https://github.com/crowsonkb/k-diffusion "${SD_WEBUI_ROOT_PATH}"/repositories k-diffusion || return 1
git_clone_repository https://github.com/lllyasviel/huggingface_guess "${SD_WEBUI_ROOT_PATH}"/repositories huggingface_guess || return 1
git_clone_repository https://github.com/lllyasviel/google_blockly_prototypes "${SD_WEBUI_ROOT_PATH}"/repositories google_blockly_prototypes || return 1
;;
*sd-webui-forge-classic)
true
;;
esac
term_sd_echo "安装 Stable Diffusion WebUI 组件完成"
}
|
2301_81996401/term-sd
|
modules/install_sd_webui.sh
|
Shell
|
agpl-3.0
| 18,941
|
#!/bin/bash
# InvokeAI 自定义节点管理器
# 管理 <InvokeAI Path>/invokeai/nodes 文件夹下的自定义节点
invokeai_custom_node_manager() {
local dialog_arg
if [[ ! -d "${INVOKEAI_ROOT_PATH}"/invokeai/nodes ]]; then
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点管理选项" \
--ok-label "确认" \
--msgbox "找不到 InvokeAI 自定义节点目录, 需启动一次生成 InvokeAI 以生成 InvokeAI 自定义目录" \
$(get_dialog_size)
return 1
fi
while true; do
cd "${INVOKEAI_ROOT_PATH}"/invokeai/nodes # 回到最初路径
dialog_arg=$(dialog --erase-on-exit --notags \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择 InvokeAI 自定义节点管理选项的功能" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 安装自定义节点" \
"2" "> 管理自定义节点" \
"3" "> 更新全部自定义节点" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
# 选择安装
invokeai_custom_node_install
;;
2)
# 选择管理
invokeai_custom_node_list
;;
3)
# 选择更新全部自定义节点
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点管理" \
--yes-label "是" --no-label "否" \
--yesno "是否更新所有 InvokeAI 自定义节点 ?" \
$(get_dialog_size)); then
update_all_extension
fi
;;
*)
break
;;
esac
done
}
# InvokeAI 自定义节点安装
invokeai_custom_node_install() {
local repo_url
local custom_node_name
repo_url=$(dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点安装选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "输入自定义节点的 Github 地址或其他下载地址" \
$(get_dialog_size) \
3>&1 1>&2 2>&3)
if [[ ! -z "${repo_url}" ]]; then
custom_node_name=$(basename "${repo_url}" | awk -F '.git' '{print $1}')
term_sd_echo "安装 ${custom_node_name} 自定义节点中"
if ! term_sd_is_git_repository_exist "${repo_url}"; then # 检查待安装的自定义节点是否存在于自定义节点文件夹中
term_sd_try git clone --recurse-submodules "${repo_url}" "${INVOKEAI_ROOT_PATH}/invokeai/nodes/${custom_node_name}"
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点安装结果" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点安装成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点安装结果" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点安装失败" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点安装结果" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点已存在" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点管理选项" \
--ok-label "确认" \
--msgbox "输入的 InvokeAI 自定义节点安装地址为空" \
$(get_dialog_size)
fi
}
# 自定义节点浏览器
# 将列出 <InvokeAI Path>/invokeai/nodes 中所有的自定义节点的文件夹
invokeai_custom_node_list() {
local custom_node_name
while true; do
cd "${INVOKEAI_ROOT_PATH}"/invokeai/nodes # 回到最初路径
get_dir_folder_list # 获取当前目录下的所有文件夹
if term_sd_is_bash_ver_lower; then # Bash 版本低于 4 时使用旧版列表显示方案
custom_node_name=$(dialog --erase-on-exit \
--ok-label "确认" --cancel-label "取消" \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点列表" \
--menu "使用上下键选择要操作的自定义节点并回车确认" \
$(get_dialog_size_menu) \
"-->返回<--" "<---------" \
"${LOCAL_DIR_LIST}" \
3>&1 1>&2 2>&3)
else
custom_node_name=$(dialog --erase-on-exit \
--ok-label "确认" --cancel-label "取消" \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点列表" \
--menu "使用上下键选择要操作的自定义节点并回车确认" \
$(get_dialog_size_menu) \
"-->返回<--" "<---------" \
"${LOCAL_DIR_LIST[@]}" \
3>&1 1>&2 2>&3)
fi
if [[ "$?" == 0 ]]; then
if [[ "${custom_node_name}" == "-->返回<--" ]]; then
break
elif [[ -d "${custom_node_name}" ]]; then # 选择文件夹
cd "${custom_node_name}"
invokeai_custom_node_interface "${custom_node_name}"
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点管理" \
--ok-label "确认" \
--msgbox "当前的选择非 InvokeAI 自定义节点, 请重新选择" \
$(get_dialog_size)
fi
else
break
fi
done
unset LOCAL_DIR_LIST
}
# InvokeAI 自定义节点管理
# 使用:
# invokeai_custom_node_interface <自定义节点的文件夹名>
invokeai_custom_node_interface() {
local dialog_arg
local custom_node_name=$@
local custom_node_folder=$@
local dialog_buttom
local status_display
local custom_node_status
while true; do
if [[ ! -f "__init__.py" ]]; then
custom_node_status=0
status_display="已禁用"
dialog_buttom="启用"
else
custom_node_status=1
status_display="已启用"
dialog_buttom="禁用"
fi
dialog_arg=$(dialog --erase-on-exit --notags \
--title "InvokeAI 选项" \
--backtitle "InvokeAI 自定义节点管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择对 ${custom_node_name} 自定义节点的管理功能\n当前更新源: $(git_remote_display)\n当前分支: $(git_branch_display)\n当前状态: ${status_display}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 更新" \
"2" "> 修复更新" \
"3" "> 版本切换" \
"4" "> 更新源切换" \
"5" "> ${dialog_buttom}自定义节点" \
"6" "> 卸载" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
if is_git_repo; then
term_sd_echo "更新 ${custom_node_name} 自定义节点中"
# 恢复文件
if [[ "${custom_node_status}" == 0 ]] && [[ -f "__init__.py.bak" ]]; then
mv -f "__init__.py.bak" "__init__.py" &> /dev/null
fi
git_pull_repository
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点更新结果" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点更新成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点更新结果" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点更新失败" \
$(get_dialog_size)
fi
# 保持自定义节点启用或者禁用状态
if [[ "${custom_node_status}" == 0 ]] && [[ -f "__init__.py" ]]; then
mv -f "__init__.py" "__init__.py.bak" &> /dev/null
fi
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点更新结果" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点非 Git 安装, 无法更新" \
$(get_dialog_size)
fi
;;
2)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点修复更新" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 ${custom_node_name} 自定义节点更新 ?" \
$(get_dialog_size)); then
# 恢复文件
if [[ "${custom_node_status}" == 0 ]] && [[ -f "__init__.py.bak" ]]; then
mv -f "__init__.py.bak" "__init__.py" &> /dev/null
fi
git_fix_pointer_offset
# 保持自定义节点启用或者禁用状态
if [[ "${custom_node_status}" == 0 ]] && [[ -f "__init__.py" ]]; then
mv -f "__init__.py" "__init__.py.bak" &> /dev/null
fi
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点修复更新" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点修复更新完成" \
$(get_dialog_size)
else
term_sd_echo "取消修复 ${custom_node_name} 自定义节点的更新"
fi
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点修复更新" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点非 Git 安装, 无法修复更新" \
$(get_dialog_size)
fi
;;
3)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点版本切换" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 ${custom_node_name} 自定义节点版本 ?" \
$(get_dialog_size)); then
git_ver_switch
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点版本切换" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点版本切换完成, 当前版本为: $(git_branch_display)" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI自定义节点版本切换" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点非 Git 安装, 无法进行版本切换" \
$(get_dialog_size)
fi
;;
4)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点更新源切换" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 ${custom_node_name} 自定义节点更新源 ?" \
$(get_dialog_size)); then
git_remote_url_select_single
fi
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点更新源切换" \
--ok-label "确认" \
--msgbox "${custom_node_name} 自定义节点非 Git 安装, 无法进行更新源切换" \
$(get_dialog_size)
fi
;;
5)
if [[ "${custom_node_status}" == 0 ]]; then
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点更新源切换" \
--yes-label "是" --no-label "否" \
--yesno "是否启用 ${custom_node_name} 自定义节点 ?" \
$(get_dialog_size)); then
mv -f "__init__.py.bak" "__init__.py" &> /dev/null
else
continue
fi
else
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点更新源切换" \
--yes-label "是" --no-label "否" \
--yesno "是否禁用 ${custom_node_name} 自定义节点 ?" \
$(get_dialog_size)); then
mv -f "__init__.py" "__init__.py.bak" &> /dev/null
else
continue
fi
fi
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点删除选项" \
--ok-label "确认" \
--msgbox "${dialog_buttom} ${custom_node_name} 自定义节点成功" \
$(get_dialog_size)
;;
6)
if (dialog --erase-on-exit \
--title "InvokeAI 选项" \
--backtitle "InvokeAI 自定义节点删除选项" \
--yes-label "是" --no-label "否" \
--yesno "是否删除 ${custom_node_name} 自定义节点 ?" \
$(get_dialog_size)); then
term_sd_echo "请再次确认是否删除 ${custom_node_name} 自定义节点 (yes/no) ?"
term_sd_echo "警告: 该操作将永久删除 ${custom_node_name} 自定义节点"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
yes|y|YES|Y)
term_sd_echo "删除 ${custom_node_name} 自定义节点中"
cd ..
rm -rf "${custom_node_folder}"
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义节点删除选项" \
--ok-label "确认" \
--msgbox "删除 ${custom_node_name} 自定义节点完成" \
$(get_dialog_size)
break
;;
*)
term_sd_echo "取消删除 ${custom_node_name} 自定义节点操作"
;;
esac
fi
;;
*)
break
;;
esac
done
}
|
2301_81996401/term-sd
|
modules/invokeai_custom_node_manager.sh
|
Shell
|
agpl-3.0
| 17,192
|
#!/bin/bash
# InvokeAI 启动界面
# 参考: https://invoke-ai.github.io/InvokeAI/features/UTILITIES
invokeai_launch() {
local dialog_arg
local launch_args
add_invokeai_normal_launch_args
while true; do
launch_args="invokeai-web $(cat "${START_PATH}"/term-sd/config/invokeai-launch.conf)"
dialog_arg=$(dialog --erase-on-exit --notags \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择 InvokeAI 启动参数\n当前自定义启动参数: ${launch_args}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 配置预设启动参数" \
"3" "> 修改自定义启动参数" \
"4" "> 重置启动参数" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
term_sd_launch
;;
2)
invokeai_launch_args_setting
;;
3)
invokeai_manual_launch
;;
4)
restore_invokeai_launch_args
;;
*)
break
;;
esac
done
}
# 启动参数预设选择
# 启动参数保存在 <Start Path>/term-sd/config/invokeai-launch.conf
invokeai_launch_args_setting() {
local dialog_arg
local arg
local launch_args
local i
dialog_arg=$(dialog --erase-on-exit --notags \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--checklist "请选择 InvokeAI 启动参数, 确认之后将覆盖原有启动参数配置\n注: InvokeAI 4.x 已移除该列表中的启动参数, 若使用将导致 InvokeAI 报错导致无法启动, 需使用修改自定义启动参数功能将所有启动参数清除" \
$(get_dialog_size_menu) \
"1" "(host) 开放远程连接" OFF \
"2" "(no-esrgan) 禁用 ESRGAN 进行画面修复" OFF \
"3" "(no-internet_available) 启用离线模式" OFF \
"4" "(log_tokenization) 启用详细日志显示" OFF \
"5" "(no-patchmatch) 禁用图片修复模块" OFF \
"6" "(ignore_missing_core_models) 忽略下载核心模型" OFF \
"7" "(log_format plain) 使用纯文本格式日志" OFF \
"8" "(log_format color) 使用彩色格式日志" OFF \
"9" "(log_format syslog) 使用系统格式日志" OFF \
"10" "(log_format legacy) 使用传统格式日志" OFF \
"11" "(log_sql) 显示数据库查新日志" OFF \
"12" "(dev_reload) 启用开发者模式" OFF \
"13" "(log_memory_usage) 显示详细内存使用日志" OFF \
"14" "(always_use_cpu) 强制使用 CPU" OFF \
"15" "(tiled_decode) 启用分块 VAE 解码, 降低显存占用" OFF \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
for i in ${dialog_arg}; do
case "${i}" in
1)
arg="--host 0.0.0.0"
;;
2)
arg="--no-esrgan"
;;
3)
arg="--no-internet_available"
;;
4)
arg="--log_tokenization"
;;
5)
arg="--no-patchmatch"
;;
6)
arg="--ignore_missing_core_models"
;;
7)
arg="--log_format plain"
;;
8)
arg="--log_format color"
;;
9)
arg="--log_format syslog"
;;
10)
arg="--log_format legacy"
;;
11)
arg="--log_sql"
;;
12)
arg="--dev_reload"
;;
13)
arg="--log_memory_usage"
;;
14)
arg="--always_use_cpu"
;;
15)
arg="--tiled_decode"
;;
esac
launch_args="${arg} ${launch_args}"
done
term_sd_echo "设置 InvokeAI 启动参数: ${launch_args}"
echo "${launch_args}" > "${START_PATH}"/term-sd/config/invokeai-launch.conf
else
term_sd_echo "取消设置 InvokeAI 启动参数"
fi
}
# 启动参数修改
# 修改参数前将从 <Start Path>/term-sd/config/invokeai-launch.conf 中读取启动参数
# 可在原来的基础上修改
invokeai_manual_launch() {
local dialog_arg
local launch_args
launch_args=$(cat "${START_PATH}"/term-sd/config/invokeai-launch.conf)
dialog_arg=$(dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 自定义启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "请输入 InvokeAI 启动参数" \
$(get_dialog_size) \
"${launch_args}" \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
term_sd_echo "设置 InvokeAI 启动参数: ${dialog_arg}"
echo "${dialog_arg}" > "${START_PATH}"/term-sd/config/invokeai-launch.conf
else
term_sd_echo "取消 InvokeAI 启动参数修改"
fi
}
# 添加默认启动参数配置
add_invokeai_normal_launch_args() {
if [[ ! -f "${START_PATH}/term-sd/config/invokeai-launch.conf" ]]; then # 找不到启动配置时默认生成一个
echo "" > "${START_PATH}"/term-sd/config/invokeai-launch.conf
fi
}
# 重置启动参数
restore_invokeai_launch_args() {
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 重置启动参数选项选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重置 InvokeAI 启动参数 ?" \
$(get_dialog_size)); then
term_sd_echo "重置启动参数"
rm -f "${START_PATH}"/term-sd/config/invokeai-launch.conf
add_invokeai_normal_launch_args
else
term_sd_echo "取消重置操作"
fi
}
# 启动 InvokeAI
# 使用:
# launch_invokeai_web <启动参数>
launch_invokeai_web() {
term_sd_python "${START_PATH}/term-sd/python_modules/launch_invokeai.py" "$@"
}
|
2301_81996401/term-sd
|
modules/invokeai_launch.sh
|
Shell
|
agpl-3.0
| 6,543
|
#!/bin/bash
# InvokeAI 管理
# 设置 INVOKEAI_ROOT 环境变量指定 InvokeAI 存放数据文件路径
invokeai_manager() {
local dialog_arg
export INVOKEAI_ROOT="${INVOKEAI_ROOT_PATH}/invokeai"
cd "${START_PATH}" # 回到最初路径
exit_venv # 确保进行下一步操作前已退出其他虚拟环境
if [[ -d "${INVOKEAI_ROOT_PATH}" ]]; then # 找到 InvokeAI 文件夹
cd "${INVOKEAI_ROOT_PATH}"
enter_venv
if is_invokeai_installed; then # 检测 InvokeAI 是否安装
while true; do
cd "${INVOKEAI_ROOT_PATH}"
dialog_arg=$(dialog --erase-on-exit --notags \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择 InvokeAI 管理选项的功能\n当前 InvokeAI 版本: $(get_invokeai_version)" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 更新" \
"3" "> 自定义节点管理" \
"4" "> 切换版本" \
"5" "> 更新依赖" \
"6" "> Python 软件包安装 / 重装 / 卸载" \
"7" "> 依赖库版本管理" \
"8" "> 重新安装 PyTorch" \
"9" "> 切换 PyTorch 类型" \
"10" "> 修复虚拟环境" \
"11" "> 重新构建虚拟环境" \
"12" "> 重新安装" \
"13" "> 卸载" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
invokeai_launch
;;
2)
# 更新前的准备
download_mirror_select # 下载镜像源选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否更新 InvokeAI ?"; then
term_sd_echo "更新 InvokeAI 中"
term_sd_tmp_disable_proxy # 临时取消代理,避免一些不必要的网络减速
update_invokeai_version
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 更新结果" \
--ok-label "确认" \
--msgbox "InvokeAI 更新成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 更新结果" \
--ok-label "确认" \
--msgbox "InvokeAI 更新失败" \
$(get_dialog_size)
fi
term_sd_tmp_enable_proxy # 恢复原有的代理
fi
clean_install_config # 清理安装参数
;;
3)
invokeai_custom_node_manager
;;
4)
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 版本切换选项" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 InvokeAI 版本 ?" \
$(get_dialog_size)); then
switch_invokeai_version
fi
;;
5)
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 依赖更新选项" \
--yes-label "是" --no-label "否" \
--yesno "是否更新 InvokeAI 的依赖 ?" \
$(get_dialog_size)); then
invokeai_update_depend
fi
;;
6)
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 的 Python 软件包安装 / 重装 / 卸载选项" \
--yes-label "是" --no-label "否" \
--yesno "是否进入 Python 软件包安装 / 重装 / 卸载选项 ?" \
$(get_dialog_size)); then
python_package_manager
fi
;;
7)
python_package_ver_backup_manager
enter_venv
;;
8)
pytorch_reinstall
enter_venv
;;
9)
switch_pytorch_type_for_invokeai
;;
10)
if is_use_venv; then
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 虚拟环境修复选项" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 InvokeAI 的虚拟环境 ?" \
$(get_dialog_size)); then
fix_venv
enter_venv
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 虚拟环境修复选项" \
--ok-label "确认" \
--msgbox "InvokeAI 虚拟环境修复完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 虚拟环境修复选项" \
--ok-label "确认" \
--msgbox "虚拟环境功能已禁用, 无法使用该功能" \
$(get_dialog_size)
fi
;;
11)
if is_use_venv; then
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 虚拟环境重建选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重建 InvokeAI 的虚拟环境 ?" \
$(get_dialog_size)); then
invokeai_venv_rebuild
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 虚拟环境重建选项" \
--ok-label "确认" \
--msgbox "InvokeAI 虚拟环境重建完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 虚拟环境重建选项" \
--ok-label "确认" \
--msgbox "虚拟环境功能已禁用, 无法使用该功能" \
$(get_dialog_size)
fi
;;
12)
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 重新安装选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重新安装 InvokeAI ?" \
$(get_dialog_size)); then
cd "${START_PATH}"
rm -f "${START_PATH}/term-sd/task/invokeai_install.sh"
exit_venv
install_invokeai
break
fi
;;
13)
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 删除选项" \
--yes-label "是" --no-label "否" \
--yesno "是否删除 InvokeAI ?" \
$(get_dialog_size)); then
term_sd_echo "请再次确认是否删除 InvokeAI (yes/no) ?"
