Search is not available for this dataset
repo stringlengths 2 152 ⌀ | file stringlengths 15 239 | code stringlengths 0 58.4M | file_length int64 0 58.4M | avg_line_length float64 0 1.81M | max_line_length int64 0 12.7M | extension_type stringclasses 364
values |
|---|---|---|---|---|---|---|
IID_representation_learning | IID_representation_learning-master/restyle/models/e4e_modules/discriminator.py | from torch import nn
class LatentCodesDiscriminator(nn.Module):
def __init__(self, style_dim, n_mlp):
super().__init__()
self.style_dim = style_dim
layers = []
for i in range(n_mlp-1):
layers.append(
nn.Linear(style_dim, style_dim)
)
... | 496 | 22.666667 | 47 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/e4e_modules/latent_codes_pool.py | import random
import torch
class LatentCodesPool:
"""This class implements latent codes buffer that stores previously generated w latent codes.
This buffer enables us to update discriminators using a history of generated w's
rather than the ones produced by the latest encoder.
"""
def __init__(se... | 2,349 | 40.964286 | 141 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/encoders/__init__.py | 0 | 0 | 0 | py | |
IID_representation_learning | IID_representation_learning-master/restyle/models/encoders/fpn_encoders.py | import torch
import torch.nn.functional as F
from torch import nn
from torch.nn import Conv2d, BatchNorm2d, PReLU, Sequential, Module
from torchvision.models.resnet import resnet34
from models.encoders.helpers import get_blocks, bottleneck_IR, bottleneck_IR_SE
from models.encoders.map2style import GradualStyleBlock
... | 5,672 | 34.45625 | 114 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/encoders/helpers.py | from collections import namedtuple
import torch
from torch.nn import Conv2d, BatchNorm2d, PReLU, ReLU, Sigmoid, MaxPool2d, AdaptiveAvgPool2d, Sequential, Module
"""
ArcFace implementation from [TreB1eN](https://github.com/TreB1eN/InsightFace_Pytorch)
"""
class Flatten(Module):
def forward(self, input):
return inp... | 3,556 | 28.641667 | 112 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/encoders/map2style.py | import numpy as np
from torch import nn
from torch.nn import Conv2d, Module
from models.stylegan2.model import EqualLinear
class GradualStyleBlock(Module):
def __init__(self, in_c, out_c, spatial):
super(GradualStyleBlock, self).__init__()
self.out_c = out_c
self.spatial = spatial
... | 1,887 | 32.714286 | 76 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/encoders/model_irse.py | from torch.nn import Linear, Conv2d, BatchNorm1d, BatchNorm2d, PReLU, Dropout, Sequential, Module
from models.encoders.helpers import get_blocks, Flatten, bottleneck_IR, bottleneck_IR_SE, l2_norm
"""
Modified Backbone implementation from [TreB1eN](https://github.com/TreB1eN/InsightFace_Pytorch)
"""
class Backbone(Mo... | 2,836 | 32.376471 | 97 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/encoders/restyle_e4e_encoders.py | from enum import Enum
from torch import nn
from torch.nn import Conv2d, BatchNorm2d, PReLU, Sequential, Module
from torchvision.models import resnet34
from models.encoders.helpers import get_blocks, bottleneck_IR, bottleneck_IR_SE
from models.encoders.map2style import GradualStyleBlock
class ProgressiveStage(Enum):
... | 5,676 | 36.846667 | 120 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/encoders/restyle_psp_encoders.py | import torch
from torch import nn
from torch.nn import Conv2d, BatchNorm2d, PReLU, Sequential, Module
from torchvision.models.resnet import resnet34
from models.encoders.helpers import get_blocks, bottleneck_IR, bottleneck_IR_SE
from models.encoders.map2style import GradualStyleBlock, GradualNoiseBlock