term_sd_echo "警告: 该操作将永久删除 InvokeAI"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
yes|y|YES|Y)
exit_venv
term_sd_echo "删除 InvokeAI 中"
cd ..
rm -rf "${INVOKEAI_ROOT_PATH}"
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 删除选项" \
--ok-label "确认" \
--msgbox "删除 InvokeAI 完成" \
$(get_dialog_size)
break
;;
*)
term_sd_echo "取消删除 InvokeAI 操作"
;;
esac
fi
;;
*)
break
;;
esac
done
else
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 安装选项" \
--yes-label "是" --no-label "否" \
--yesno "检测到当前未安装 InvokeAI, 是否进行安装 ?" \
$(get_dialog_size)); then
cd "${INVOKEAI_PARENT_PATH}"
rm -f "${START_PATH}/term-sd/task/invokeai_install.sh"
install_invokeai
fi
fi
else
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 安装选项" \
--yes-label "是" --no-label "否" \
--yesno "检测到当前未安装 InvokeAI, 是否进行安装 ?" \
$(get_dialog_size)); then
rm -f "${START_PATH}/term-sd/task/invokeai_install.sh"
install_invokeai
fi
fi
unset INVOKEAI_ROOT
}
# InvokeAI 更新依赖
invokeai_update_depend() {
# 更新前的准备
download_mirror_select # 下载镜像源选择
pip_install_mode_select upgrade # 安装方式选择
if term_sd_install_confirm "是否更新 InvokeAI 依赖 ?"; then
term_sd_print_line "InvokeAI 依赖更新"
term_sd_echo "更新 InvokeAI 依赖中"
term_sd_tmp_disable_proxy
enter_venv
get_python_env_pkg | awk -F '==' '{print $1}' > requirements.txt # 生成一个更新列表
python_package_update "requirements.txt"
rm -f requirements.txt
exit_venv
term_sd_tmp_enable_proxy
term_sd_echo "更新 InvokeAI 依赖结束"
term_sd_pause
fi
clean_install_config # 清理安装参数
}
# 检测 InvokeAI 是否安装
is_invokeai_installed() {
local status
status=$(term_sd_python "${START_PATH}/term-sd/python_modules/check_invokeai_installed.py")
if [[ "${status}" == "True" ]]; then
return 0
else
return 1
fi
}
# 切换 InvokeAI 版本
switch_invokeai_version() {
local dialog_arg
local invokeai_ver
local device_type
download_mirror_select # 下载镜像源选择
pip_install_mode_select # 安装方式选择
term_sd_echo "获取原 PyTorch 类型"
device_type=$(term_sd_python "${START_PATH}/term-sd/python_modules/get_pytorch_type.py")
term_sd_echo "获取 InvokeAI 版本列表中"
dialog_arg=$(dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 版本切换选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择要切换的 InvokeAI 版本\n当前 InvokeAI 版本: $(get_invokeai_version)" \
$(get_dialog_size_menu) \
"-->返回<--" "<-------------------" \
$(term_sd_pip index versions invokeai --pre |\
grep -oP "Available versions: \K.*" |\
awk -F ',' '{ for (i = 1; i <= NF; i++) {print $i " <-------------------"} }' \
) \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
if [[ ! "${dialog_arg}" == "-->返回<--" ]]; then
invokeai_ver=$dialog_arg
term_sd_echo "当前选择的 InvokeAI 版本: ${invokeai_ver}"
term_sd_echo "切换 InvokeAI 版本中"
update_or_switch_invokeai_version_process "${device_type}" "${invokeai_ver}"
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 版本切换选项" \
--ok-label "确认" \
--msgbox "切换 InvokeAI 版本成功, 当前版本为: ${invokeai_ver}" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 版本切换选项" \
--ok-label "确认" \
--msgbox "切换 InvokeAI 版本失败" \
$(get_dialog_size)
fi
else
term_sd_echo "取消切换版本"
fi
else
term_sd_echo "取消切换版本"
fi
clean_install_config # 清理安装参数
}
# 更新 InvokeAI
update_invokeai_version() {
local device_type
term_sd_echo "获取原 PyTorch 类型"
device_type=$(term_sd_python "${START_PATH}/term-sd/python_modules/get_pytorch_type.py")
term_sd_echo "更新 InvokeAI 中"
update_or_switch_invokeai_version_process "${device_type}" "latest"
}
# 获取 InvokeAI 版本
get_invokeai_version() {
local status
status=$(term_sd_python "${START_PATH}/term-sd/python_modules/get_invokeai_version.py")
if [[ "${status}" == "None" ]]; then
echo "无"
else
echo "${status}"
fi
}
# 获取 InvokeAI 当前版本对应的 PyTorch 所需的PyTorch镜像源类型
# 使用:
# get_pytorch_mirror_type_for_invokeai <显卡类型>
# 可用的显卡类型: cuda, rocm, xpu, cpu
# 返回: PyTorch 镜像源类型
get_pytorch_mirror_type_for_invokeai() {
local status
local device_type=$@
status=$(term_sd_python "${START_PATH}/term-sd/python_modules/get_pytorch_mirror_type.py" --device-type "${device_type}")
echo "${status}"
}
# 配置安装 InvokeAI 所需的 PyTorch 安装信息
# 使用:
# set_pytorch_install_config_for_invokeai <显卡类型>
# 设置 PYTORCH_TYPE, INSTALL_PYTORCH_VERSION, INSTALL_XFORMERS_VERSION 全局变量进行 PyTorch 安装信息配置
# 使用时需确保 InvokeAI 核心包已被安装
set_pytorch_install_config_for_invokeai() {
local device_type=$@
local pytorch_ver
local xformers_ver
term_sd_echo "配置 InvokeAI 所需 PyTorch 的安装信息"
PYTORCH_TYPE=$(get_pytorch_mirror_type_for_invokeai "${device_type}")
pytorch_ver=$(term_sd_python "${START_PATH}/term-sd/python_modules/get_invokeai_require_pytorch.py")
xformers_ver=$(term_sd_python "${START_PATH}/term-sd/python_modules/get_invokeai_require_xformers.py")
case "${PYTORCH_TYPE}" in
cpu|xpu|ipex_legacy_arc|rocm62|other)
INSTALL_PYTORCH_VERSION=$pytorch_ver
;;
*)
INSTALL_PYTORCH_VERSION="${pytorch_ver} ${xformers_ver}" # 合并依赖需求
;;
esac
if term_sd_is_debug; then
term_sd_echo "PYTORCH_TYPE: ${PYTORCH_TYPE}"
term_sd_echo "pytorch_ver: ${pytorch_ver}"
term_sd_echo "xformers_ver: ${xformers_ver}"
term_sd_echo "INSTALL_PYTORCH_VERSION: ${INSTALL_PYTORCH_VERSION}"
fi
term_sd_echo "InvokeAI 所需 PyTorch 的安装信息配置完成"
}
# 同步 InvokeAI 组件
# 使用:
# sync_invokeai_component <显卡类型> <可选参数: force_reinstall (用于强制切换 PyTorch 版本)>
sync_invokeai_component() {
local invokeai_package_ver
local device_type=$1
local force_reinstall_pytorch=$2
invokeai_package_ver=$(get_invokeai_version)
[[ "${invokeai_package_ver}" == "无" ]] && invokeai_package_ver="invokeai"
term_sd_echo "同步 InvokeAI 组件中"
set_pytorch_install_config_for_invokeai "${device_type}" # 配置 PyTorch 安装信息
term_sd_echo "同步 PyTorch 组件中"
if [[ "${force_reinstall_pytorch}" == "force_reinstall" ]]; then
PIP_FORCE_REINSTALL_ARG="--force-reinstall" process_pytorch || return 1 # 安装 PyTorch
else
process_pytorch || return 1 # 安装 PyTorch
fi
term_sd_echo "同步 InvokeAI 其余组件中"
install_python_package "invokeai==${invokeai_package_ver}" || return 1 # 安装 InvokeAI 依赖
term_sd_echo "同步 InvokeAI 组件完成"
}
# 安装 InvokeAI 处理
# 使用:
# install_invokeai_process <显卡类型>
install_invokeai_process() {
local device_type=$@
install_python_package invokeai --no-deps || return 1
sync_invokeai_component "${device_type}" || return 1
}
# 更新 / 切换 InvokeAI 版本处理
# 使用:
# switch_invokeai_version_process <显卡类型> <InvokeAI 版本> <可选参数: force_reinstall (用于强制切换 PyTorch 版本)>
# 当 <InvokeAI 版本> 指定为 latest 时, 则更新 InvokeAI 到最新版本
# 否则切换到指定的 InvokeAI 版本
update_or_switch_invokeai_version_process() {
local device_type=$1
local invokeai_version=$2
local force_reinstall_pytorch=$3
local current_version
current_version=$(get_invokeai_version)
[[ "${current_version}" == "无" ]] && current_version="5.0.2"
if [[ "${invokeai_version}" == "latest" ]]; then
term_sd_echo "更新 InvokeAI 内核中"
install_python_package invokeai --no-deps --upgrade
else
term_sd_echo "切换 InvokeAI 内核版本到 ${invokeai_version} 中"
install_python_package "invokeai==${invokeai_version}" --no-deps
fi
if [[ "$?" == 0 ]]; then
# 内核更新成功时再同步组件版本
term_sd_echo "切换 InvokeAI 内核版本完成, 开始同步组件版本中"
if sync_invokeai_component "${device_type}" "${force_reinstall_pytorch}"; then
term_sd_echo "InvokeAI 版本切换成功"
return 0
else
term_sd_echo "InvokeAI 组件同步失败, 回退 InvokeAI 版本中"
install_python_package "invokeai==${current_version}" --no-deps
term_sd_echo "回退 InvokeAI 版本结束"
return 1
fi
else
term_sd_echo "InvokeAI 内核版本切换失败"
return 1
fi
}
# 切换 InvokeAI 环境的 PyTorch 类型
switch_pytorch_type_for_invokeai() {
local current_version
if (dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 环境 PyTorch 类型切换选项" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 PyTorch 类型 ?" \
$(get_dialog_size)); then
pytorch_type_select # 选择 PyTorch 类型
download_mirror_select # 下载镜像源选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否切换 PyTorch 类型 ?"; then
term_sd_echo "开始切换 PyTorch 类型"
current_version=$(get_invokeai_version)
[[ "${current_version}" == "无" ]] && current_version="5.0.2"
update_or_switch_invokeai_version_process "${PYTORCH_TYPE}" "${current_version}" "force_reinstall"
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 环境 PyTorch 类型切换选项" \
--ok-label "确认" \
--msgbox "切换 PyTorch 类型成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "InvokeAI 管理" \
--backtitle "InvokeAI 环境 PyTorch 类型切换选项" \
--ok-label "确认" \
--msgbox "切换 PyTorch 类型失败" \
$(get_dialog_size)
fi
else
term_sd_echo "取消切换 PyTorch 类型"
fi
clean_install_config # 清理安装参数
else
term_sd_echo "取消切换 PyTorch 类型"
fi
}
|
2301_81996401/term-sd
|
modules/invokeai_manager.sh
|
Shell
|
agpl-3.0
| 22,170
|
#!/bin/bash
# kohya_ss 启动参数设置
# 启动参数将保存在 <Start Path>/term-sd/config/kohya_ss-launch.conf
kohya_ss_launch_args_setting() {
local arg
local dialog_arg
local launch_args
local i
dialog_arg=$(dialog --erase-on-exit --notags \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--checklist "请选择 kohya_ss 启动参数, 确认之后将覆盖原有启动参数配置" \
$(get_dialog_size_menu) \
"1" "(listen) 开放远程连接" OFF \
"2" "(inbrowser) 启动 WebUI 完成后自动启动浏览器" OFF \
"3" "(share) 启用 Gradio 共享" OFF \
"4" "(language zh-CN) 启用中文界面" OFF \
"5" "(headless) 禁用文件浏览按钮" OFF \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
for i in ${dialog_arg}; do
case "${i}" in
1)
arg="--listen 0.0.0.0"
;;
2)
arg="--inbrowser"
;;
3)
arg="--share"
;;
4)
arg="--language zh-CN"
;;
5)
arg="--headless"
;;
esac
launch_args="${arg} ${launch_args}"
done
# 生成启动脚本
term_sd_echo "设置 kohya_ss 启动参数: ${launch_args}"
echo "kohya_gui.py ${launch_args}" > "${START_PATH}"/term-sd/config/kohya_ss-launch.conf
else
term_sd_echo "取消设置 kohya_ss 启动参数"
fi
}
# kohya_ss启动界面
kohya_ss_launch() {
local dialog_arg
local launch_args
add_kohya_ss_normal_launch_args
while true; do
launch_args=$(cat "${START_PATH}"/term-sd/config/kohya_ss-launch.conf)
if is_use_venv; then
launch_args="python ${launch_args}"
else
launch_args="${TERM_SD_PYTHON_PATH} ${launch_args}"
fi
dialog_arg=$(dialog --erase-on-exit --notags \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 启动选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择启动 kohya_ss / 修改 kohya_ss 启动参数\n当前启动参数: ${launch_args}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 配置预设启动参数" \
"3" "> 修改自定义启动参数" \
"4" "> 重置启动参数" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
term_sd_launch
;;
2)
kohya_ss_launch_args_setting
;;
3)
kohya_ss_launch_args_revise
;;
4)
restore_kohya_ss_launch_args
;;
*)
break
;;
esac
done
}
# kohya_ss 启动参数修改
# 输入前将从 <Start Path>/term-sd/config/kohya_ss-launch.conf 读取启动参数
# 可在原来的基础上修改
kohya_ss_launch_args_revise() {
local dialog_arg
local launch_args
launch_args=$(cat "${START_PATH}"/term-sd/config/kohya_ss-launch.conf | awk '{sub("kohya_gui.py ","")}1')
dialog_arg=$(dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 自定义启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "请输入 kohya_ss 启动参数" \
$(get_dialog_size) \
"${launch_args}" \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
term_sd_echo "设置 kohya_ss 启动参数: ${dialog_arg}"
echo "kohya_gui.py ${dialog_arg}" > "${START_PATH}"/term-sd/config/kohya_ss-launch.conf
else
term_sd_echo "取消修改 kohya_ss 启动参数"
fi
}
# 添加默认启动参数配置
add_kohya_ss_normal_launch_args() {
if [[ ! -f "${START_PATH}/term-sd/config/kohya_ss-launch.conf" ]]; then # 找不到启动配置时默认生成一个
echo "kohya_gui.py --inbrowser --language zh-CN" > "${START_PATH}"/term-sd/config/kohya_ss-launch.conf
fi
}
# 重置启动参数
restore_kohya_ss_launch_args() {
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 重置启动参数选项选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重置 kohya_ss 启动参数 ?" \
$(get_dialog_size)); then
term_sd_echo "重置 kohya_ss 启动参数"
rm -f "${START_PATH}"/term-sd/config/kohya_ss-launch.conf
add_kohya_ss_normal_launch_args
else
term_sd_echo "取消重置 kohya_ss 启动参数操作"
fi
}
|
2301_81996401/term-sd
|
modules/kohya_ss_launch.sh
|
Shell
|
agpl-3.0
| 4,904
|
#!/bin/bash
# kohya_ss 管理界面
kohya_ss_manager() {
local dialog_arg
cd "${START_PATH}" # 回到最初路径
exit_venv # 确保进行下一步操作前已退出其他虚拟环境
if [[ -d "${KOHYA_SS_ROOT_PATH}" ]] && ! term_sd_is_dir_empty "${KOHYA_SS_ROOT_PATH}"; then
while true; do
cd "${KOHYA_SS_ROOT_PATH}"
dialog_arg=$(dialog --erase-on-exit --notags \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 管理选项" \
--ok-label "确认" \
--cancel-label "取消" \
--menu "请选择 kohya_ss 管理选项的功能\n当前更新源: $(git_remote_display)\n当前分支: $(git_branch_display)" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 更新" \
"3" "> 修复更新" \
"4" "> 切换版本" \
"5" "> 更新源替换" \
"6" "> 更新依赖" \
"7" "> Python 软件包安装 / 重装 / 卸载" \
"8" "> 依赖库版本管理" \
"9" "> 重新安装 PyTorch" \
"10" "> 修复虚拟环境" \
"11" "> 重新构建虚拟环境" \
"12" "> 重新安装后端组件" \
"13" "> 重新安装" \
"14" "> 卸载" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
kohya_ss_launch
;;
2)
if is_git_repo; then
term_sd_echo "更新 kohya_ss 中"
git_pull_repository
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 更新结果" \
--ok-label "确认" \
--msgbox "kohya_ss 更新成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 更新结果" \
--ok-label "确认" \
--msgbox "kohya_ss 更新失败" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 更新结果" \
--ok-label "确认" \
--msgbox "kohya_ss 非 Git 安装, 无法更新" \
$(get_dialog_size)
fi
;;
3)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 更新修复选项" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 kohya_ss 更新 ?" \
$(get_dialog_size)); then
git_fix_pointer_offset
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 更新修复选项" \
--ok-label "确认" \
--msgbox "kohya_ss 修复更新完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 更新修复选项" \
--ok-label "确认" \
--msgbox "kohya_ss 非 Git 安装, 无法修复更新" \
$(get_dialog_size)
fi
;;
4)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 版本切换选项" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 kohya_ss 版本 ?" \
$(get_dialog_size)); then
git_ver_switch && \
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 版本切换选项" \
--ok-label "确认" \
--msgbox "kohya_ss 切换版本完成, 当前版本为: $(git_branch_display)" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 版本切换选项" \
--ok-label "确认" \
--msgbox "kohya_ss 非 Git 安装, 无法切换版本" \
$(get_dialog_size)
fi
;;
5)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 更新源切换选项" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 kohya_ss 更新源 ?" \
$(get_dialog_size)); then
kohya_ss_remote_revise
fi
else
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 更新源切换选项" \
--ok-label "确认" \
--msgbox "kohya_ss 非 Git 安装, 无法切换更新源" \
$(get_dialog_size)
fi
;;
6)
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 依赖更新选项" \
--yes-label "是" --no-label "否" \
--yesno "是否更新 kohya_ss 的依赖 ?" \
$(get_dialog_size)); then
kohya_ss_update_depend
fi
;;
7)
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 的 Python 软件包安装 / 重装 / 卸载选项" \
--yes-label "是" --no-label "否" \
--yesno "是否进入 Python 软件包安装 / 重装 / 卸载选项 ?" \
$(get_dialog_size)); then
python_package_manager
fi
;;
8)
python_package_ver_backup_manager
;;
9)
pytorch_reinstall
;;
10)
if is_use_venv; then
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 虚拟环境修复选项" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 kohya_ss 的虚拟环境 ?" \
$(get_dialog_size)); then
fix_venv
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 虚拟环境修复选项" \
--ok-label "确认" \
--msgbox "kohya_ss 虚拟环境修复完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 虚拟环境修复选项" \
--ok-label "确认" \
--msgbox "虚拟环境功能已禁用, 无法使用该功能" \
$(get_dialog_size)
fi
;;
11)
if is_use_venv; then
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 虚拟环境重建选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重建 kohya_ss 的虚拟环境 ?" \
$(get_dialog_size)); then
kohya_ss_venv_rebuild
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 虚拟环境重建选项" \
--ok-label "确认" \
--msgbox "kohya_ss 虚拟环境重建完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 虚拟环境重建选项" \
--ok-label "确认" \
--msgbox "虚拟环境功能已禁用, 无法使用该功能" \
$(get_dialog_size)
fi
;;
12)
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 后端组件重装选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重新安装 kohya_ss 后端组件 ?" \
$(get_dialog_size)); then
kohya_ss_backend_repo_reinstall
fi
;;
13)
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 重新安装选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重新安装 kohya_ss ?" \
$(get_dialog_size)); then
cd "${START_PATH}"
rm -f "${START_PATH}/term-sd/task/kohya_ss_install.sh"
exit_venv
install_kohya_ss
break
fi
;;
14)
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 删除选项" \
--yes-label "是" --no-label "否" \
--yesno "是否删除 kohya_ss ?" \
$(get_dialog_size)); then
term_sd_echo "请再次确认是否删除 kohya_ss (yes/no) ?"
term_sd_echo "警告: 该操作将永久删除 kohya_ss"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
yes|y|YES|Y)
term_sd_echo "删除 kohya_ss 中"
exit_venv
cd ..
rm -rf "${KOHYA_SS_ROOT_PATH}"
dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 删除选项" \
--ok-label "确认" \
--msgbox "删除 kohya_ss 完成" \
$(get_dialog_size)
break
;;
*)
term_sd_echo "取消删除 kohya_ss 操作"
;;
esac
fi
;;
*)
break
;;
esac
done
else
if (dialog --erase-on-exit \
--title "kohya_ss 管理" \
--backtitle "kohya_ss 安装选项" \
--yes-label "是" --no-label "否" \
--yesno "检测到当前未安装 kohya_ss , 是否进行安装 ?" \
$(get_dialog_size)); then
rm -f "${START_PATH}/term-sd/task/kohya_ss_install.sh"
install_kohya_ss
fi
fi
}
# kohya_ss 依赖更新功能
kohya_ss_update_depend() {
# 更新前的准备
download_mirror_select # 下载镜像源选择
pip_install_mode_select upgrade # 安装方式选择
if term_sd_install_confirm "是否更新 kohya_ss 依赖 ?"; then
term_sd_print_line "kohya_ss 依赖更新"
term_sd_echo "更新 kohya_ss 依赖中"
term_sd_tmp_disable_proxy
enter_venv
python_package_update "requirements.txt" # kohya_ss 依赖
exit_venv
term_sd_tmp_enable_proxy
term_sd_echo "更新 kohya_ss 依赖结束"
term_sd_pause
fi
clean_install_config # 清理安装参数
}
# 后端组件重装
kohya_ss_backend_repo_reinstall() {
download_mirror_select # 下载镜像源选择
if term_sd_install_confirm "是否重新安装 kohya_ss 后端组件 ?"; then
term_sd_print_line "kohya_ss 后端组件重装"
term_sd_echo "删除原有 kohya_ss 后端组件中"
rm -rf "${KOHYA_SS_ROOT_PATH}"/sd-scripts
term_sd_mkdir "${KOHYA_SS_ROOT_PATH}"/sd-scripts
term_sd_echo "重新下载 kohya_ss 后端组件中"
git_clone_repository https://github.com/kohya-ss/sd-scripts "${KOHYA_SS_ROOT_PATH}" sd-scripts # kohya_ss 后端
git_init_submodule "${KOHYA_SS_ROOT_PATH}"
term_sd_echo "重装 kohya_ss 后端组件结束"
term_sd_pause
fi
clean_install_config # 清理安装参数
}
|
2301_81996401/term-sd
|
modules/kohya_ss_manager.sh
|
Shell
|
agpl-3.0
| 15,112
|
#!/bin/bash
# lora-scripts 启动参数配置
# 设置的启动参数将保存在 <Start Path>/term-sd/config/lora-scripts-launch.conf
lora_scripts_launch_args_setting() {
local arg
local dialog_arg
local launch_args
local i
dialog_arg=$(dialog --erase-on-exit --notags \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--checklist "请选择 lora-scripts 启动参数, 确认之后将覆盖原有启动参数配置" \
$(get_dialog_size_menu) \
"1" "(listen) 开放远程连接" OFF \
"2" "(skip-prepare-environment) 跳过环境检查" OFF \
"3" "(disable-tensorboard)禁用 TernsorBoard" OFF \
"4" "(disable-tageditor) 禁用标签管理器" OFF \
"5" "(dev) 启用开发版功能" OFF \
"6" "(skip-prepare-onnxruntime) 跳过 onnxruntime 检查" ON \
"7" "(disable-auto-mirror) 禁用自动设置镜像" OFF \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
for i in ${dialog_arg}; do
case "${i}" in
1)
arg="--listen"
;;
2)
arg="--skip-prepare-environment"
;;
3)
arg="--disable-tensorboard"
;;
4)
arg="--disable-tageditor"
;;
5)
arg="--dev"
;;
6)
arg="--skip-prepare-onnxruntime"
;;
7)
arg="--disable-auto-mirror"
;;
esac
launch_args="${arg} ${launch_args}"
done
# 生成启动脚本
term_sd_echo "设置 lora-scripts 启动参数: ${launch_args}"
echo "gui.py ${launch_args}" > "${START_PATH}"/term-sd/config/lora-scripts-launch.conf
else
term_sd_echo "取消设置 lora-scripts 启动参数"
fi
}
# lora-scripts 启动界面
lora_scripts_launch() {
local dialog_arg
local launch_args
add_lora_scripts_normal_launch_args
while true; do
launch_args=$(cat "${START_PATH}"/term-sd/config/lora-scripts-launch.conf)
if is_use_venv; then
launch_args="python ${launch_args}"
else
launch_args="${TERM_SD_PYTHON_PATH} ${launch_args}"
fi
dialog_arg=$(dialog --erase-on-exit --notags \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 启动选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择启动 lora-scripts / 修改 lora-scripts 启动参数\n当前启动参数: ${launch_args}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 配置预设启动参数" \
"3" "> 修改自定义启动参数" \
"4" "> 重置启动参数" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
term_sd_launch
;;
2)
lora_scripts_launch_args_setting
;;
3)
lora_scripts_launch_args_revise
;;
4)
restore_lora_scripts_launch_args
;;
*)
break
;;
esac
done
}
# lora-scripts 启动参数修改
# 修改启动参数前从 term-sd/config/lora-scripts-launch.conf 读取启动参数
# 可在原来的基础上修改
lora_scripts_launch_args_revise() {
local dialog_arg
local launch_args
launch_args=$(cat "${START_PATH}"/term-sd/config/lora-scripts-launch.conf | awk '{sub("gui.py ","")}1')
dialog_arg=$(dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 自定义启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "请输入 lora-scripts 启动参数" \
$(get_dialog_size) \
"${launch_args}" \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
term_sd_echo "设置 lora-scripts 启动参数: ${dialog_arg}"
echo "gui.py ${dialog_arg}" > "${START_PATH}"/term-sd/config/lora-scripts-launch.conf
else
term_sd_echo "取消修改 lora-scripts 启动参数"
fi
}
# 添加默认启动参数配置
add_lora_scripts_normal_launch_args() {
if [[ ! -f "${START_PATH}/term-sd/config/lora-scripts-launch.conf" ]]; then # 找不到启动配置时默认生成一个
echo "gui.py --skip-prepare-onnxruntime" > "${START_PATH}"/term-sd/config/lora-scripts-launch.conf
fi
}
# 重置启动参数
restore_lora_scripts_launch_args() {
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 重置启动参数选项选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重置 lora-scripts 启动参数 ?" \
$(get_dialog_size)); then
term_sd_echo "重置 lora-scripts 启动参数"
rm -f "${START_PATH}"/term-sd/config/lora-scripts-launch.conf
add_lora_scripts_normal_launch_args
else
term_sd_echo "取消重置 lora-scripts 启动参数操作"
fi
}
|
2301_81996401/term-sd
|
modules/lora_scripts_launch.sh
|
Shell
|
agpl-3.0
| 5,393
|
#!/bin/bash
# lora-scripts 管理
lora_scripts_manager() {
local dialog_arg
cd "${START_PATH}" # 回到最初路径
exit_venv # 确保进行下一步操作前已退出其他虚拟环境
if [[ -d "${LORA_SCRIPTS_ROOT_PATH}" ]] && ! term_sd_is_dir_empty "${LORA_SCRIPTS_ROOT_PATH}"; then
while true; do
cd "${LORA_SCRIPTS_ROOT_PATH}"
dialog_arg=$(dialog --erase-on-exit --notags \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择 lora-scripts 管理选项的功能\n当前更新源: $(git_remote_display)\n当前分支: $(git_branch_display)" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 更新" \
"3" "> 修复更新" \
"4" "> 切换版本" \
"5" "> 更新源替换" \
"6" "> 更新依赖" \
"7" "> Python 软件包安装 / 重装 / 卸载" \
"8" "> 依赖库版本管理" \
"9" "> 重新安装 PyTorch" \
"10" "> 修复虚拟环境" \
"11" "> 重新构建虚拟环境" \
"12" "> 重新安装后端组件" \
"13" "> 重新安装" \
"14" "> 卸载" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
lora_scripts_launch
;;
2)
if is_git_repo; then
term_sd_echo "更新 lora-scripts 中"
git_pull_repository
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 更新结果" \
--ok-label "确认" \
--msgbox "lora-scripts 更新成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 更新结果" \
--ok-label "确认" \
--msgbox "lora-scripts 更新失败" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 更新结果" \
--ok-label "确认" \
--msgbox "lora-scripts 非 Git 安装, 无法更新" \
$(get_dialog_size)
fi
;;
3)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 更新修复选项" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 lora-scripts 更新 ?" \
$(get_dialog_size)); then
git_fix_pointer_offset
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 更新修复选项" \
--ok-label "确认" \
--msgbox "lora-scripts 更新修复完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 更新修复选项" \
--ok-label "确认" \
--msgbox "lora-scripts 非 Git 安装, 无法修复更新" \
$(get_dialog_size)
fi
;;
4)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 版本切换选项" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 lora-scripts 版本 ?" \
$(get_dialog_size)); then
git_ver_switch && \
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 版本切换选项" \
--ok-label "确认" \
--msgbox "lora-scripts 版本切换完成, 当前版本为: $(git_branch_display)" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 版本切换选项" \
--ok-label "确认" \
--msgbox "lora-scripts 非 Git 安装, 无法切换更新" \
$(get_dialog_size)
fi
;;
5)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 更新源切换选项" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 lora-scripts 更新源 ?" \
$(get_dialog_size)); then
lora_scripts_remote_revise
fi
else
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 更新源切换选项" \
--ok-label "确认" \
--msgbox "lora-scripts 非 Git 安装, 无法切换更新源" \
$(get_dialog_size)
fi
;;
6)
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 依赖更新选项" \
--yes-label "是" --no-label "否" \
--yesno "是否更新 lora-scripts 的依赖 ?" \
$(get_dialog_size)); then
lora_scripts_update_depend
fi
;;
7)
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 的 Python 软件包安装 / 重装/ 卸载选项" \
--yes-label "是" --no-label "否" \
--yesno "是否进入 Python 软件包安装/ 重装 / 卸载选项 ?" \
$(get_dialog_size)); then
python_package_manager
fi
;;
8)
python_package_ver_backup_manager
;;
9)
pytorch_reinstall
;;
10)
if is_use_venv; then
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 虚拟环境修复选项" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 lora-scripts 的虚拟环境 ?" \
$(get_dialog_size)); then
fix_venv
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 虚拟环境修复选项" \
--ok-label "确认" \
--msgbox "lora-scripts 虚拟环境修复完成" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 虚拟环境修复选项" \
--ok-label "确认" \
--msgbox "虚拟环境功能已禁用, 无法使用该功能" \
$(get_dialog_size)
fi
;;
11)
if is_use_venv; then
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 虚拟环境重建选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重建 lora-scripts 的虚拟环境 ?" \
$(get_dialog_size)); then
lora_scripts_venv_rebuild
fi
else
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 虚拟环境重建选项" \
--ok-label "确认" \
--msgbox "虚拟环境功能已禁用, 无法使用该功能" \
$(get_dialog_size)
fi
;;
12)
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 后端组件重装选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重新安装 lora-scripts 后端组件 ?" \
$(get_dialog_size)); then
lora_scripts_backend_repo_reinstall
fi
;;
13)
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 重新安装选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重新安装 lora-scripts ?" \
$(get_dialog_size)); then
cd "${START_PATH}"
rm -f "${START_PATH}/term-sd/task/lora_scripts_install.sh"
exit_venv
install_lora_scripts
break
fi
;;
14)
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 删除选项" \
--yes-label "是" --no-label "否" \
--yesno "是否删除 lora-scripts ?" \
$(get_dialog_size)); then
term_sd_echo "请再次确认是否删除 lora-scripts (yes/no) ?"
term_sd_echo "警告: 该操作将永久删除 lora-scripts"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
yes|y|YES|Y)
term_sd_echo "删除 lora-scripts 中"
exit_venv
cd ..
rm -rf "${LORA_SCRIPTS_ROOT_PATH}"
dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 删除选项" \
--ok-label "确认" \
--msgbox "删除 lora-scripts 完成" \
$(get_dialog_size)
break
;;
*)
term_sd_echo "取消删除 lora-scripts 操作"
;;
esac
fi
;;
*)
break
;;
esac
done
else
if (dialog --erase-on-exit \
--title "lora-scripts 管理" \
--backtitle "lora-scripts 安装选项" \
--yes-label "是" --no-label "否" \
--yesno "检测到当前未安装 lora_scripts, 是否进行安装 ?" \
$(get_dialog_size)); then
rm -f "${START_PATH}/term-sd/task/lora_scripts_install.sh"
install_lora_scripts
fi
fi
}
# lora-scripts 依赖更新功能
lora_scripts_update_depend() {
# 更新前的准备
download_mirror_select # 下载镜像源选择
pip_install_mode_select upgrade # 安装方式选择
if term_sd_install_confirm "是否更新 lora-scripts 依赖 ?"; then
term_sd_print_line "lora-scripts 依赖更新"
term_sd_echo "更新 lora-scripts 依赖中"
term_sd_tmp_disable_proxy
enter_venv
python_package_update requirements.txt # lora-scripts 依赖
exit_venv
term_sd_tmp_enable_proxy
term_sd_echo "更新 lora-scripts 依赖结束"
term_sd_pause
fi
clean_install_config # 清理安装参数
}
# 后端组件重装
lora_scripts_backend_repo_reinstall() {
download_mirror_select # 下载镜像源选择
if term_sd_install_confirm "是否重新安装 lora-scripts 后端组件 ?"; then
term_sd_print_line "lora-scripts 后端组件重装"
term_sd_echo "删除原有 lora-scripts 后端组件中"
rm -rf "${LORA_SCRIPTS_ROOT_PATH}"/frontend
rm -rf "${LORA_SCRIPTS_ROOT_PATH}"/mikazuki/dataset-tag-editor
term_sd_mkdir frontend
term_sd_mkdir mikazuki/dataset-tag-editor
term_sd_echo "重新下载 lora-scripts 后端组件中"
git_clone_repository https://github.com/hanamizuki-ai/lora-gui-dist "${LORA_SCRIPTS_ROOT_PATH}" frontend # lora-scripts 前端
git_clone_repository https://github.com/Akegarasu/dataset-tag-editor "${LORA_SCRIPTS_ROOT_PATH}"/mikazuki dataset-tag-editor # 标签编辑器
git_init_submodule "${LORA_SCRIPTS_ROOT_PATH}"
term_sd_echo "重装 lora-scripts 后端组件结束"
term_sd_pause
fi
clean_install_config # 清理安装参数
}
|
2301_81996401/term-sd
|
modules/lora_scripts_manager.sh
|
Shell
|
agpl-3.0
| 15,378
|
#!/bin/bash
# 安装 Python 软件包功能
# 使用 PIP_PACKAGE_MANAGER_METHON_NAME 全局变量获取进行操作的 Python 软件包的操作名
# 使用 PIP_PACKAGE_MANAGER_METHON 全集变量获取要进行的 Python 软件包操作
python_package_manager() {
local dialog_arg
local req
local i
# 安装前的准备
download_mirror_select # 下载镜像源选择
pip_manage_package_methon_select # Python 软件包操作方式选择
dialog_arg=$(dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${TERM_SD_MANAGE_OBJECT} Python 软件包安装 / 重装 / 卸载选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "请输入需要安装 / 重装 / 卸载的 Python 软件包名" \
$(get_dialog_size) 3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]] && [ ! -z "$(echo ${dialog_arg} | awk '{gsub(/[=+<>]/, "")}1')" ]; then
if term_sd_install_confirm "是否${PIP_PACKAGE_MANAGER_METHON_NAME}输入的 Python 软件包 ?"; then
term_sd_print_line "Python 软件包${PIP_PACKAGE_MANAGER_METHON_NAME}"
term_sd_echo "将${PIP_PACKAGE_MANAGER_METHON_NAME}以下 Python 软件包"
for i in ${dialog_arg}; do
echo ${i}
done
term_sd_print_line
enter_venv
term_sd_tmp_disable_proxy
case "${PIP_PACKAGE_MANAGER_METHON}" in # 选择pip包管理器管理方法
1)
# 常规安装
install_python_package ${dialog_arg}
;;
2)
# 仅安装
install_python_package --no-deps ${dialog_arg}
;;
3)
# 强制重装
install_python_package --force-reinstall ${dialog_arg}
;;
4)
# 仅强制重装
install_python_package --force-reinstall --no-deps ${dialog_arg}
;;
5)
# 卸载
term_sd_try term_sd_pip uninstall -y ${dialog_arg}
;;
esac
req=$?