class Backbon... | 4,334 | 35.737288 | 120 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/mtcnn/__init__.py | 0 | 0 | 0 | py | |
IID_representation_learning | IID_representation_learning-master/restyle/models/mtcnn/mtcnn.py | import numpy as np
import torch
from PIL import Image
from models.mtcnn.mtcnn_pytorch.src.get_nets import PNet, RNet, ONet
from models.mtcnn.mtcnn_pytorch.src.box_utils import nms, calibrate_box, get_image_boxes, convert_to_square
from models.mtcnn.mtcnn_pytorch.src.first_stage import run_first_stage
from models.mtcnn.... | 6,220 | 38.624204 | 116 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/mtcnn/mtcnn_pytorch/__init__.py | 0 | 0 | 0 | py | |
IID_representation_learning | IID_representation_learning-master/restyle/models/mtcnn/mtcnn_pytorch/src/__init__.py | from .visualization_utils import show_bboxes
from .detector import detect_faces
| 80 | 26 | 44 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/mtcnn/mtcnn_pytorch/src/align_trans.py | # -*- coding: utf-8 -*-
"""
Created on Mon Apr 24 15:43:29 2017
@author: zhaoy
"""
import numpy as np
import cv2
# from scipy.linalg import lstsq
# from scipy.ndimage import geometric_transform # , map_coordinates
from models.mtcnn.mtcnn_pytorch.src.matlab_cp2tform import get_similarity_transform_for_cv2
# referenc... | 11,036 | 35.186885 | 109 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/mtcnn/mtcnn_pytorch/src/box_utils.py | import numpy as np
from PIL import Image
def nms(boxes, overlap_threshold=0.5, mode='union'):
"""Non-maximum suppression.
Arguments:
boxes: a float numpy array of shape [n, 5],
where each row is (xmin, ymin, xmax, ymax, score).
overlap_threshold: a float number.
mode: 'uni... | 6,936 | 28.025105 | 90 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/mtcnn/mtcnn_pytorch/src/detector.py | import numpy as np
import torch
from .get_nets import PNet, RNet, ONet
from .box_utils import nms, calibrate_box, get_image_boxes, convert_to_square
from .first_stage import run_first_stage
def detect_faces(image, min_face_size=20.0,
thresholds=[0.6, 0.7, 0.8],
nms_thresholds=[0.7, 0... | 4,333 | 33.396825 | 101 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/mtcnn/mtcnn_pytorch/src/first_stage.py | import torch
import math
from PIL import Image
import numpy as np
from .box_utils import nms, _preprocess
# device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
device = 'cuda:0'
def run_first_stage(image, net, scale, threshold):
"""Run P-Net, generate bounding boxes, and do NMS.
Argument... | 3,147 | 30.168317 | 76 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/mtcnn/mtcnn_pytorch/src/get_nets.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from collections import OrderedDict
import numpy as np
from configs.paths_config import model_paths
PNET_PATH = model_paths["mtcnn_pnet"]
ONET_PATH = model_paths["mtcnn_onet"]
RNET_PATH = model_paths["mtcnn_rnet"]
class Flatten(nn.Module):
def _... | 4,995 | 28.046512 | 65 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/mtcnn/mtcnn_pytorch/src/matlab_cp2tform.py | # -*- coding: utf-8 -*-
"""
Created on Tue Jul 11 06:54:28 2017
@author: zhaoyafei
"""
import numpy as np
from numpy.linalg import inv, norm, lstsq
from numpy.linalg import matrix_rank as rank
class MatlabCp2tormException(Exception):
def __str__(self):
return 'In File {}:{}'.format(
__file__... | 8,562 | 23.396011 | 77 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/mtcnn/mtcnn_pytorch/src/visualization_utils.py | from PIL import ImageDraw
def show_bboxes(img, bounding_boxes, facial_landmarks=[]):
"""Draw bounding boxes and facial landmarks.
Arguments:
img: an instance of PIL.Image.
bounding_boxes: a float numpy array of shape [n, 5].
facial_landmarks: a float numpy array of shape [n, 10].