term_sd_echo "${PIP_PACKAGE_MANAGER_METHON_NAME} Python 软件包结束"
term_sd_tmp_enable_proxy
term_sd_print_line
if [[ "${req}" == 0 ]]; then
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "Python 软件包${PIP_PACKAGE_MANAGER_METHON_NAME}结果" \
--ok-label "确认" \
--msgbox "以下 Python 软件包${PIP_PACKAGE_MANAGER_METHON_NAME}成功\n${TERM_SD_DELIMITER}\n${dialog_arg}\n${TERM_SD_DELIMITER}" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "Python 软件包${PIP_PACKAGE_MANAGER_METHON_NAME}结果" \
--ok-label "确认" \
--msgbox "以下 Python 软件包${PIP_PACKAGE_MANAGER_METHON_NAME}失败\n${TERM_SD_DELIMITER}\n${dialog_arg}\n${TERM_SD_DELIMITER}" \
$(get_dialog_size)
fi
else
term_sd_echo "取消${PIP_PACKAGE_MANAGER_METHON_NAME} Python 软件包操作"
fi
else
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${TERM_SD_MANAGE_OBJECT} Python 软件包安装 / 重装 / 卸载选项" \
--ok-label "确认" \
--msgbox "未输入 Python 软件包名, 不执行 Python 软件包操作" \
$(get_dialog_size)
fi
unset PIP_PACKAGE_MANAGER_METHON
unset PIP_PACKAGE_MANAGER_METHON_NAME
clean_install_config # 清理安装参数
}
# Pip 管理软件包方法选择
# 将操作方法的名称保存至 PIP_PACKAGE_MANAGER_METHON_NAME 全局变量
# 将操作方法保存在 PIP_PACKAGE_MANAGER_METHON 全局变量中
pip_manage_package_methon_select() {
local dialog_arg
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Term-SD" \
--backtitle "Pip 操作方式选项" \
--ok-label "确认" --no-cancel \
--menu "请选择 Pip 操作方式\n1、常规安装用于安装缺失的软件包\n2、强制重装可解决软件包损坏问题, 但同时重新安装软件包所需的依赖, 速度较慢\n3、卸载软件包\n注: 带有 \"仅\" 的功能是在安装时只安装用户输入的软件包, 而不安装这些软件包的依赖\n安装 / 重装软件包时可以只写包名, 也可以指定包名版本\n可以输入多个软件包的包名, 并使用空格隔开\n如果想要更新某个软件包的版本, 可以加上 -U 参数\n例:\nxformers\nxformers==0.0.21\nxformers==0.0.21 numpy\nnumpy -U" \
$(get_dialog_size_menu) \
"1" "> 常规安装 (install)" \
"2" "> 仅安装 (--no-deps)" \
"3" "> 强制重装 (--force-reinstall)" \
"4" "> 仅强制重装 (--no-deps --force-reinstall)" \
"5" "> 卸载 (uninstall)" \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
case "${dialog_arg}" in
1)
PIP_PACKAGE_MANAGER_METHON_NAME="安装"
PIP_PACKAGE_MANAGER_METHON=1
;;
2)
PIP_PACKAGE_MANAGER_METHON_NAME="安装 (--no-deps)"
PIP_PACKAGE_MANAGER_METHON=2
;;
3)
PIP_PACKAGE_MANAGER_METHON_NAME="强制重装 (--force-reinstall)"
PIP_PACKAGE_MANAGER_METHON=3
;;
4)
PIP_PACKAGE_MANAGER_METHON_NAME="强制重装 (--no-deps --force-reinstall)"
PIP_PACKAGE_MANAGER_METHON=4
;;
5)
PIP_PACKAGE_MANAGER_METHON_NAME="卸载"
PIP_PACKAGE_MANAGER_METHON=5
;;
esac
fi
}
# Python 软件包更新
# 使用:
# python_package_update <requirements.txt>
# 进行更新依赖操作时将忽略部分软件包
# 忽略的软件包名单:
# torch torchvision torchaudio xformers InvokeAI
python_package_update() {
cat "$@" > tmp-python-package-update-list.txt # 生成要更新的软件包名单
local ignore_update_python_package_list="torch torchvision torchaudio xformers InvokeAI" # 忽略更新的软件包名单
for i in ${ignore_update_python_package_list}; do
sed -i '/'$i'/d' tmp-python-package-update-list.txt 2> /dev/null # 将忽略的软件包从名单删除
done
if term_sd_is_debug; then
term_sd_print_line "Python 软件包更新列表"
term_sd_echo "要进行更新的软件包名单:"
cat tmp-python-package-update-list.txt
term_sd_print_line
term_sd_echo "cmd: install_python_package -r tmp-python-package-update-list.txt"
fi
# 更新 Python 软件包
install_python_package -r tmp-python-package-update-list.txt
rm -f tmp-python-package-update-list.txt # 删除列表缓存
}
# Python 软件包安装
# 使用:
# install_python_package <软件包> <其他参数>
# 使用以下全局变量作为参数使用
# PIP_INDEX_MIRROR, PIP_EXTRA_INDEX_MIRROR, PIP_FIND_LINKS_MIRROR
# UV_INDEX_MIRROR, UV_EXTRA_INDEX_MIRROR, UV_FIND_LINKS_MIRROR
# PIP_BREAK_SYSTEM_PACKAGE_ARG, PIP_USE_PEP517_ARG, PIP_FORCE_REINSTALL_ARG
# 可使用 Pip 或者 uv 进行 Python 软件包安装
install_python_package() {
if term_sd_is_debug; then
term_sd_echo "PIP_INDEX_MIRROR: ${PIP_INDEX_MIRROR}"
term_sd_echo "PIP_EXTRA_INDEX_MIRROR: ${PIP_EXTRA_INDEX_MIRROR}"
term_sd_echo "PIP_FIND_LINKS_MIRROR: ${PIP_FIND_LINKS_MIRROR}"
term_sd_echo "UV_INDEX_MIRROR: ${UV_INDEX_MIRROR}"
term_sd_echo "UV_EXTRA_INDEX_MIRROR: ${UV_EXTRA_INDEX_MIRROR}"
term_sd_echo "UV_FIND_LINKS_MIRROR: ${UV_FIND_LINKS_MIRROR}"
term_sd_echo "PIP_BREAK_SYSTEM_PACKAGE_ARG: ${PIP_BREAK_SYSTEM_PACKAGE_ARG}"
term_sd_echo "PIP_USE_PEP517_ARG: ${PIP_USE_PEP517_ARG}"
term_sd_echo "PIP_FORCE_REINSTALL_ARG: ${PIP_FORCE_REINSTALL_ARG}"
term_sd_echo "PIP_UPDATE_PACKAGE_ARG: ${PIP_UPDATE_PACKAGE_ARG}"
if term_sd_is_use_uv; then
term_sd_echo "cmd: term_sd_uv_install $@ ${UV_INDEX_MIRROR} ${UV_EXTRA_INDEX_MIRROR} ${UV_FIND_LINKS_MIRROR} ${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG}"
else
term_sd_echo "cmd: term_sd_pip install $@ ${PIP_INDEX_MIRROR} ${PIP_EXTRA_INDEX_MIRROR} ${PIP_FIND_LINKS_MIRROR} ${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_USE_PEP517_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG}"
fi
fi
if term_sd_is_use_uv; then
term_sd_try term_sd_uv_install "$@" ${UV_INDEX_MIRROR} ${UV_EXTRA_INDEX_MIRROR} ${UV_FIND_LINKS_MIRROR} ${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG}
if check_uv_install_failed_and_warning; then
term_sd_try term_sd_pip install "$@" ${PIP_INDEX_MIRROR} ${PIP_EXTRA_INDEX_MIRROR} ${PIP_FIND_LINKS_MIRROR} ${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_USE_PEP517_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG}
fi
else
term_sd_try term_sd_pip install "$@" ${PIP_INDEX_MIRROR} ${PIP_EXTRA_INDEX_MIRROR} ${PIP_FIND_LINKS_MIRROR} ${PIP_BREAK_SYSTEM_PACKAGE_ARG} ${PIP_USE_PEP517_ARG} ${PIP_FORCE_REINSTALL_ARG} ${PIP_UPDATE_PACKAGE_ARG}
fi
}
|
2301_81996401/term-sd
|
modules/python_package_manager.sh
|
Shell
|
agpl-3.0
| 9,532
|
#!/bin/bash
# Python 依赖库版本备份与恢复功能
# 使用 TERM_SD_MANAGE_OBJECT 全局变量判断要进行备份依赖的 AI 软件
python_package_ver_backup_manager() {
local dialog_arg
local req_file_info
local backup_req_file_name
# 如果没有存放备份文件的文件夹时就创建一个新的用于存放备份的依赖信息
term_sd_mkdir "${START_PATH}"/term-sd/requirements-backup
case "${TERM_SD_MANAGE_OBJECT}" in
stable-diffusion-webui)
term_sd_mkdir "${START_PATH}"/term-sd/requirements-backup/stable-diffusion-webui
backup_req_file_name="stable-diffusion-webui"
enter_venv "${SD_WEBUI_ROOT_PATH}"
;;
ComfyUI)
term_sd_mkdir "${START_PATH}"/term-sd/requirements-backup/ComfyUI
backup_req_file_name="ComfyUI"
enter_venv "${COMFYUI_ROOT_PATH}"
;;
InvokeAI)
term_sd_mkdir "${START_PATH}"/term-sd/requirements-backup/InvokeAI
backup_req_file_name="InvokeAI"
enter_venv "${INVOKEAI_ROOT_PATH}"
;;
Fooocus)
term_sd_mkdir "${START_PATH}"/term-sd/requirements-backup/Fooocus
backup_req_file_name="Fooocus"
enter_venv "${FOOOCUS_ROOT_PATH}"
;;
lora-scripts)
term_sd_mkdir "${START_PATH}"/term-sd/requirements-backup/lora-scripts
backup_req_file_name="lora-scripts"
enter_venv "${LORA_SCRIPTS_ROOT_PATH}"
;;
kohya_ss)
term_sd_mkdir "${START_PATH}"/term-sd/requirements-backup/kohya_ss
backup_req_file_name="kohya_ss"
enter_venv "${KOHYA_SS_ROOT_PATH}"
;;
esac
while true; do
if term_sd_is_dir_empty "${START_PATH}"/term-sd/requirements-backup/"${backup_req_file_name}"; then
req_file_info="无"
else
req_file_info=$(ls -lht "${START_PATH}"/term-sd/requirements-backup/${backup_req_file_name} --time-style=+"%Y-%m-%d" | awk 'NR==2 {print $7}' )
fi
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Term-SD" \
--backtitle "${backup_req_file_name} 依赖库版本管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择 Term-SD 的依赖库版本管理功能\n当前 ${backup_req_file_name} 依赖库版本备份情况: ${req_file_info}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 备份 Python 依赖库版本" \
"2" "> Python 依赖库版本管理" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
if (dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${backup_req_file_name} 依赖库版本备份选项" \
--yes-label "是" --no-label "否" \
--yesno "是否备份 ${backup_req_file_name} 依赖库 ?" \
$(get_dialog_size)); then
backup_python_package_ver "${backup_req_file_name}"
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${backup_req_file_name} 依赖库版本备份选项" \
--ok-label "确认" \
--msgbox "${backup_req_file_name} 依赖库版本备份成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${backup_req_file_name} 依赖库版本备份选项" \
--ok-label "确认" \
--msgbox "${backup_req_file_name} 依赖库版本备份失败" \
$(get_dialog_size)
fi
fi
;;
2)
python_package_ver_backup_list "${backup_req_file_name}"
;;
*)
exit_venv
break
;;
esac
done
}
# Python 依赖库备份功能
# 使用:
# backup_python_package_ver <要备份软件包的 AI 软件名>
# 依赖信息文件保存在 <Start Path>/term-sd/requirements-backup/<要备份软件包的 AI 软件名> 中
# 获取 TERM_SD_MANAGE_OBJECT 全局变量作为文件名
backup_python_package_ver() {
local req_file
local backup_name=$@
local name
term_sd_echo "备份 ${backup_name} 的 Python 依赖库版本中"
# 生成一个文件名
case "${TERM_SD_MANAGE_OBJECT}" in
stable-diffusion-webui)
case "$(git remote get-url origin | awk -F '/' '{print $NF}')" in # 分支判断
stable-diffusion-webui|stable-diffusion-webui.git)
name="stable-diffusion-webui"
;;
automatic|automatic.git)
name="sdnext"
;;
stable-diffusion-webui-directml|stable-diffusion-webui-directml.git|stable-diffusion-webui-amdgpu|stable-diffusion-webui-amdgpu.git)
name="stable-diffusion-webui-directml"
;;
stable-diffusion-webui-forge|stable-diffusion-webui-forge.git)
name="stable-diffusion-webui-forge"
;;
stable-diffusion-webui-reForge|stable-diffusion-webui-reForge.git)
name="stable-diffusion-webui-reForge"
;;
sd-webui-forge-classic|sd-webui-forge-classic.git)
name="sd-webui-forge-classic"
;;
*)
name="stable-diffusion-webui"
;;
esac
;;
ComfyUI|InvokeAI|Fooocus|lora-scripts|kohya_ss)
name=$TERM_SD_MANAGE_OBJECT
;;
esac
req_file="${name}-$(date "+%Y-%m-%d-%H-%M-%S").txt"
# 将python依赖库中各个包和包版本备份到文件中
get_python_env_pkg > "${START_PATH}/term-sd/requirements-backup/${backup_name}/${req_file}"
if [[ "$?" == 0 ]]; then
term_sd_echo "备份 ${backup_name} 依赖库版本成功"
return 0
else
term_sd_echo "备份 ${backup_name} 依赖库版本失败"
rm -f "${START_PATH}/term-sd/requirements-backup/${backup_name}/${req_file}"
return 1
fi
}
# 备份文件列表浏览器
# 使用:
# python_package_ver_backup_list <要备份软件包的 AI 软件名>
python_package_ver_backup_list() {
local backup_name=$@
while true; do
get_dir_list "${START_PATH}/term-sd/requirements-backup/${backup_name}" # 获取当前目录下的所有文件夹
if term_sd_is_bash_ver_lower; then # Bash 版本低于 4 时使用旧版列表显示方案
req_file_name=$(dialog --erase-on-exit \
--ok-label "确认" --cancel-label "取消" \
--title "Term-SD" \
--backtitle "${backup_name} 依赖库版本记录列表选项" \
--menu "使用上下键请选择依赖库版本记录" \
$(get_dialog_size_menu) \
"-->返回<--" "<---------" \
"${LOCAL_DIR_LIST}" \
3>&1 1>&2 2>&3)
else
req_file_name=$(dialog --erase-on-exit \
--ok-label "确认" --cancel-label "取消" \
--title "Term-SD" \
--backtitle "${backup_name} 依赖库版本记录列表选项" \
--menu "使用上下键请选择依赖库版本记录" \
$(get_dialog_size_menu) \
"-->返回<--" "<---------" \
"${LOCAL_DIR_LIST[@]}" \
3>&1 1>&2 2>&3)
fi
if [[ "$?" == 0 ]]; then
if [[ "${req_file_name}" == "-->返回<--" ]]; then
break
elif [[ -f "${START_PATH}/term-sd/requirements-backup/${backup_name}/${req_file_name}" ]]; then # 选择的是文件
process_python_package_ver_backup "${backup_name}" "${req_file_name}"
elif [[ -f "${START_PATH}/term-sd/requirements-backup/${backup_name}/${req_file_name}" ]]; then # 选择的是文件夹
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${backup_name} 依赖库版本记录列表选项" \
--ok-label "确认" \
--msgbox "选中的项目不是依赖记录文件, 请重新选择" \
$(get_dialog_size)
fi
else
break
fi
done
}
# 依赖库备份文件处理选项
# 使用:
# process_python_package_ver_backup <要备份软件包的 AI 软件名> <依赖文件的文件名>
process_python_package_ver_backup() {
local dialog_arg
local backup_name=$1
local req_file_name=$2
while true; do
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Term-SD" \
--backtitle "依赖库版本记录管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择 Term-SD 的依赖库版本记录管理功能\n当前版本记录: ${req_file_name%.txt}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 恢复该版本记录" \
"2" "> 删除该版本记录" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
if (dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "依赖库版本恢复确认选项" \
--yes-label "是" --no-label "否" \
--yesno "是否恢复该版本记录 ?" \
$(get_dialog_size)); then
restore_python_package_ver "${backup_name}" "${req_file_name}"
fi
;;
2)
if (dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "安装确认选项" \
--yes-label "是" --no-label "否" \
--yesno "是否删除该版本记录 ?" \
$(get_dialog_size)); then
term_sd_echo "删除 ${req_file_name%.txt} 记录中"
rm -f "${START_PATH}/term-sd/requirements-backup/${backup_name}/${req_file_name}"
dialog --erase-on-exit \
--title "Term-SD" \
--backtitle "${backup_name} 依赖库版本记录列表选项" \
--ok-label "确认" \
--msgbox "${req_file_name%.txt} 记录删除完成" \
$(get_dialog_size)
break
fi
;;
*)
break
;;
esac
done
}
# 恢复依赖库版本功能
# 使用:
# restore_python_package_ver <要备份软件包的 AI 软件名> <依赖文件的文件名>
restore_python_package_ver() {
local backup_name=$1
local req_file_name=$2
local i
local tmp_py_pkg_has_ver_list_path="${START_PATH}/term-sd/task/tmp-${TERM_SD_MANAGE_OBJECT}-python-pkg-has-vers.txt" # 含有版本的 Python 软件包列表(环境)
local tmp_py_pkg_no_ver_list_path="${START_PATH}/term-sd/task/tmp-${TERM_SD_MANAGE_OBJECT}-python-pkg-no-vers.txt" # 无版本的 Python 软件包列表(环境)
local tmp_py_pkg_no_ver_bak_list_path="${START_PATH}/term-sd/task/tmp-${TERM_SD_MANAGE_OBJECT}-python-pkg-no-vers-bak.txt" # 无版本的 Python 软件包列表(备份列表)
local ipex_mirror
# 安装前的准备
download_mirror_select # 下载镜像源选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否恢复依赖库版本 ?"; then
term_sd_print_line "Python 软件包版本恢复"
term_sd_echo "开始恢复依赖库版本中, 版本: ${req_file_name%.txt}"
term_sd_echo "统计需要安装和卸载的 Python 软件包中"
rm -f "${tmp_py_pkg_has_ver_list_path}"
rm -f "${tmp_py_pkg_no_ver_list_path}"
rm -f "${tmp_py_pkg_no_ver_bak_list_path}"
cat "${START_PATH}"/term-sd/requirements-backup/${backup_name}/${req_file_name} | awk -F'==' '{print $1}' | awk -F '@' '{print $1}' > "${tmp_py_pkg_no_ver_bak_list_path}" # 生成一份无版本的备份列表
get_python_env_pkg > "${tmp_py_pkg_has_ver_list_path}" # 生成一份含有版本的现有列表
# 生成一份软件包卸载名单
for i in $(cat "${tmp_py_pkg_no_ver_bak_list_path}"); do
sed -i '/'$i'==/d' "${tmp_py_pkg_has_ver_list_path}" 2> /dev/null
sed -i '/'$i' @/d' "${tmp_py_pkg_has_ver_list_path}" 2> /dev/null
done
sed -i '/-e /d' "${tmp_py_pkg_has_ver_list_path}" 2> /dev/null
cat "${tmp_py_pkg_has_ver_list_path}" | awk -F '==' '{print $1}' | awk -F '@' '{print $1}' > "${tmp_py_pkg_no_ver_list_path}" # 生成一份无版本的卸载列表
term_sd_tmp_disable_proxy # 临时取消代理,避免一些不必要的网络减速
if [[ ! -z "$(cat "${tmp_py_pkg_no_ver_list_path}")" ]]; then
term_sd_print_line "Python 软件包卸载列表"
term_sd_echo "将要卸载以下 Python 软件包"
cat "${tmp_py_pkg_no_ver_list_path}"
term_sd_print_line
term_sd_echo "卸载多余 Python 软件包中"
term_sd_pip uninstall -y -r "${tmp_py_pkg_no_ver_list_path}" # 卸载名单中的依赖包
else
term_sd_echo "无需卸载 Python 软件包"
fi
term_sd_print_line "Python 软件包安装列表"
term_sd_echo "将要安装以下 Python 软件包"
cat "${START_PATH}/term-sd/requirements-backup/${backup_name}/${req_file_name}"
term_sd_print_line
term_sd_echo "恢复依赖库版本中"
if is_use_pip_mirror; then
ipex_mirror="--extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/cn"
else
ipex_mirror="--extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us"
fi
install_python_package -r "${START_PATH}/term-sd/requirements-backup/${backup_name}/${req_file_name}" --no-deps ${ipex_mirror} # 安装原有版本的依赖包
term_sd_tmp_enable_proxy # 恢复原有的代理
rm -f "${tmp_py_pkg_has_ver_list_path}"
rm -f "${tmp_py_pkg_no_ver_list_path}"
rm -f "${tmp_py_pkg_no_ver_bak_list_path}"
term_sd_echo "恢复依赖库版本完成"
term_sd_pause
fi
clean_install_config # 清理安装参数
}
# 获取 Python 软件包版本列表
get_python_env_pkg() {
term_sd_pip freeze \
|| PIP_DISABLE_PIP_VERSION_CHECK=1 term_sd_pip list | awk 'NR>2 { if ($2 != "" && $3 == "" && $1 != "pip") {print $1 "==" $2} }'
}
|
2301_81996401/term-sd
|
modules/python_package_ver_backup.sh
|
Shell
|
agpl-3.0
| 15,143
|
#!/bin/bash
# 虚拟环境创建功能
create_venv() {
if is_use_venv; then
if [[ ! -z "$@" ]]; then # 指定路径创建虚拟环境
term_sd_echo "创建虚拟环境"
term_sd_python -m venv "$@"/venv &> /dev/null
term_sd_echo "创建虚拟环境完成"
else
term_sd_echo "创建虚拟环境"
term_sd_python -m venv venv &> /dev/null
term_sd_echo "创建虚拟环境完成"
fi
fi
}
# 检测并修复虚拟环境的激活脚本中的现路径错误
# 使用:
# fix_activate_venv_script <虚拟环境的路径>
fix_activate_venv_script() {
local status
local venv_path=$@
local venv_bin_path
if [[ -d "${venv_path}/Scripts" ]]; then
venv_bin_path="${venv_path}/Scripts"
elif [[ -d "${venv_path}/bin" ]]; then
venv_bin_path="${venv_path}/bin"
else
venv_bin_path="${venv_path}/bin"
fi
status=$(term_sd_python "${START_PATH}/term-sd/python_modules/check_venv_path_invalid.py" \
--venv-bin-path "${venv_bin_path}"\
--venv-path "${venv_path}"\
)
if [[ "${status}" == "True" ]]; then
term_sd_echo "修正虚拟环境激活脚本中"
term_sd_python -m venv "${venv_path}"
fi
}
# 修复虚拟环境功能(一种骚操作, 修复完后只会丢失一些命令文件, 而 Python 的库调用依然正常)
# 已知问题: 使用该方法修复虚拟环境后, PyTorch 可能会报错, 提示某个文件找不到, 需要使用 PyTorch 重装功能将 PyTorch 重新安装
# fix_venv <虚拟环境的路径>
fix_venv() {
local venv_path
# 虚拟环境路径
if [[ ! -z "$@" ]]; then
venv_path="$(term_sd_win2unix_path "$@")/venv"
else
venv_path="$(pwd)/venv"
fi
if is_use_venv; then
if [[ -d "${venv_path}" ]]; then
term_sd_echo "修复虚拟环境中"
# 判断虚拟环境的类型
if [[ -d "${venv_path}/Scripts" ]]; then # Windows 端的 venv 结构
term_sd_echo "将虚拟环境的库转移到临时文件夹中"
mkdir term-sd-tmp
mv -f "${venv_path}"/Lib term-sd-tmp # 将依赖库转移到临时文件夹
rm -rf venv # 删除原有虚拟环境
term_sd_echo "重新创建新的虚拟环境"
term_sd_python -m venv "${venv_path}" &> /dev/null # 重新创建新的虚拟环境
rm -rf "${venv_path}"/Lib # 删除新的虚拟环境中的库文件, 为移入原有的库腾出空间
term_sd_echo "恢复虚拟环境库文件中"
mv -f term-sd-tmp/Lib "${venv_path}" # 移入原有的库
rm -rf term-sd-tmp # 清理临时文件夹
term_sd_python -m venv "${venv_path}" &> /dev/null
term_sd_echo "修复虚拟环境完成"
elif [[ -d "${venv_path}/bin" ]]; then # Linux / MacOS 端的 venv 结构
term_sd_echo "将虚拟环境的库转移到临时文件夹中"
mkdir term-sd-tmp
mv -f "${venv_path}"/lib term-sd-tmp # 将依赖库转移到临时文件夹
rm -rf "${venv_path}" # 删除原有虚拟环境
term_sd_echo "重新创建新的虚拟环境"
term_sd_python -m venv "${venv_path}" &> /dev/null # 重新创建新的虚拟环境
rm -rf "${venv_path}"/lib # 删除新的虚拟环境中的库文件, 为移入原有的库腾出空间
term_sd_echo "恢复虚拟环境库文件中"
mv -f term-sd-tmp/lib "${venv_path}" # 移入原有的库
rm -rf term-sd-tmp # 清理临时文件夹
term_sd_python -m venv "${venv_path}" &> /dev/null
term_sd_echo "修复虚拟环境完成"
else # 未判断出类型
term_sd_echo "创建虚拟环境中"
term_sd_python -m venv "${venv_path}" &> /dev/null
term_sd_echo "创建虚拟环境完成"
fi
else
term_sd_echo "创建虚拟环境中"
term_sd_python -m venv "${venv_path}" &> /dev/null
term_sd_echo "创建虚拟环境完成"
fi
fi
}
# 进入虚拟环境功能
# 使用:
# enter_venv <虚拟环境的路径>
enter_venv() {
local venv_path
local is_venv_broken=0
# 虚拟环境路径
if [[ ! -z "$@" ]]; then
venv_path="$(term_sd_win2unix_path "$@")/venv"
else
venv_path="$(pwd)/venv"
fi
if is_use_venv; then
if [[ ! -z "${VIRTUAL_ENV}" ]]; then # 检测到未退出虚拟环境
exit_venv &> /dev/null
fi
term_sd_echo "进入虚拟环境"
fix_activate_venv_script "${venv_path}" # 检查虚拟环境激活脚本
if [[ -f "${venv_path}/Scripts/activate" ]]; then # 在 Windows 端的 venv 目录结构和 Linux, MacoOS 的不同, 所以进入虚拟环境的方式有区别
. "${venv_path}"/Scripts/activate &> /dev/null
elif [[ -f "${venv_path}/bin/activate" ]]; then
. "${venv_path}"/bin/activate &> /dev/null
else
term_sd_echo "虚拟环境文件损坏"
is_venv_broken=1
fi
# 检测虚拟环境是否有问题
if [[ ! -d "${VIRTUAL_ENV}" ]] \
|| [[ ! "$(term_sd_win2unix_path "${VIRTUAL_ENV}")" == "${venv_path}" ]] \
|| [[ "${is_venv_broken}" == 1 ]]; then
term_sd_echo "检测虚拟环境出现异常, 尝试修复中"
exit_venv &> /dev/null
fix_venv "$@" # 修复虚拟环境
# 重新进入虚拟环境
if [[ -f "${venv_path}/Scripts/activate" ]]; then # 在 Windows 端的 venv 目录结构和 Linux, MacoOS 的不同, 所以进入虚拟环境的方式有区别
. "${venv_path}"/Scripts/activate &> /dev/null
elif [[ -f "${venv_path}/bin/activate" ]]; then
. "${venv_path}"/bin/activate &> /dev/null
fi
fi
pip_package_manager_update
fi
}
# 退出虚拟环境功能(方法来自 Python 官方的退出虚拟环境脚本)
exit_venv() {
if [[ ! -z "${VIRTUAL_ENV}" ]]; then # 检测是否在虚拟环境中
term_sd_echo "退出虚拟环境"
# reset old environment variables
if [ -n "${_OLD_VIRTUAL_PATH:-}" ] ; then
PATH="${_OLD_VIRTUAL_PATH:-}"
export PATH
unset _OLD_VIRTUAL_PATH
fi
if [ -n "${_OLD_VIRTUAL_PYTHONHOME:-}" ] ; then
PYTHONHOME="${_OLD_VIRTUAL_PYTHONHOME:-}"
export PYTHONHOME
unset _OLD_VIRTUAL_PYTHONHOME
fi
# This should detect bash and zsh, which have a hash command that must
# be called to get it to forget past commands. Without forgetting
# past commands the $PATH changes we made may not be respected
if [ -n "${BASH:-}" -o -n "${ZSH_VERSION:-}" ] ; then
hash -r 2> /dev/null
fi
if [ -n "${_OLD_VIRTUAL_PS1:-}" ] ; then
PS1="${_OLD_VIRTUAL_PS1:-}"
export PS1
unset _OLD_VIRTUAL_PS1
fi
unset VIRTUAL_ENV
unset VIRTUAL_ENV_PROMPT
if [ ! "${1:-}" = "nondestructive" ] ; then
# Self destruct!
unset -f deactivate
fi
term_sd_echo "退出虚拟环境完成"
fi
}
# 更新虚拟环境中的 Pip 包管理器
pip_package_manager_update() {
local upgrade_status
upgrade_status=$(term_sd_python "${START_PATH}/term-sd/python_modules/check_pip_need_upgrade.py" --pip-mininum-ver "${TERM_SD_PIP_MININUM_VER}")
if [[ "${ENABLE_PIP_VER_CHECK}" == 1 ]]; then
term_sd_echo "开始更新 Pip 包管理器"
term_sd_pip install --upgrade pip
if [[ "$?" == 0 ]]; then
term_sd_echo "Pip 包管理器更新成功"
else
term_sd_echo "Pip 包管理器更新失败"
fi
elif [[ "${upgrade_status}" == "True" ]]; then
term_sd_echo "开始更新 Pip 包管理器"
term_sd_pip install --upgrade pip
if [[ "$?" == 0 ]]; then
term_sd_echo "Pip 包管理器更新成功"
else
term_sd_echo "Pip 包管理器更新失败"
fi
fi
}
# 如果启用了虚拟环境, 则返回 0
is_use_venv() {
if [[ "${ENABLE_VENV}" == 1 ]]; then
return 0
else
return 1
fi
}
|
2301_81996401/term-sd
|
modules/python_venv.sh
|
Shell
|
agpl-3.0
| 8,516
|
#!/bin/bash
# SD WebUI 虚拟环境重构功能
# 使用 TERM_SD_MANAGE_OBJECT 全局变量显示要管理的 AI 软件名
# 使用 GITHUB_MIRROR 全局变量来使用 Github 镜像源
sd_webui_venv_rebuild() {
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否重新构建 Stable-Diffusion-WebUI 的虚拟环境 ?"; then
term_sd_print_line "${TERM_SD_MANAGE_OBJECT} 虚拟环境重建"
term_sd_tmp_disable_proxy
term_sd_echo "开始重新构建 Stable-Diffusion-WebUI 的虚拟环境"
term_sd_echo "删除原有虚拟环境中"
rm -rf "${SD_WEBUI_ROOT_PATH}/venv"
term_sd_echo "删除完成"
create_venv "${SD_WEBUI_ROOT_PATH}"
enter_venv "${SD_WEBUI_ROOT_PATH}"
install_pytorch # 安装 PyTorch
install_python_package git+$(git_format_repository_url "${GITHUB_MIRROR}" https://github.com/openai/CLIP)
install_python_package -r requirements_versions.txt # 安装stable-diffusion-webui的依赖
term_sd_echo "重新构建 Stable-Diffusion-WebUI 的虚拟环境结束"
exit_venv
term_sd_tmp_enable_proxy
term_sd_pause
fi
clean_install_config # 清理安装参数
}
# ComfyUI 虚拟环境重构功能
# 使用 TERM_SD_MANAGE_OBJECT 全局变量显示要管理的 AI 软件名
comfyui_venv_rebuild() {
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否重新构建 ComfyUI 的虚拟环境 ?"; then
term_sd_print_line "${TERM_SD_MANAGE_OBJECT} 虚拟环境重建"
term_sd_tmp_disable_proxy
term_sd_echo "开始重新构建 ComfyUI 的虚拟环境"
term_sd_echo "删除原有虚拟环境中"
rm -rf "${COMFYUI_ROOT_PATH}/venv"
term_sd_echo "删除完成"
create_venv "${COMFYUI_ROOT_PATH}"
enter_venv "${COMFYUI_ROOT_PATH}"
install_pytorch # 安装 PyTorch
install_python_package -r requirements.txt
term_sd_echo "重新构建 ComfyUI 的虚拟环境结束"
exit_venv
term_sd_tmp_enable_proxy
term_sd_pause
fi
clean_install_config # 清理安装参数
}
# InvokeAI 虚拟环境重构功能
# 使用 TERM_SD_MANAGE_OBJECT 全局变量显示要管理的 AI 软件名
invokeai_venv_rebuild() {
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否重新构建 InvokeAI 的虚拟环境 ?"; then
term_sd_print_line "${TERM_SD_MANAGE_OBJECT} 虚拟环境重建"
term_sd_tmp_disable_proxy
term_sd_echo "开始重新构建 InvokeAI 的虚拟环境"
term_sd_echo "删除原有虚拟环境中"
rm -rf "${INVOKEAI_ROOT_PATH}/venv"
term_sd_echo "删除完成"
create_venv "${INVOKEAI_ROOT_PATH}"
enter_venv "${INVOKEAI_ROOT_PATH}"
install_pytorch # 安装 PyTorch
install_python_package invokeai
term_sd_echo "重新构建 InvokeAI 的虚拟环境结束"
exit_venv
term_sd_tmp_enable_proxy
term_sd_pause
fi
clean_install_config # 清理安装参数
}
# Fooocus 虚拟环境重建功能
# 使用 TERM_SD_MANAGE_OBJECT 全局变量显示要管理的 AI 软件名
fooocus_venv_rebuild() {
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否重新构建 Fooocus 的虚拟环境 ?"; then
term_sd_print_line "${TERM_SD_MANAGE_OBJECT} 虚拟环境重建"
term_sd_tmp_disable_proxy
term_sd_echo "开始重新构建 Fooocus 的虚拟环境"
term_sd_echo "删除原有虚拟环境中"
rm -rf "${FOOOCUS_ROOT_PATH}/venv"
term_sd_echo "删除完成"
create_venv "${FOOOCUS_ROOT_PATH}"
enter_venv "${FOOOCUS_ROOT_PATH}"
install_pytorch # 安装 PyTorch
install_python_package -r requirements_versions.txt
term_sd_echo "重新构建 Fooocus 的虚拟环境结束"
exit_venv
term_sd_tmp_enable_proxy
term_sd_pause
fi
clean_install_config # 清理安装参数
}
# lora-scripts 虚拟环境重构功能
# 使用 TERM_SD_MANAGE_OBJECT 全局变量显示要管理的 AI 软件名
lora_scripts_venv_rebuild() {
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否重新构建 lora-scripts 的虚拟环境 ?"; then
term_sd_print_line "${TERM_SD_MANAGE_OBJECT} 虚拟环境重建"
term_sd_tmp_disable_proxy
term_sd_echo "开始重新构建 lora-scripts 的虚拟环境"
term_sd_echo "删除原有虚拟环境中"
rm -rf "${LORA_SCRIPTS_ROOT_PATH}/venv"
term_sd_echo "删除完成"
create_venv "${LORA_SCRIPTS_ROOT_PATH}"
enter_venv "${LORA_SCRIPTS_ROOT_PATH}"
install_pytorch # 安装 PyTorch
install_python_package -r requirements.txt # lora-scripts 依赖
term_sd_echo "重新构建 lora-scripts 的虚拟环境结束"
exit_venv
term_sd_tmp_enable_proxy
term_sd_pause
fi
clean_install_config # 清理安装参数
}