... | 786 | 23.59375 | 63 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/stylegan2/__init__.py | 0 | 0 | 0 | py | |
IID_representation_learning | IID_representation_learning-master/restyle/models/stylegan2/model.py | import math
import random
import torch
from torch import nn
from torch.nn import functional as F
from models.stylegan2.op import FusedLeakyReLU, fused_leaky_relu, upfirdn2d
class PixelNorm(nn.Module):
def __init__(self):
super().__init__()
def forward(self, input):
return input * torch.rsqrt... | 18,559 | 26.537092 | 100 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/stylegan2/op/__init__.py | from .fused_act import FusedLeakyReLU, fused_leaky_relu
from .upfirdn2d import upfirdn2d
| 89 | 29 | 55 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/stylegan2/op/fused_act.py | import os
import torch
from torch import nn
from torch.autograd import Function
from torch.utils.cpp_extension import load
module_path = os.path.dirname(__file__)
fused = load(
'fused',
sources=[
os.path.join(module_path, 'fused_bias_act.cpp'),
os.path.join(module_path, 'fused_bias_act_kernel.... | 2,378 | 26.662791 | 83 | py |
IID_representation_learning | IID_representation_learning-master/restyle/models/stylegan2/op/fused_bias_act.cpp | #include <torch/extension.h>
torch::Tensor fused_bias_act_op(const torch::Tensor& input, const torch::Tensor& bias, const torch::Tensor& refer,
int act, int grad, float alpha, float scale);
#define CHECK_CUDA(x) TORCH_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
#define CHECK_CONTIGUOUS(x) TORCH_CHECK(... | 826 | 38.380952 | 114 | cpp |
IID_representation_learning | IID_representation_learning-master/restyle/models/stylegan2/op/upfirdn2d.cpp | #include <torch/extension.h>
torch::Tensor upfirdn2d_op(const torch::Tensor& input, const torch::Tensor& kernel,
int up_x, int up_y, int down_x, int down_y,
int pad_x0, int pad_x1, int pad_y0, int pad_y1);
#define CHECK_CUDA(x) TORCH_CHECK(x.type().is_cuda(), #... | 966 | 41.043478 | 99 | cpp |
IID_representation_learning | IID_representation_learning-master/restyle/models/stylegan2/op/upfirdn2d.py | import os
import torch
from torch.autograd import Function
from torch.utils.cpp_extension import load
module_path = os.path.dirname(__file__)
upfirdn2d_op = load(
'upfirdn2d',
sources=[
os.path.join(module_path, 'upfirdn2d.cpp'),
os.path.join(module_path, 'upfirdn2d_kernel.cu'),
],
)
cla... | 5,203 | 27.12973 | 108 | py |
IID_representation_learning | IID_representation_learning-master/restyle/options/__init__.py | 0 | 0 | 0 | py | |
IID_representation_learning | IID_representation_learning-master/restyle/options/e4e_train_options.py | from options.train_options import TrainOptions
class e4eTrainOptions(TrainOptions):
def __init__(self):
super(e4eTrainOptions, self).__init__()
def initialize(self):
super(e4eTrainOptions, self).initialize()
self.parser.add_argument('--w_discriminator_lambda', default=0, type=float,
... | 3,016 | 58.156863 | 120 | py |
IID_representation_learning | IID_representation_learning-master/restyle/options/test_options.py | from argparse import ArgumentParser
class TestOptions:
def __init__(self):
self.parser = ArgumentParser()
self.initialize()
def initialize(self):
# arguments for inference script
self.parser.add_argument('--exp_dir', type=str,
help='Path to ex... | 2,530 | 51.729167 | 115 | py |
IID_representation_learning | IID_representation_learning-master/restyle/options/train_options.py | from argparse import ArgumentParser
class TrainOptions:
def __init__(self):
self.parser = ArgumentParser()
self.initialize()
def initialize(self):
# general setup
self.parser.add_argument('--exp_dir', type=str,
help='Path to experiment output ... | 4,690 | 54.188235 | 115 | py |
IID_representation_learning | IID_representation_learning-master/restyle/scripts/align_faces_parallel.py | """
brief: face alignment with FFHQ method (https://github.com/NVlabs/ffhq-dataset)
author: lzhbrian (https://lzhbrian.me)
date: 2020.1.5
note: code is heavily borrowed from
https://github.com/NVlabs/ffhq-dataset
http://dlib.net/face_landmark_detection.py.html
requirements:
apt install cmake
conda install Pillow n... | 6,988 | 32.927184 | 117 | py |
IID_representation_learning | IID_representation_learning-master/restyle/scripts/calc_id_loss_parallel.py | from argparse import ArgumentParser
import time
import numpy as np
import os
import json
import sys
from PIL import Image
import multiprocessing as mp
import math
import torch
import torchvision.transforms as trans
sys.path.append(".")
sys.path.append("..")
from models.mtcnn.mtcnn import MTCNN
from models.encoders.mo... | 3,804 | 27.609023 | 111 | py |
IID_representation_learning | IID_representation_learning-master/restyle/scripts/calc_losses_on_images.py | from argparse import ArgumentParser
import os
import json
import sys
from tqdm import tqdm
import numpy as np
import torch
from torch.utils.data import DataLoader
import torchvision.transforms as transforms
sys.path.append(".")
sys.path.append("..")
from criteria.lpips.lpips import LPIPS
from datasets.gt_res_dataset ... | 2,822 | 27.515152 | 85 | py |
IID_representation_learning | IID_representation_learning-master/restyle/scripts/encoder_bootstrapping_inference.py | import os
from argparse import Namespace
from tqdm import tqdm
import time
import numpy as np
import torch
from PIL import Image
from torch.utils.data import DataLoader
import sys
from utils.inference_utils import get_average_image
sys.path.append(".")
sys.path.append("..")
from configs import data_configs
from dat... | 5,208 | 34.678082 | 110 | py |
IID_representation_learning | IID_representation_learning-master/restyle/scripts/inference_iterative.py | import os
from argparse import Namespace
from tqdm import tqdm
import time
import numpy as np
import torch
from torch.utils.data import DataLoader
import sys
sys.path.append(".")
sys.path.append("..")
from configs import data_configs
from datasets.inference_dataset import InferenceDataset
from options.test_options im... | 3,601 | 32.351852 | 106 | py |
IID_representation_learning | IID_representation_learning-master/restyle/scripts/inference_iterative_save_coupled.py | import os
from argparse import Namespace
from tqdm import tqdm
import time
import numpy as np
import torch
from PIL import Image
from torch.utils.data import DataLoader
import sys
sys.path.append(".")
sys.path.append("..")
from configs import data_configs
from datasets.inference_dataset import InferenceDataset
from o... | 3,513 | 32.466667 | 106 | py |
IID_representation_learning | IID_representation_learning-master/restyle/scripts/train_restyle_e4e.py | """
This file runs the main training/val loop
"""
import os
import json
import math
import sys
import pprint
import torch
from argparse import Namespace
sys.path.append(".")
sys.path.append("..")
from options.e4e_train_options import e4eTrainOptions
from training.coach_restyle_e4e import Coach
def main():
opts = e... | 2,438 | 27.360465 | 95 | py |
IID_representation_learning | IID_representation_learning-master/restyle/scripts/train_restyle_psp.py | """
This file runs the main training/val loop
"""
import os
import json
import sys
import pprint
sys.path.append(".")
sys.path.append("..")
from options.train_options import TrainOptions
from training.coach_restyle_psp import Coach
def main():
opts = TrainOptions().parse()
os.makedirs(opts.exp_dir, exist_ok=True)... | 560 | 17.096774 | 61 | py |
IID_representation_learning | IID_representation_learning-master/restyle/training/__init__.py | 0 | 0 | 0 | py | |
IID_representation_learning | IID_representation_learning-master/restyle/training/coach_restyle_e4e.py | from models.encoders.restyle_e4e_encoders import ProgressiveStage
from models.e4e_modules.discriminator import LatentCodesDiscriminator
from models.e4e_modules.latent_codes_pool import LatentCodesPool
from training.ranger import Ranger
from models.e4e import e4e
from criteria.lpips.lpips import LPIPS
from datasets.imag... | 24,241 | 43.318099 | 129 | py |
IID_representation_learning | IID_representation_learning-master/restyle/training/coach_restyle_psp.py | from training.ranger import Ranger
from models.psp import pSp
from criteria.lpips.lpips import LPIPS
from wilds import get_dataset
from wilds.common.data_loaders import get_train_loader, get_eval_loader
from configs import data_configs
from criteria import id_loss, w_norm, moco_loss
from utils import common, train_util... | 15,114 | 42.811594 | 129 | py |
IID_representation_learning | IID_representation_learning-master/restyle/training/ranger.py | # Ranger deep learning optimizer - RAdam + Lookahead + Gradient Centralization, combined into one optimizer.