# kohya_ss 虚拟环境重建功能
# 使用 TERM_SD_MANAGE_OBJECT 全局变量显示要管理的 AI 软件名
kohya_ss_venv_rebuild() {
# 安装前的准备
download_mirror_select # 下载镜像源选择
pytorch_version_select # PyTorch 版本选择
pip_install_mode_select # 安装方式选择
if term_sd_install_confirm "是否重新构建 kohya_ss 的虚拟环境 ?"; then
term_sd_print_line "${TERM_SD_MANAGE_OBJECT} 虚拟环境重建"
term_sd_tmp_disable_proxy
term_sd_echo "开始重新构建 kohya_ss 的虚拟环境"
term_sd_echo "删除原有虚拟环境中"
rm -rf "${KOHYA_SS_ROOT_PATH}/venv"
term_sd_echo "删除完成"
create_venv "${KOHYA_SS_ROOT_PATH}"
enter_venv "${KOHYA_SS_ROOT_PATH}"
install_pytorch # 安装 PyTorch
install_python_package -r requirements.txt # kohya_ss 依赖
term_sd_echo "重新构建 kohya_ss 的虚拟环境结束"
exit_venv
term_sd_tmp_enable_proxy
term_sd_pause
fi
clean_install_config # 清理安装参数
}
|
2301_81996401/term-sd
|
modules/python_venv_rebuild.sh
|
Shell
|
agpl-3.0
| 6,812
|
#!/bin/bash
# SD WebUI 启动分支判断
sd_webui_launch() {
term_sd_echo "检测 Stable-Diffusion-WebUI 分支中"
case "$(git remote get-url origin | awk -F '/' '{print $NF}')" in # 分支判断
stable-diffusion-webui|stable-diffusion-webui.git)
a1111_sd_webui_launch
;;
automatic|automatic.git)
vlad_sd_webui_launch
;;
stable-diffusion-webui-directml|stable-diffusion-webui-directml.git|stable-diffusion-webui-amdgpu|stable-diffusion-webui-amdgpu.git)
sd_webui_directml_launch
;;
stable-diffusion-webui-forge|stable-diffusion-webui-forge.git)
sd_webui_forge_launch
;;
stable-diffusion-webui-reForge|stable-diffusion-webui-reForge.git)
sd_webui_reforge_launch
;;
sd-webui-forge-classic|sd-webui-forge-classic.git)
sd_webui_forge_classic_launch
;;
*)
a1111_sd_webui_launch
;;
esac
}
|
2301_81996401/term-sd
|
modules/sd_webui_branch.sh
|
Shell
|
agpl-3.0
| 1,022
|
#!/bin/bash
# SD WebUI 分支切换功能
# 使用 GITHUB_MIRROR 环境变量设置 GIthub 镜像源
sd_webui_branch_switch() {
local sd_webui_branch
local dialog_arg
local remote_url
case "$(git remote get-url origin | awk -F '/' '{print $NF}')" in # 分支判断
stable-diffusion-webui|stable-diffusion-webui.git)
sd_webui_branch="AUTOMATIC1111 webui $(git_branch_display)"
;;
automatic|automatic.git)
sd_webui_branch="vladmandic webui $(git_branch_display)"
;;
stable-diffusion-webui-directml|stable-diffusion-webui-directml.git|stable-diffusion-webui-amdgpu|stable-diffusion-webui-amdgpu.git)
sd_webui_branch="lshqqytiger webui $(git_branch_display)"
;;
stable-diffusion-webui-forge|stable-diffusion-webui-forge.git)
sd_webui_branch="lllyasviel webui $(git_branch_display)"
;;
stable-diffusion-webui-reForge|stable-diffusion-webui-reForge.git)
sd_webui_branch="Panchovix webui $(git_branch_display)"
;;
sd-webui-forge-classic|sd-webui-forge-classic.git)
sd_webui_branch="Haoming02 webui $(git_branch_display)"
;;
*)
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 更新结果" \
--ok-label "确认" \
--msgbox "Stable-Diffusion-WebUI 非 Git 安装, 无法切换分支" \
$(get_dialog_size)
return 10
;;
esac
download_mirror_select # 切换前选择 Github 源
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 分支切换选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择要切换的 Stable-Diffusion-WebUI 分支\n当前更新源: $(git_remote_display)\n当前分支: ${sd_webui_branch}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> AUTOMATIC1111 - Stable-Diffusion-WebUI 主分支" \
"2" "> AUTOMATIC1111 - Stable-Diffusion-WebUI 测试分支" \
"3" "> lllyasviel - Stable-Diffusion-WebUI-Forge 分支" \
"4" "> Panchovix - Stable-Diffusion-WebUI-reForge 主分支" \
"5" "> Panchovix - Stable-Diffusion-WebUI-reForge 测试分支" \
"6" "> Haoming02 - Stable-Diffusion-WebUI-Forge-Classic 分支" \
"7" "> Haoming02 - Stable-Diffusion-WebUI-Forge-Neo 分支" \
"8" "> lshqqytiger - Stable-Diffusion-WebUI-AMDGPU 分支" \
"9" "> vladmandic - SD.NEXT 主分支" \
"10" "> vladmandic - SD.NEXT 测试分支" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
term_sd_print_line "Stable-Diffusion-WebUI 分支切换"
term_sd_echo "切换到 AUTOMATIC1111 - Stable-Diffusion-WebUI 主分支"
remote_url=$(git_format_repository_url "${GITHUB_MIRROR}" https://github.com/AUTOMATIC1111/stable-diffusion-webui)
git_switch_branch "${remote_url}" master
if [[ "$?" == 0 ]]; then
mv -f "${SD_WEBUI_ROOT_PATH}"/repositories/blip "${SD_WEBUI_ROOT_PATH}"/repositories/BLIP &> /dev/null
term_sd_echo "Stable-Diffusion-WebUI 分支切换完成"
else
term_sd_echo "Stable-Diffusion-WebUI 分支切换失败"
fi
term_sd_pause
;;
2)
term_sd_print_line "Stable-Diffusion-WebUI 分支切换"
term_sd_echo "切换到 AUTOMATIC1111 - Stable-Diffusion-WebUI 测试分支"
remote_url=$(git_format_repository_url "${GITHUB_MIRROR}" https://github.com/AUTOMATIC1111/stable-diffusion-webui)
git_switch_branch "${remote_url}" dev
if [[ "$?" == 0 ]]; then
mv -f "${SD_WEBUI_ROOT_PATH}"/repositories/blip "${SD_WEBUI_ROOT_PATH}"/repositories/BLIP &> /dev/null
term_sd_echo "Stable-Diffusion-WebUI 分支切换完成"
else
term_sd_echo "Stable-Diffusion-WebUI 分支切换失败"
fi
term_sd_pause
;;
3)
term_sd_print_line "Stable-Diffusion-WebUI 分支切换"
term_sd_echo "切换到 lllyasviel - Stable-Diffusion-WebUI-Forge 主分支"
remote_url=$(git_format_repository_url "${GITHUB_MIRROR}" https://github.com/lllyasviel/stable-diffusion-webui-forge)
git_switch_branch "${remote_url}" main
if [[ "$?" == 0 ]]; then
mv -f "${SD_WEBUI_ROOT_PATH}"/repositories/blip "${SD_WEBUI_ROOT_PATH}"/repositories/BLIP &> /dev/null
term_sd_echo "Stable-Diffusion-WebUI 分支切换完成"
else
term_sd_echo "Stable-Diffusion-WebUI 分支切换失败"
fi
term_sd_pause
;;
4)
term_sd_print_line "Stable-Diffusion-WebUI 分支切换"
term_sd_echo "切换到 Panchovix - Stable-Diffusion-WebUI-reForge 主分支"
remote_url=$(git_format_repository_url "${GITHUB_MIRROR}" https://github.com/Panchovix/stable-diffusion-webui-reForge)
git_switch_branch "${remote_url}" main
if [[ "$?" == 0 ]]; then
mv -f "${SD_WEBUI_ROOT_PATH}"/repositories/blip "${SD_WEBUI_ROOT_PATH}"/repositories/BLIP &> /dev/null
term_sd_echo "Stable-Diffusion-WebUI 分支切换完成"
else
term_sd_echo "Stable-Diffusion-WebUI 分支切换失败"
fi
term_sd_pause
;;
5)
term_sd_print_line "Stable-Diffusion-WebUI 分支切换"
term_sd_echo "切换到 Panchovix - Stable-Diffusion-WebUI-reForge 测试分支"
remote_url=$(git_format_repository_url "${GITHUB_MIRROR}" https://github.com/Panchovix/stable-diffusion-webui-reForge)
git_switch_branch "${remote_url}" dev_upstream
if [[ "$?" == 0 ]]; then
mv -f "${SD_WEBUI_ROOT_PATH}"/repositories/blip "${SD_WEBUI_ROOT_PATH}"/repositories/BLIP &> /dev/null
term_sd_echo "Stable-Diffusion-WebUI 分支切换完成"
else
term_sd_echo "Stable-Diffusion-WebUI 分支切换失败"
fi
term_sd_pause
;;
6)
term_sd_print_line "Stable-Diffusion-WebUI 分支切换"
term_sd_echo "切换到 Haoming02 - Stable-Diffusion-WebUI-Forge-Classic 分支"
remote_url=$(git_format_repository_url "${GITHUB_MIRROR}" https://github.com/Haoming02/sd-webui-forge-classic)
git_switch_branch "${remote_url}" classic
if [[ "$?" == 0 ]]; then
mv -f "${SD_WEBUI_ROOT_PATH}"/repositories/blip "${SD_WEBUI_ROOT_PATH}"/repositories/BLIP &> /dev/null
term_sd_echo "Stable-Diffusion-WebUI 分支切换完成"
else
term_sd_echo "Stable-Diffusion-WebUI 分支切换失败"
fi
term_sd_pause
;;
7)
term_sd_print_line "Stable-Diffusion-WebUI 分支切换"
term_sd_echo "切换到 Haoming02 - Stable-Diffusion-WebUI-Forge-Neo 分支"
remote_url=$(git_format_repository_url "${GITHUB_MIRROR}" https://github.com/Haoming02/sd-webui-forge-classic)
git_switch_branch "${remote_url}" neo
if [[ "$?" == 0 ]]; then
mv -f "${SD_WEBUI_ROOT_PATH}"/repositories/blip "${SD_WEBUI_ROOT_PATH}"/repositories/BLIP &> /dev/null
term_sd_echo "Stable-Diffusion-WebUI 分支切换完成"
else
term_sd_echo "Stable-Diffusion-WebUI 分支切换失败"
fi
term_sd_pause
;;
8)
term_sd_print_line "Stable-Diffusion-WebUI 分支切换"
term_sd_echo "切换到 lshqqytiger - Stable-Diffusion-WebUI-AMDGPU 主分支"
remote_url=$(git_format_repository_url "${GITHUB_MIRROR}" https://github.com/lshqqytiger/stable-diffusion-webui-amdgpu)
git_switch_branch "${remote_url}" master
if [[ "$?" == 0 ]]; then
mv -f "${SD_WEBUI_ROOT_PATH}"/repositories/blip "${SD_WEBUI_ROOT_PATH}"/repositories/BLIP &> /dev/null
term_sd_echo "Stable-Diffusion-WebUI 分支切换完成"
else
term_sd_echo "Stable-Diffusion-WebUI 分支切换失败"
fi
term_sd_pause
;;
9)
term_sd_print_line "Stable-Diffusion-WebUI 分支切换"
term_sd_echo "切换到 vladmandic - SD.NEXT 主分支"
remote_url=$(git_format_repository_url "${GITHUB_MIRROR}" https://github.com/vladmandic/sdnext)
git_switch_branch "${remote_url}" master --submod
if [[ "$?" == 0 ]]; then
mv -f "${SD_WEBUI_ROOT_PATH}"/repositories/BLIP "${SD_WEBUI_ROOT_PATH}"/repositories/blip &> /dev/null
term_sd_echo "Stable-Diffusion-WebUI 分支切换完成"
else
term_sd_echo "Stable-Diffusion-WebUI 分支切换失败"
fi
term_sd_pause
;;
10)
term_sd_print_line "Stable-Diffusion-WebUI 分支切换"
term_sd_echo "切换到 vladmandic - SD.NEXT 测试分支"
remote_url=$(git_format_repository_url "${GITHUB_MIRROR}" https://github.com/vladmandic/sdnext)
git_switch_branch "${remote_url}" dev --submod
if [[ "$?" == 0 ]]; then
mv -f "${SD_WEBUI_ROOT_PATH}"/repositories/BLIP "${SD_WEBUI_ROOT_PATH}"/repositories/blip &> /dev/null
term_sd_echo "Stable-Diffusion-WebUI 分支切换完成"
else
term_sd_echo "Stable-Diffusion-WebUI 分支切换失败"
fi
term_sd_pause
;;
esac
clean_install_config # 清理安装参数
}
|
2301_81996401/term-sd
|
modules/sd_webui_branch_switch.sh
|
Shell
|
agpl-3.0
| 10,056
|
#!/bin/bash
# SD WebUI DirectML 启动参数配置
# 启动参数将保存在 <Start Path>/term-sd/config/sd-webui-directml-launch.conf
sd_webui_directml_launch_args_setting() {
local dialog_arg
local arg
local launch_args
local i
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--checklist "请选择 Stable-Diffusion-WebUI-DirectML 启动参数, 确认之后将覆盖原有启动参数配置" \
$(get_dialog_size_menu) \
"1" "(update-all-extensions) 启动时更新所有扩展" OFF \
"2" "(skip-python-version-check) 跳过检查 Python 版本" OFF \
"3" "(skip-torch-cuda-test) 跳过 CUDA 可用性检查" OFF \
"4" "(reinstall-xformers) 启动时重新安装 xFormers" OFF \
"5" "(reinstall-torch) 启动时重新安装 PyTorch" OFF \
"6" "(update-check) 启动时检查更新" OFF \
"7" "(test-server) 配置测试服务器" OFF \
"8" "(log-startup) 显示详细启动日志" OFF \
"9" "(skip-prepare-environment) 跳过所有环境准备工作" OFF \
"10" "(skip-install) 跳过软件包的安装" OFF \
"11" "(dump-sysinfo) 将系统信息文件保存到磁盘并退出" OFF \
"12" "(do-not-download-clip) 跳过下载 CLIP 模型" OFF \
"13" "(no-half) 关闭 UNet 半精度优化" OFF \
"14" "(no-half-vae) 关闭 VAE 模型半精度优化" OFF \
"15" "(no-progressbar-hiding) 不隐藏 Gradio UI 中进度条" OFF \
"16" "(allow-code) 允许从 WebUI 执行自定义脚本" OFF \
"17" "(medvram) 启用显存优化 (显存 < 6g 时推荐使用)" OFF \
"18" "(medvram-sdxl) 仅在 SDXL 模型启用显存优化 (显存 < 8g 时推荐使用)" OFF \
"19" "(lowvram) 启用显存优化 (显存 < 4g时推荐使用)" OFF \
"20" "(lowram) 将模型加载到显存中而不是内存中" OFF \
"21" "(precision full) 使用模型全精度" OFF \
"22" "(upcast-sampling) 使用向上采样法提高精度" OFF \
"23" "(share) 通过 Gradio 共享" OFF \
"24" "(enable-insecure-extension-access) 允许在开放远程访问时安装插件" OFF \
"25" "(xformers) 尝试使用 xFormers 优化" OFF \
"26" "(force-enable-xformers) 强制使用 xFormers 优化" OFF \
"27" "(xformers-flash-attention) 使用 xFormers-Flash 优化 (仅支持 SD2.x 以上)" OFF \
"28" "(opt-split-attention) 使用 Opt-Split 优化" OFF \
"29" "(opt-sub-quad-attention) 使用 Opt-Sub-Quad优化" OFF \
"30" "(opt-split-attention-invokeai) 使用 Opt-Sub-Quad-InvokeAI 优化" OFF \
"31" "(opt-split-attention-v1) 使用 Opt-Sub-Quad-V1优化" OFF \
"32" "(opt-sdp-attention) 使用 Opt-Sdp优化(仅限 PyTorch2.0 以上)" OFF \
"33" "(opt-sdp-no-mem-attention) 使用无高效内存使用的 Opt-Sdp 优化" OFF \
"34" "(disable-opt-split-attention) 禁用 Opt-Split 优化" OFF \
"35" "(disable-nan-check) 禁用潜空间 NAN 检查" OFF \
"36" "(use-cpu) 使用 CPU 进行生图" OFF \
"37" "(disable-model-loading-ram-optimization) 禁用减少内存使用的优化" OFF \
"38" "(listen) 开放远程连接" OFF \
"39" "(hide-ui-dir-config) 隐藏 WebUI 目录配置" OFF \
"40" "(freeze-settings) 冻结 WebUI 设置" OFF \
"41" "(gradio-debug) 以 Debug 模式启用 Gradio" OFF \
"42" "(opt-channelslast) 使用 ChannelsLast 内存格式优化" OFF \
"43" "(autolaunch) 启动 WebUI 完成后自动启动浏览器" OFF \
"44" "(theme dark) 使用黑暗主题" OFF \
"45" "(use-textbox-seed) 使用文本框在 WebUI 中生成的种子" OFF \
"46" "(disable-console-progressbars) 禁用控制台进度条显示" OFF \
"47" "(enable-console-prompts) 启用在生图时输出提示词到控制台" OFF \
"48" "(disable-safe-unpickle) 禁用检查模型是否包含恶意代码" OFF \
"49" "(api) 启用 API" OFF \
"50" "(api-log) 启用输出所有 API 请求的日志记录" OFF \
"51" "(nowebui) 不加载 WebUI 界面" OFF \
"52" "(onnx) 使用 ONNX 模型" OFF \
"53" "(olive) 使用 OLIVE 模型" OFF \
"54" "(backend cuda) 使用 CUDA 作为后端进行生图" OFF \
"55" "(backend rocm) 使用 ROCM 作为后端进行生图" OFF \
"56" "(backend directml) 使用 DirectML 作为后端进行生图" OFF \
"57" "(ui-debug-mode) 不加载模型启动 WebUI (UI Debug)" OFF \
"58" "(administrator) 启用管理员权限" OFF \
"59" "(disable-tls-verify) 禁用 TLS 证书验证" OFF \