# https://github.com/lessw2020/Ranger-Deep-Learning-Optimizer
# and/or
# https://github.com/lessw2020/Best-Deep-Learning-Optimizers
# Ranger has now been used to capture 12 records on the FastAI leaderboard.
... | 5,899 | 34.97561 | 169 | py |
IID_representation_learning | IID_representation_learning-master/restyle/utils/__init__.py | 0 | 0 | 0 | py | |
IID_representation_learning | IID_representation_learning-master/restyle/utils/common.py | from PIL import Image
import matplotlib.pyplot as plt
def tensor2im(var):
var = var.cpu().detach().transpose(0, 2).transpose(0, 1).numpy()
var = ((var + 1) / 2)
var[var < 0] = 0
var[var > 1] = 1
var = var * 255
return Image.fromarray(var.astype('uint8'))
def vis_faces(log_hooks):
display... | 1,486 | 35.268293 | 88 | py |
IID_representation_learning | IID_representation_learning-master/restyle/utils/data_utils.py | """
Code adopted from pix2pixHD:
https://github.com/NVIDIA/pix2pixHD/blob/master/data/image_folder.py
"""
import os
import torch
IMG_EXTENSIONS = [
'.jpg', '.JPG', '.jpeg', '.JPEG',
'.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP', '.tiff'
]
def is_image_file(filename):
return any(filename.endswith(extensi... | 1,541 | 31.808511 | 110 | py |
IID_representation_learning | IID_representation_learning-master/restyle/utils/inference_utils.py | import torch
def get_average_image(net, opts):
avg_image = net(net.latent_avg.unsqueeze(0),
input_code=True,
randomize_noise=False,
return_latents=False,
average_code=True)[0]
avg_image = avg_image.to('cuda').float().detach()
... | 1,879 | 35.862745 | 89 | py |
IID_representation_learning | IID_representation_learning-master/restyle/utils/model_utils.py | # specify the encoder types for pSp and e4e - this is mainly used for the inference scripts
ENCODER_TYPES = {
'pSp': ['GradualStyleEncoder', 'ResNetGradualStyleEncoder', 'BackboneEncoder', 'ResNetBackboneEncoder'],
'e4e': ['ProgressiveBackboneEncoder', 'ResNetProgressiveBackboneEncoder']
}
RESNET_MAPPING = {
... | 743 | 28.76 | 108 | py |
IID_representation_learning | IID_representation_learning-master/restyle/utils/train_utils.py |
def aggregate_loss_dict(agg_loss_dict):
mean_vals = {}
for output in agg_loss_dict:
for key in output:
mean_vals[key] = mean_vals.setdefault(key, []) + [output[key]]
for key in mean_vals:
if len(mean_vals[key]) > 0:
mean_vals[key] = sum(mean_vals[key]) / len(mean_vals[key])
else:
print('{} has no val... | 377 | 26 | 65 | py |
mmdetection | mmdetection-master/.owners.yml | assign:
strategy:
# random
daily-shift-based
scedule: "*/1 * * * *"
assignees:
- Czm369
- hhaAndroid
- zwhus
- RangiLyu
- BIGWangYuDong
- ZwwWayne
- ZwwWayne
| 200 | 13.357143 | 24 | yml |
mmdetection | mmdetection-master/.pre-commit-config.yaml | repos:
- repo: https://github.com/PyCQA/flake8
rev: 5.0.4
hooks:
- id: flake8
- repo: https://github.com/PyCQA/isort
rev: 5.11.5
hooks:
- id: isort
- repo: https://github.com/pre-commit/mirrors-yapf
rev: v0.32.0
hooks:
- id: yapf