"60" "(no-gradio-queue) 禁用 Gradio 队列" OFF \
"61" "(skip-version-check) 禁用 PyTorch, xFormers 版本检查" OFF \
"62" "(no-hashing) 禁用模型 Hash 检查" OFF \
"63" "(no-download-sd-model) 禁用自动下载模型, 即使模型路径无模型" OFF \
"64" "(add-stop-route) 添加 /_stop 路由以停止服务器" OFF \
"65" "(api-server-stop) 通过 API 启用服务器停止 / 重启 / 终止功能" OFF \
"66" "(disable-all-extensions) 禁用所有扩展运行" OFF \
"67" "(disable-extra-extensions) 禁用非内置的扩展运行" OFF \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
for i in ${dialog_arg}; do
case "${i}" in
1)
arg="--update-all-extensions"
;;
2)
arg="--skip-python-version-check"
;;
3)
arg="--skip-torch-cuda-test"
;;
4)
arg="--reinstall-xformers"
;;
5)
arg="--reinstall-torch"
;;
6)
arg="--update-check"
;;
7)
arg="--test-server"
;;
8)
arg="--log-startup"
;;
9)
arg="--skip-prepare-environment"
;;
10)
arg="--skip-install"
;;
11)
arg="--dump-sysinfo"
;;
12)
arg="--do-not-download-clip"
;;
13)
arg="--no-half"
;;
14)
arg="--no-half-vae"
;;
15)
arg="--no-progressbar-hiding"
;;
16)
arg="--allow-code"
;;
17)
arg="--medvram"
;;
18)
arg="--medvram-sdxl"
;;
19)
arg="--lowvram"
;;
20)
arg="--lowram"
;;
21)
arg="--precision full"
;;
22)
arg="--upcast-sampling"
;;
23)
arg="--share"
;;
24)
arg="--enable-insecure-extension-access"
;;
25)
arg="--xformers"
;;
26)
arg="--force-enable-xformers"
;;
27)
arg="--xformers-flash-attention"
;;
28)
arg="--opt-split-attention"
;;
29)
arg="--opt-sub-quad-attention"
;;
30)
arg="--opt-split-attention-invokeai"
;;
31)
arg="--opt-split-attention-v1"
;;
32)
arg="--opt-sdp-attention"
;;
33)
arg="--opt-sdp-no-mem-attention"
;;
34)
arg="--disable-opt-split-attention"
;;
35)
arg="--disable-nan-check"
;;
36)
arg="--use-cpu all"
;;
37)
arg="--disable-model-loading-ram-optimization"
;;
38)
arg="--listen"
;;
39)
arg="--hide-ui-dir-config"
;;
40)
arg="--freeze-settings"
;;
41)
arg="--gradio-debug"
;;
42)
arg="--opt-channelslast"
;;
43)
arg="--autolaunch"
;;
44)
arg="--theme dark"
;;
45)
arg="--use-textbox-seed"
;;
46)
arg="--disable-console-progressbars"
;;
47)
arg="--enable-console-prompts"
;;
48)
arg="--disable-safe-unpickle"
;;
49)
arg="--api"
;;
50)
arg="--api-log"
;;
51)
arg="--nowebui"
;;
52)
arg="--onnx"
;;
53)
arg="--olive"
;;
54)
arg="--backend cuda"
;;
55)
arg="--backend rocm"
;;
56)
arg="--backend directml"
;;
57)
arg="--ui-debug-mode"
;;
58)
arg="--administrator"
;;
59)
arg="--disable-tls-verify"
;;
60)
arg="--no-gradio-queue"
;;
61)
arg="--skip-version-check"
;;
62)
arg="--no-hashing"
;;
63)
arg="--no-download-sd-model"
;;
64)
arg="--add-stop-route"
;;
65)
arg="--api-server-stop"
;;
66)
arg="--disable-all-extensions"
;;
67)
arg="--disable-extra-extensions"
;;
esac
launch_args="${arg} ${launch_args}"
done
# 生成启动脚本
term_sd_echo "设置 Stable-Diffusion-WebUI-DirectML 启动参数: ${launch_args}"
echo "launch.py ${launch_args}" > "${START_PATH}"/term-sd/config/sd-webui-directml-launch.conf
else
term_sd_echo "取消设置 Stable-Diffusion-WebUI-DirectML 启动参数"
fi
}
# SD WebUI DirectML 启动界面
sd_webui_directml_launch() {
local dialog_arg
local launch_args
add_sd_webui_directml_normal_launch_args
while true; do
launch_args=$(cat "${START_PATH}"/term-sd/config/sd-webui-directml-launch.conf)
if is_use_venv; then
launch_args="python ${launch_args}"
else
launch_args="${TERM_SD_PYTHON_PATH} ${launch_args}"
fi
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 启动选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择启动 Stable-Diffusion-WebUI-DirectML / 修改 Stable-Diffusion-WebUI-DirectML 启动参数\n当前启动参数: ${launch_args}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 配置预设启动参数" \
"3" "> 修改自定义启动参数" \
"4" "> 重置启动参数" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
term_sd_launch
;;
2)
sd_webui_directml_launch_args_setting
;;
3)
sd_webui_directml_launch_args_revise
;;
4)
restore_sd_webui_directml_launch_args
;;
*)
break
;;
esac
done
}
# SD WebUI DirectML 修改启动参数功能
# 修改前从 <Start Path>/term-sd/config/sd-webui-directml-launch.conf 读取启动参数
# 可从上次的基础上修改
sd_webui_directml_launch_args_revise() {
local dialog_arg
local launch_args
launch_args=$(cat "${START_PATH}"/term-sd/config/sd-webui-directml-launch.conf | awk '{sub("launch.py ","")}1')
dialog_arg=$(dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 自定义启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "请输入 Stable-Diffusion-WebUI-DirectML 启动参数" \
$(get_dialog_size) \
"${launch_args}" \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
term_sd_echo "设置 Stable-Diffusion-WebUI-DirectML 启动参数: $dialog_arg"
echo "launch.py $dialog_arg" > "${START_PATH}"/term-sd/config/sd-webui-directml-launch.conf
else
term_sd_echo "取消修改 Stable-Diffusion-WebUI-DirectML 启动参数"
fi
}
# 添加默认启动参数配置
add_sd_webui_directml_normal_launch_args() {
if [[ ! -f "${START_PATH}/term-sd/config/sd-webui-directml-launch.conf" ]]; then # 找不到启动配置时默认生成一个
echo "launch.py --theme dark --autolaunch --api --skip-torch-cuda-test --backend directml" > "${START_PATH}"/term-sd/config/sd-webui-directml-launch.conf
fi
}
# 重置启动参数
restore_sd_webui_directml_launch_args() {
if (dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 重置启动参数选项选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重置 Stable-Diffusion-WebUI 启动参数" \
$(get_dialog_size)); then
term_sd_echo "重置启动参数"
rm -f "${START_PATH}"/term-sd/config/sd-webui-directml-launch.conf
add_sd_webui_directml_normal_launch_args
else
term_sd_echo "取消重置操作"
fi
}
|
2301_81996401/term-sd
|
modules/sd_webui_directml_launch.sh
|
Shell
|
agpl-3.0
| 15,428
|
#!/bin/bash
# SD WebUI 插件管理器
sd_webui_extension_manager() {
local dialog_arg
if [[ ! -d "${SD_WEBUI_ROOT_PATH}"/extensions ]]; then
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件管理选项" \
--ok-label "确认" \
--msgbox "Stable-Diffusion-WebUI 插件目录, 请检查 Stable-Diffusion-WebUI 是否安装完整" \
$(get_dialog_size)
return 1
fi
while true; do
cd "${SD_WEBUI_ROOT_PATH}"/extensions #回到最初路径
# 功能选择界面
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择 Stable-Diffusion-WebUI 插件管理选项的功能" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 安装插件" \
"2" "> 管理插件" \
"3" "> 更新全部插件" \
3>&1 1>&2 2>&3 )
case "${dialog_arg}" in
1)
# 选择安装
sd_webui_extension_install
;;
2)
# 选择管理
sd_webui_extension_list
;;
3)
# 选择更新全部插件
if (dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件管理" \
--yes-label "是" --no-label "否" \
--yesno "是否更新所有 Stable-Diffusion-WebUI 插件 ?" \
$(get_dialog_size)); then
update_all_extension
fi
;;
*)
break
;;
esac
done
}
# SD WebUI 插件安装
sd_webui_extension_install() {
local repo_url
local name
repo_url=$(dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件安装选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "请输入插件的 Github 地址或其他下载地址" \
$(get_dialog_size) \
3>&1 1>&2 2>&3)
if [ ! -z "${repo_url}" ]; then
name=$(basename "${repo_url}" | awk -F '.git' '{print $1}')
term_sd_echo "安装 ${name} 插件中"
if ! term_sd_is_git_repository_exist "${repo_url}" ;then
term_sd_try git clone --recurse-submodules "${repo_url}"
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件安装结果" \
--ok-label "确认" \
--msgbox "${name} 插件安装成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件安装结果" \
--ok-label "确认" \
--msgbox "${name} 插件安装失败" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件安装结果" \
--ok-label "确认" \
--msgbox "${name} 插件已存在" \
$(get_dialog_size)
fi
else
term_sd_echo "输入的 Stable-Diffusion-WebUI 插件安装地址为空"
fi
}
# 插件列表浏览器
sd_webui_extension_list() {
local extension_name
while true; do
cd "${SD_WEBUI_ROOT_PATH}"/extensions #回到最初路径
get_dir_folder_list # 获取当前目录下的所有文件夹
if term_sd_is_bash_ver_lower; then # Bash 版本低于 4 时使用旧版列表显示方案
extension_name=$(dialog --erase-on-exit \
--ok-label "确认" --cancel-label "取消" \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件列表" \
--menu "使用上下键选择要操作的插件并回车确认" \
$(get_dialog_size_menu) \
"-->返回<--" "<---------" \
"${LOCAL_DIR_LIST}" \
3>&1 1>&2 2>&3)
else
extension_name=$(dialog --erase-on-exit \
--ok-label "确认" --cancel-label "取消" \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件列表" \
--menu "使用上下键选择要操作的插件并回车确认" \
$(get_dialog_size_menu) \
"-->返回<--" "<---------" \
"${LOCAL_DIR_LIST[@]}" \
3>&1 1>&2 2>&3)
fi
if [[ "$?" == 0 ]]; then
if [[ "${extension_name}" == "-->返回<--" ]]; then
break
elif [[ -d "${extension_name}" ]]; then # 选择文件夹
cd "${extension_name}"
sd_webui_extension_interface "${extension_name}"
fi
else
break
fi
done
unset LOCAL_DIR_LIST
}
# 插件管理功能
# 使用:
# sd_webui_extension_interface <插件文件名>
sd_webui_extension_interface() {
local dialog_arg
local extension_name=$@
local extension_status
local dialog_buttom
local status_display
while true; do
if is_sd_webui_extension_disabled "${extension_name}"; then
extension_status=0
dialog_buttom="启用"
status_display="已禁用"
else
extension_status=1
dialog_buttom="禁用"
status_display="已启用"
fi
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件管理选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择对 ${extension_name} 插件的管理功能\n当前更新源: $(git_remote_display)\n当前分支: $(git_branch_display)\n当前状态: ${status_display}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 更新" \
"2" "> 修复更新" \
"3" "> 版本切换" \
"4" "> 更新源切换" \
"5" "> ${dialog_buttom}插件" \
"6" "> 卸载" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
if is_git_repo; then
term_sd_echo "更新 $(echo ${extension_name} | awk -F "/" '{print $NF}') 插件中"
git_pull_repository
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件更新结果" \
--ok-label "确认" \
--msgbox "${extension_name} 插件更新成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件更新结果" \
--ok-label "确认" \
--msgbox "${extension_name} 插件更新失败" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件更新结果" \
--ok-label "确认" \
--msgbox "${extension_name} 插件非 Git 安装, 无法更新" \
$(get_dialog_size)
fi
;;
2)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件修复更新" \
--yes-label "是" --no-label "否" \
--yesno "是否修复 ${extension_name} 插件更新 ?" \
$(get_dialog_size)); then
git_fix_pointer_offset
fi
else
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件修复更新" \
--ok-label "确认" \
--msgbox "${extension_name} 插件非 Git 安装, 无法修复更新" \
$(get_dialog_size)
fi
;;
3)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件版本切换" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 ${extension_name} 插件版本 ?" \
$(get_dialog_size)); then
git_ver_switch
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 自定义节点版本切换" \
--ok-label "确认" \
--msgbox "${extension_name} 自定义节点版本切换完成, 当前版本为: $(git_branch_display)" \
$(get_dialog_size)
fi
else
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件版本切换" \
--ok-label "确认" \
--msgbox "${extension_name} 插件非 Git 安装, 无法进行版本切换" \
$(get_dialog_size)
fi
;;
4)
if is_git_repo; then
if (dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件更新源切换" \
--yes-label "是" --no-label "否" \
--yesno "是否切换 ${extension_name} 插件更新源 ?" \
$(get_dialog_size)); then
git_remote_url_select_single
fi
else
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件更新源切换" \
--ok-label "确认" \
--msgbox "${extension_name} 插件非 Git 安装, 无法进行更新源切换" \
$(get_dialog_size)
fi
;;
5)
if [[ "${extension_status}" == 0 ]]; then
if (dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件更新源切换" \
--yes-label "是" --no-label "否" \
--yesno "是否启用 ${extension_name} 插件 ?" \
$(get_dialog_size)); then
switch_sd_webui_enable_extension_status "${extension_name}"
else
continue
fi
else
if (dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件更新源切换" \
--yes-label "是" --no-label "否" \
--yesno "是否禁用 ${extension_name} 插件 ?" \
$(get_dialog_size)); then
switch_sd_webui_enable_extension_status "${extension_name}"
else
continue
fi
fi
if [[ "$?" == 0 ]]; then
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件删除选项" \
--ok-label "确认" \
--msgbox "${dialog_buttom} ${extension_name} 插件成功" \
$(get_dialog_size)
else
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件删除选项" \
--ok-label "确认" \
--msgbox "${dialog_buttom} ${extension_name} 插件失败" \
$(get_dialog_size)
fi
;;
6)
if (dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件删除选项" \
--yes-label "是" --no-label "否" \
--yesno "是否删除 ${extension_name} 插件 ?" \
$(get_dialog_size)); then
term_sd_echo "请再次确认是否删除 ${extension_name} (yes/no) ?"
term_sd_echo "警告: 该操作将永久删除 ${extension_name}"
term_sd_echo "提示: 输入 yes 或 no 后回车"
case "$(term_sd_read)" in
yes|y|YES|Y)
term_sd_echo "删除 ${extension_name} 插件中"
cd ..