- repo: https://github.com/pre-commit/pr... | 1,452 | 27.490196 | 89 | yaml |
mmdetection | mmdetection-master/.readthedocs.yml | version: 2
formats: all
python:
version: 3.8
install:
- requirements: requirements/docs.txt
- requirements: requirements/readthedocs.txt
| 151 | 14.2 | 48 | yml |
mmdetection | mmdetection-master/README.md | <div align="center">
<img src="resources/mmdet-logo.png" width="600"/>
<div> </div>
<div align="center">
<b><font size="5">OpenMMLab website</font></b>
<sup>
<a href="https://openmmlab.com">
<i><font size="4">HOT</font></i>
</a>
</sup>
<b><font... | 22,446 | 53.615572 | 560 | md |
mmdetection | mmdetection-master/README_zh-CN.md | <div align="center">
<img src="resources/mmdet-logo.png" width="600"/>
<div> </div>
<div align="center">
<b><font size="5">OpenMMLab 官网</font></b>
<sup>
<a href="https://openmmlab.com">
<i><font size="4">HOT</font></i>
</a>
</sup>
<b><font size... | 18,742 | 44.055288 | 367 | md |
mmdetection | mmdetection-master/model-index.yml | Import:
- configs/atss/metafile.yml
- configs/autoassign/metafile.yml
- configs/carafe/metafile.yml
- configs/cascade_rcnn/metafile.yml
- configs/cascade_rpn/metafile.yml
- configs/centernet/metafile.yml
- configs/centripetalnet/metafile.yml
- configs/cornernet/metafile.yml
- configs/convnext/metafile... | 2,401 | 31.459459 | 44 | yml |
mmdetection | mmdetection-master/setup.py | #!/usr/bin/env python
# Copyright (c) OpenMMLab. All rights reserved.
import os
import os.path as osp
import platform
import shutil
import sys
import warnings
from setuptools import find_packages, setup
import torch
from torch.utils.cpp_extension import (BuildExtension, CppExtension,
... | 7,887 | 34.692308 | 125 | py |
mmdetection | mmdetection-master/.circleci/config.yml | version: 2.1
# this allows you to use CircleCI's dynamic configuration feature
setup: true
# the path-filtering orb is required to continue a pipeline based on
# the path of an updated fileset
orbs:
path-filtering: circleci/path-filtering@0.1.2
workflows:
# the always-run workflow is always triggered, regardless... | 1,275 | 35.457143 | 87 | yml |
mmdetection | mmdetection-master/.circleci/test.yml |
version: 2.1
# the default pipeline parameters, which will be updated according to
# the results of the path-filtering orb
parameters:
lint_only:
type: boolean
default: true
jobs:
lint:
docker:
- image: cimg/python:3.7.4
steps:
- checkout
- run:
name: Install pre-comm... | 6,158 | 31.415789 | 177 | yml |
mmdetection | mmdetection-master/.circleci/scripts/get_mmcv_var.sh | #!/bin/bash
TORCH=$1
CUDA=$2
# 10.2 -> cu102
MMCV_CUDA="cu`echo ${CUDA} | tr -d '.'`"
# MMCV only provides pre-compiled packages for torch 1.x.0
# which works for any subversions of torch 1.x.
# We force the torch version to be 1.x.0 to ease package searching
# and avoid unnecessary rebuild during MMCV's installatio... | 574 | 27.75 | 66 | sh |
mmdetection | mmdetection-master/.dev_scripts/batch_test_list.py | # Copyright (c) OpenMMLab. All rights reserved.