rm -rf "${SD_WEBUI_ROOT_PATH}/extensions/${extension_name}"
dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 插件删除选项" \
--ok-label "确认" \
--msgbox "删除 ${extension_name} 插件完成" \
$(get_dialog_size)
break
;;
*)
term_sd_echo "取消删除 ${extension_name} 插件操作"
;;
esac
fi
;;
*)
break
;;
esac
done
}
# 切换插件的启用状态
# 使用:
# switch_sd_webui_enable_extension_status <插件名称>
# 通过修改 <SD WebUI Path>/config.json 文件调整插件的启用状态
# 当插件启用时, 执行该函数将禁用插件, 反过来同理
switch_sd_webui_enable_extension_status() {
local extension_name=$@
local status
if is_sd_webui_extension_disabled "${extension_name}"; then
# 插件被禁用时
term_sd_echo "尝试启用 ${extension_name} 插件"
status="True"
else
# 插件启用时
term_sd_echo "尝试禁用 ${extension_name} 插件"
status="False"
fi
if set_sd_webui_extension_status "${extension_name}" "${status}"; then
term_sd_echo "操作 ${extension_name} 插件成功"
return 0
else
term_sd_echo "操作 ${extension_name} 插件失败"
return 1
fi
}
# 查询插件是否被禁用
# 使用:
# is_sd_webui_extension_disabled <插件名>
is_sd_webui_extension_disabled() {
local config_path
local extension_name=$@
config_path="${SD_WEBUI_ROOT_PATH}/config.json"
# 没有配置文件时返回 1 说明插件未被禁用
if [[ ! -f "${config_path}" ]]; then
return 1
fi
result=$(term_sd_python "${START_PATH}/term-sd/python_modules/check_sd_webui_extension_disabled.py" \
--config-path "${config_path}" \
--extension "${extension_name}" \
)
if [[ "${result}" == "True" ]]; then
return 0
else
return 1
fi
}
# 修改插件的启用状态
# 使用:
# set_sd_webui_extension_status <插件名> <True / False>
set_sd_webui_extension_status() {
local extension_name=$1
local status=$2
local config_path
local result
config_path="${SD_WEBUI_ROOT_PATH}/config.json"
if [[ ! -f "${config_path}" ]]; then
echo "{}" > "${config_path}"
fi
result=$(term_sd_python "${START_PATH}/term-sd/python_modules/set_sd_webui_extension_status.py" \
--config-path "${config_path}" \
--extension "${extension_name}" \
--status "${status}" \
)
if [[ "${result}" == "True" ]]; then
return 0
else
return 1
fi
}
|
2301_81996401/term-sd
|
modules/sd_webui_extension_manager.sh
|
Shell
|
agpl-3.0
| 17,626
|
#!/bin/bash
# SD WebUI Forge Classic 启动参数配置
# 启动参数将保存在 <Start Path>/term-sd/config/sd-webui-forge-classic-launch.conf
sd_webui_forge_classic_launch_args_setting() {
local arg
local dialog_arg
local launch_args
local i
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--checklist "请选择 Stable-Diffusion-WebUI-Forge-Classic 启动参数, 确认之后将覆盖原有启动参数配置" \
$(get_dialog_size_menu) \
"1" "(update-all-extensions) 启动时更新所有扩展" OFF \
"2" "(skip-python-version-check) 跳过检查 Python 版本" OFF \
"3" "(skip-torch-cuda-test) 跳过 CUDA 可用性检查" OFF \
"4" "(reinstall-xformers) 启动时重新安装 xFormers" OFF \
"5" "(reinstall-torch) 启动时重新安装 PyTorch" OFF \
"6" "(update-check) 启动时检查更新" OFF \
"7" "(test-server) 配置测试服务器" OFF \
"8" "(log-startup) 显示详细启动日志" OFF \
"9" "(skip-prepare-environment) 跳过所有环境准备工作" OFF \
"10" "(skip-install) 跳过软件包的安装" OFF \
"11" "(dump-sysinfo) 将系统信息文件保存到磁盘并退出" OFF \
"12" "(do-not-download-clip) 跳过下载 CLIP 模型" OFF \
"13" "(no-half) 关闭 UNet 半精度优化" OFF \
"14" "(no-half-vae) 关闭 VAE 模型半精度优化" OFF \
"15" "(no-progressbar-hiding) 不隐藏 Gradio UI 中进度条" OFF \
"16" "(allow-code) 允许从 WebUI 执行自定义脚本" OFF \
"17" "(medvram) 启用显存优化 (显存 < 6g 时推荐使用)" OFF \
"18" "(medvram-sdxl) 仅在 SDXL 模型启用显存优化 (显存 < 8g 时推荐使用)" OFF \
"19" "(lowvram) 启用显存优化 (显存 < 4g 时推荐使用)" OFF \
"20" "(lowram) 将模型加载到显存中而不是内存中" OFF \
"21" "(precision full) 使用模型全精度" OFF \
"22" "(upcast-sampling) 使用向上采样法提高精度" OFF \
"23" "(share) 通过 Gradio 共享" OFF \
"24" "(enable-insecure-extension-access) 允许在开放远程访问时安装插件" OFF \
"25" "(xformers) 尝试使用 xFormers 优化" OFF \
"26" "(force-enable-xformers) 强制使用 xFormers 优化" OFF \
"27" "(xformers-flash-attention) 使用 xFormers-Flash优化 (仅支持 SD2.x 以上)" OFF \
"28" "(opt-split-attention) 使用 Split 优化" OFF \
"29" "(opt-sub-quad-attention) 使用 Sub-Quad 优化" OFF \
"30" "(opt-split-attention-invokeai) 使用 Sub-Quad-InvokeAI 优化" OFF \
"31" "(opt-split-attention-v1) 使用 Sub-Quad-V1 优化" OFF \
"32" "(opt-sdp-attention) 使用 Sdp 优化 (仅限 PyTorch2.0 以上)" OFF \
"33" "(opt-sdp-no-mem-attention) 使用无高效内存使用的 Sdp 优化" OFF \
"34" "(disable-opt-split-attention) 禁用 Split 优化" OFF \
"35" "(disable-nan-check) 禁用潜空间 NAN 检查" OFF \
"36" "(use-cpu) 使用 CPU 进行生图" OFF \
"37" "(disable-model-loading-ram-optimization) 禁用减少内存使用的优化" OFF \
"38" "(listen) 开放远程连接" OFF \
"39" "(hide-ui-dir-config) 隐藏 WebUI 目录配置" OFF \
"40" "(freeze-settings) 冻结 WebUI 设置" OFF \
"41" "(gradio-debug) 以 Debug 模式启用 Gradio" OFF \
"42" "(opt-channelslast) 使用 ChannelsLast 内存格式优化" OFF \
"43" "(autolaunch) 启动 WebUI 完成后自动启动浏览器" OFF \
"44" "(theme dark) 使用黑暗主题" OFF \
"45" "(use-textbox-seed) 使用文本框在 WebUI 中生成的种子" OFF \
"46" "(disable-console-progressbars) 禁用控制台进度条显示" OFF \
"47" "(enable-console-prompts) 启用在生图时输出提示词到控制台" OFF \
"48" "(disable-safe-unpickle) 禁用检查模型是否包含恶意代码" OFF \
"49" "(api) 启用 API" OFF \
"50" "(api-log) 启用输出所有 API 请求的日志记录" OFF \
"51" "(nowebui) 不加载 WebUI 界面" OFF \
"52" "(ui-debug-mode) 不加载模型启动 WebUI (UI Debug)" OFF \
"53" "(administrator) 启用管理员权限" OFF \
"54" "(disable-tls-verify) 禁用 TLS 证书验证" OFF \
"55" "(no-gradio-queue) 禁用 Gradio 队列" OFF \
"56" "(skip-version-check) 禁用 PyTorch, xFormers 版本检查" OFF \
"57" "(no-hashing) 禁用模型 Hash 检查" OFF \
"58" "(no-download-sd-model) 禁用自动下载模型, 即使模型路径无模型" OFF \
"59" "(add-stop-route) 添加 /_stop 路由以停止服务器" OFF \
"60" "(api-server-stop) 通过 API 启用服务器停止 / 重启 / 终止功能" OFF \
"61" "(disable-all-extensions) 禁用所有扩展运行" OFF \
"62" "(disable-extra-extensions) 禁用非内置的扩展运行" OFF \
"63" "(use-ipex) 使用 Intel XPU 作为生图后端" OFF \
"64" "(skip-load-model-at-start) 启动 WebUI 时不加载模型, 加速启动" OFF \
"65" "(in-browser) 启动 WebUI 完成后自动启动浏览器" OFF \
"66" "(disable-in-browser) 禁用在启动 WebUI 完成后自动启动浏览器" OFF \
"67" "(async-cuda-allocation) 启用 CUDA 流顺序内存分配器" OFF \
"68" "(disable-async-cuda-allocation) 禁用 CUDA 流顺序内存分配器" OFF \
"69" "(disable-attention-upcast) 禁用向上注意力优化" OFF \
"70" "(all-in-fp32) 强制使用 FP32" OFF \
"71" "(all-in-fp16) 强制使用 FP16" OFF \
"72" "(unet-in-bf16) 使用 BF16 精度运行 UNet" OFF \
"73" "(unet-in-fp16) 使用 FP16 精度运行 UNet" OFF \
"74" "(unet-in-fp8-e4m3fn) 使用 FP8(e4m3fn) 精度运行 UNet" OFF \
"75" "(unet-in-fp8-e5m2) 使用 FP8(e5m2) 精度运行 UNet" OFF \
"76" "(vae-in-fp16) 使用 FP16 精度运行 VAE" OFF \
"77" "(vae-in-fp32) 使用 FP32 精度运行 VAE" OFF \
"78" "(vae-in-bf16) 使用 BF16 精度运行 VAE" OFF \
"79" "(vae-in-cpu) 将 VAE 移至 CPU" OFF \
"80" "(clip-in-fp8-e4m3fn) 使用 FP8(e4m3fn) 精度运行 CLIP" OFF \
"81" "(clip-in-fp8-e5m2) 使用 FP8(e5m2) 精度运行 CLIP" OFF \
"82" "(clip-in-fp16) 使用 FP16 精度运行 CLIP" OFF \
"83" "(clip-in-fp32) 使用 FP32 精度运行 CLIP" OFF \
"84" "(disable-ipex-hijack) 禁用 IEPX 修复" OFF \
"85" "(preview-option none) 不使用图片预览" OFF \
"86" "(preview-option fast) 使用快速图片预览" OFF \
"87" "(preview-option taesd) 使用 TAESD 图片预览" OFF \
"88" "(attention-split) 使用 Split 优化" OFF \
"89" "(attention-quad) 使用 Quad 优化" OFF \
"90" "(attention-pytorch) 使用 PyTorch 方案优化" OFF \
"91" "(disable-xformers) 禁用 xFormers 优化" OFF \
"92" "(always-gpu) 将所有模型, 文本编码器储存在 GPU 中" OFF \
"93" "(always-high-vram) 不使用显存优化" OFF \
"94" "(always-normal-vram) 使用默认显存优化" OFF \
"95" "(always-low-vram) 使用显存优化 (将会降低生图速度)" OFF \
"96" "(always-no-vram) 使用显存优化 (将会大量降低生图速度)" OFF \
"97" "(always-cpu) 使用 CPU 进行生图" OFF \
"98" "(always-offload-from-vram) 生图完成后将模型从显存中卸载" OFF \
"99" "(pytorch-deterministic) 将 PyTorch 配置为使用确定性算法" OFF \
"100" "(disable-server-log) 禁用服务端日志输出" OFF \
"101" "(debug-mode) 启用 Debug 模式" OFF \
"102" "(is-windows-embedded-python) 启用 Windows 独占功能" OFF \
"103" "(disable-server-info) 禁用服务端信息输出" OFF \
"104" "(multi-user) 启用多用户模式" OFF \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
for i in ${dialog_arg}; do
case "${i}" in
1)
arg="--update-all-extensions"
;;
2)
arg="--skip-python-version-check"
;;
3)
arg="--skip-torch-cuda-test"
;;
4)
arg="--reinstall-xformers"
;;
5)
arg="--reinstall-torch"
;;
6)
arg="--update-check"
;;
7)
arg="--test-server"
;;
8)
arg="--log-startup"
;;
9)
arg="--skip-prepare-environment"
;;
10)
arg="--skip-install"
;;
11)
arg="--dump-sysinfo"
;;
12)
arg="--do-not-download-clip"
;;
13)
arg="--no-half"
;;
14)
arg="--no-half-vae"
;;
15)
arg="--no-progressbar-hiding"
;;
16)
arg="--allow-code"
;;
17)
arg="--medvram"
;;
18)
arg="--medvram-sdxl"
;;
19)
arg="--lowvram"
;;
20)
arg="--lowram"
;;
21)
arg="--precision full"
;;
22)
arg="--upcast-sampling"
;;
23)
arg="--share"
;;
24)
arg="--enable-insecure-extension-access"
;;
25)
arg="--xformers"
;;
26)
arg="--force-enable-xformers"
;;
27)
arg="--xformers-flash-attention"
;;
28)
arg="--opt-split-attention"
;;
29)
arg="--opt-sub-quad-attention"
;;
30)
arg="--opt-split-attention-invokeai"
;;
31)
arg="--opt-split-attention-v1"
;;
32)
arg="--opt-sdp-attention"
;;
33)
arg="--opt-sdp-no-mem-attention"
;;
34)
arg="--disable-opt-split-attention"
;;
35)
arg="--disable-nan-check"
;;
36)
arg="--use-cpu all"
;;
37)
arg="--disable-model-loading-ram-optimization"
;;
38)
arg="--listen"
;;
39)
arg="--hide-ui-dir-config"
;;
40)
arg="--freeze-settings"
;;
41)
arg="--gradio-debug"
;;
42)
arg="--opt-channelslast"
;;
43)
arg="--autolaunch"
;;
44)
arg="--theme dark"
;;
45)
arg="--use-textbox-seed"
;;
46)
arg="--disable-console-progressbars"
;;
47)
arg="--enable-console-prompts"
;;
48)
arg="--disable-safe-unpickle"
;;
49)
arg="--api"
;;
50)
arg="--api-log"
;;
51)
arg="--nowebui"
;;
52)
arg="--ui-debug-mode"
;;
53)
arg="--administrator"
;;
54)
arg="--disable-tls-verify"
;;
55)
arg="--no-gradio-queue"
;;
56)
arg="--skip-version-check"
;;
57)
arg="--no-hashing"
;;
58)
arg="--no-download-sd-model"
;;
59)
arg="--add-stop-route"
;;
60)
arg="--api-server-stop"
;;
61)
arg="--disable-all-extensions"
;;
62)
arg="--disable-extra-extensions"
;;
63)
arg="--use-ipex"
;;
64)
arg="--skip-load-model-at-start"
;;
65)
arg="--in-browser"
;;
66)
arg="--disable-in-browser"
;;
67)
arg="--async-cuda-allocation"
;;
68)
arg="--disable-async-cuda-allocation"
;;
69)
arg="--disable-attention-upcast"
;;
70)
arg="--all-in-fp32"
;;
71)
arg="--all-in-fp16"
;;
72)
arg="--unet-in-bf16"
;;
73)
arg="--unet-in-fp16"
;;
74)
arg="--unet-in-fp8-e4m3fn"
;;
75)
arg="--unet-in-fp8-e5m2"
;;
76)
arg="--vae-in-fp16"
;;
77)
arg="--vae-in-fp32"
;;
78)
arg="--vae-in-bf16"
;;
79)
arg="--vae-in-cpu"
;;
80)
arg="--clip-in-fp8-e4m3fn"
;;
81)
arg="--clip-in-fp8-e5m2"
;;
82)
arg="--clip-in-fp16"
;;
83)
arg="--clip-in-fp32"
;;
84)
arg="--disable-ipex-hijack"
;;
85)
arg="--preview-option none"
;;
86)
arg="--preview-option fast"
;;
87)
arg="--preview-option taesd"
;;
88)
arg="--attention-split"
;;
89)
arg="--attention-quad"
;;
90)
arg="--attention-pytorch"
;;
91)
arg="--disable-xformers"
;;
92)
arg="--always-gpu"
;;
93)
arg="--always-high-vram"
;;
94)
arg="--always-normal-vram"
;;
95)
arg="--always-low-vram"
;;
96)
arg="--always-no-vram"
;;
97)
arg="--always-cpu"
;;
98)
arg="--always-offload-from-vram"
;;
99)
arg="--pytorch-deterministic"
;;
100)
arg="--disable-server-log"
;;
101)
arg="--debug-mode"
;;
102)
arg="--is-windows-embedded-python"
;;
103)
arg="--disable-server-info"
;;
104)
arg="--multi-user"
;;
esac
launch_args="${arg} ${launch_args}"
done
# 生成启动脚本
term_sd_echo "设置 Stable-Diffusion-WebUI-Forge-Classic 启动参数: ${launch_args}"
echo "launch.py ${launch_args}" > "${START_PATH}"/term-sd/config/sd-webui-forge-classic-launch.conf
else
term_sd_echo "取消设置 Stable-Diffusion-WebUI-Forge-Classic 启动参数"
fi
}
# SD WebUI Forge Classic 启动界面
sd_webui_forge_classic_launch() {
local dialog_arg
local launch_args
add_sd_webui_forge_classic_normal_launch_args
while true; do
launch_args=$(cat "${START_PATH}"/term-sd/config/sd-webui-forge-classic-launch.conf)
if is_use_venv; then
launch_args="python ${launch_args}"
else
launch_args="${TERM_SD_PYTHON_PATH} ${launch_args}"
fi
dialog_arg=$(dialog --erase-on-exit --notags \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 启动选项" \
--ok-label "确认" --cancel-label "取消" \
--menu "请选择启动 Stable-Diffusion-WebUI-Forge-Classic / 修改 Stable-Diffusion-WebUI-Forge-Classic 启动参数\n当前启动参数: ${launch_args}" \
$(get_dialog_size_menu) \
"0" "> 返回" \
"1" "> 启动" \
"2" "> 配置预设启动参数" \
"3" "> 修改自定义启动参数" \
"4" "> 重置启动参数" \
3>&1 1>&2 2>&3)
case "${dialog_arg}" in
1)
term_sd_launch
;;
2)
sd_webui_forge_classic_launch_args_setting
;;
3)
sd_webui_forge_classic_launch_args_revise
;;
4)
restore_sd_webui_forge_classic_launch_args
;;
*)
break
;;
esac
done
}
# SD WebUI Forge CLassic 启动参数修改
sd_webui_forge_classic_launch_args_revise() {
local dialog_arg
local launch_args
launch_args=$(cat "${START_PATH}"/term-sd/config/sd-webui-forge-classic-launch.conf | awk '{sub("launch.py ","")}1')
dialog_arg=$(dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 自定义启动参数选项" \
--ok-label "确认" --cancel-label "取消" \
--inputbox "请输入 Stable-Diffusion-WebUI-Forge-Classic 启动参数" \
$(get_dialog_size) \
"${launch_args}" \
3>&1 1>&2 2>&3)
if [[ "$?" == 0 ]]; then
term_sd_echo "设置 Stable-Diffusion-WebUI-Forge-Classic 启动参数: ${dialog_arg}"
echo "launch.py ${dialog_arg}" > "${START_PATH}"/term-sd/config/sd-webui-forge-classic-launch.conf
else
term_sd_echo "取消修改 Stable-Diffusion-WebUI-Forge-Classic 启动参数"
fi
}
# 添加默认启动参数配置
add_sd_webui_forge_classic_normal_launch_args() {
if [[ ! -f "${START_PATH}/term-sd/config/sd-webui-forge-classic-launch.conf" ]]; then # 找不到启动配置时默认生成一个
echo "launch.py --theme dark --autolaunch --xformers --api" > "${START_PATH}"/term-sd/config/sd-webui-forge-classic-launch.conf
fi
}
# 重置启动参数
restore_sd_webui_forge_classic_launch_args() {
if (dialog --erase-on-exit \
--title "Stable-Diffusion-WebUI 管理" \
--backtitle "Stable-Diffusion-WebUI 重置启动参数选项选项" \
--yes-label "是" --no-label "否" \
--yesno "是否重置 Stable-Diffusion-WebUI-Forge-CLassic 启动参数" \
$(get_dialog_size)); then
term_sd_echo "重置 Stable-Diffusion-WebUI-Forge-Classic 启动参数"
rm -f "${START_PATH}"/term-sd/config/sd-webui-forge-classic-launch.conf
add_sd_webui_forge_classic_normal_launch_args
else
term_sd_echo "取消重置 Stable-Diffusion-WebUI-Forge-Classic 启动参数操作"
fi
}
|
2301_81996401/term-sd
|
modules/sd_webui_forge_classic_launch.sh
|
Shell
|
agpl-3.0
| 21,433
|