# yapf: disable
atss = dict(
config='configs/atss/atss_r50_fpn_1x_coco.py',
checkpoint='atss_r50_fpn_1x_coco_20200209-985f7bd0.pth',
eval='bbox',
metric=dict(bbox_mAP=39.4),
)
autoassign = dict(
config='configs/autoassign/autoassign_r50_fpn_8x2_1x_coco... | 12,707 | 34.3 | 117 | py |
mmdetection | mmdetection-master/.dev_scripts/benchmark_filter.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
import os.path as osp
def parse_args():
parser = argparse.ArgumentParser(description='Filter configs to train')
parser.add_argument(
'--basic-arch',
action='store_true',
help='to train models in basic arch')
... | 7,106 | 41.303571 | 92 | py |
mmdetection | mmdetection-master/.dev_scripts/benchmark_inference_fps.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
import os.path as osp
import mmcv
from mmcv import Config, DictAction
from mmcv.runner import init_dist
from terminaltables import GithubFlavoredMarkdownTable
from tools.analysis_tools.benchmark import repeat_measure_inference_speed
def parse... | 6,764 | 38.561404 | 79 | py |
mmdetection | mmdetection-master/.dev_scripts/benchmark_test_image.py | # Copyright (c) OpenMMLab. All rights reserved.
import logging
import os.path as osp
from argparse import ArgumentParser
from mmcv import Config
from mmdet.apis import inference_detector, init_detector, show_result_pyplot
from mmdet.utils import get_root_logger
def parse_args():
parser = ArgumentParser()
pa... | 3,674 | 34.679612 | 77 | py |
mmdetection | mmdetection-master/.dev_scripts/check_links.py | # Modified from:
# https://github.com/allenai/allennlp/blob/main/scripts/check_links.py
import argparse
import logging
import os
import pathlib
import re
import sys
from multiprocessing.dummy import Pool
from typing import NamedTuple, Optional, Tuple
import requests
from mmcv.utils import get_logger
def parse_args(... | 5,049 | 30.962025 | 76 | py |
mmdetection | mmdetection-master/.dev_scripts/convert_test_benchmark_script.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
import os.path as osp
from mmcv import Config
def parse_args():
parser = argparse.ArgumentParser(
description='Convert benchmark model list to script')
parser.add_argument('config', help='test config file path')
parser.add_... | 3,604 | 29.041667 | 79 | py |
mmdetection | mmdetection-master/.dev_scripts/convert_train_benchmark_script.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
import os.path as osp
def parse_args():
parser = argparse.ArgumentParser(
description='Convert benchmark model json to script')
parser.add_argument(
'txt_path', type=str, help='txt path output by benchmark_filter')
p... | 3,307 | 32.08 | 74 | py |
mmdetection | mmdetection-master/.dev_scripts/gather_models.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import glob
import json
import os.path as osp
import shutil
import subprocess
from collections import OrderedDict
import mmcv
import torch
import yaml
def ordered_yaml_dump(data, stream=None, Dumper=yaml.SafeDumper, **kwds):
class OrderedDumper(Dum... | 12,487 | 35.408163 | 79 | py |
mmdetection | mmdetection-master/.dev_scripts/gather_test_benchmark_metric.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import glob
import os.path as osp
import mmcv
from mmcv import Config
def parse_args():
parser = argparse.ArgumentParser(
description='Gather benchmarked models metric')
parser.add_argument('config', help='test config file path')
par... | 3,916 | 39.381443 | 79 | py |
mmdetection | mmdetection-master/.dev_scripts/gather_train_benchmark_metric.py | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import glob
import os.path as osp
import mmcv
from gather_models import get_final_results
try:
import xlrd
except ImportError:
xlrd = None
try:
import xlutils
from xlutils.copy import copy
except ImportError:
xlutils = None
def pars... | 5,843 | 37.701987 | 79 | py |
mmdetection | mmdetection-master/.dev_scripts/linter.sh | yapf -r -i mmdet/ configs/ tests/ tools/
isort -rc mmdet/ configs/ tests/ tools/
flake8 .
| 90 | 21.75 | 40 | sh |
mmdetection | mmdetection-master/.dev_scripts/test_benchmark.sh | PARTITION=$1
CHECKPOINT_DIR=$2
echo 'configs/atss/atss_r50_fpn_1x_coco.py' &
GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=2 tools/slurm_test.sh $PARTITION atss_r50_fpn_1x_coco configs/atss/atss_r50_fpn_1x_coco.py $CHECKPOINT_DIR/atss_r50_fpn_1x_coco_20200209-985f7bd0.pth --work-dir tools/batch_test/atss_r50_fpn_1x_coco --ev... | 23,366 | 193.725 | 467 | sh |
mmdetection | mmdetection-master/.dev_scripts/test_init_backbone.py | # Copyright (c) OpenMMLab. All rights reserved.
"""Check out backbone whether successfully load pretrained checkpoint."""
import copy
import os
from os.path import dirname, exists, join
import pytest
from mmcv import Config, ProgressBar
from mmcv.runner import _load_checkpoint
from mmdet.models import build_detector
... | 6,625 | 35.406593 | 78 | py |
mmdetection | mmdetection-master/.dev_scripts/train_benchmark.sh | echo 'configs/atss/atss_r50_fpn_1x_coco.py' &
GPUS=8 GPUS_PER_NODE=8 CPUS_PER_TASK=2 ./tools/slurm_train.sh openmmlab atss_r50_fpn_1x_coco configs/atss/atss_r50_fpn_1x_coco.py ./tools/work_dir/atss_r50_fpn_1x_coco --cfg-options checkpoint_config.max_keep_ckpts=1 >/dev/null &
echo 'configs/autoassign/autoassign_r50_fp... | 22,182 | 163.318519 | 336 | sh |
mmdetection | mmdetection-master/.github/CODE_OF_CONDUCT.md | # Contributor Covenant Code of Conduct
## Our Pledge
In the interest of fostering an open and welcoming environment, we as
contributors and maintainers pledge to making participation in our project and
our community a harassment-free experience for everyone, regardless of age, body
size, disability, ethnicity, sex ch... | 3,355 | 42.584416 | 87 | md |
mmdetection | mmdetection-master/.github/CONTRIBUTING.md | We appreciate all contributions to improve MMDetection. Please refer to [CONTRIBUTING.md](https://github.com/open-mmlab/mmcv/blob/master/CONTRIBUTING.md) in MMCV for more details about the contributing guideline.
| 213 | 106 | 212 | md |
mmdetection | mmdetection-master/.github/pull_request_template.md | Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily get feedback. If you do not understand some items, don't worry, just make the pull request and seek help from maintainers.
## Motivation
Please describe the motivation of this ... | 1,310 | 49.423077 | 264 | md |
mmdetection | mmdetection-master/.github/ISSUE_TEMPLATE/1-bug-report.yml | name: "🐞 Bug report"
description: "Create a report to help us reproduce and fix the bug"
labels: "kind/bug,status/unconfirmed"
title: "[Bug] "
body:
- type: markdown
attributes:
value: |
If you have already identified the reason, we strongly appreciate you creating a new PR to fix it [here](https:... | 3,938 | 36.160377 | 200 | yml |
mmdetection | mmdetection-master/.github/ISSUE_TEMPLATE/2-feature-request.yml | name: 🚀 Feature request
description: Suggest an idea for this project
labels: "kind/enhancement,status/unconfirmed"
title: "[Feature] "
body:
- type: markdown
attributes:
value: |
We strongly appreciate you creating a PR to implement this feature [here](https://github.com/open-mmlab/mmdetection/pu... | 1,077 | 32.6875 | 131 | yml |
mmdetection | mmdetection-master/.github/ISSUE_TEMPLATE/3-new-model.yml | name: "\U0001F31F New model/dataset/scheduler addition"
description: Submit a proposal/request to implement a new model / dataset / scheduler
labels: "kind/feature,status/unconfirmed"
title: "[New Models] "
body:
- type: textarea
id: description-request
validations:
required: true
attributes:
... | 1,084 | 31.878788 | 94 | yml |
mmdetection | mmdetection-master/.github/ISSUE_TEMPLATE/4-documentation.yml | name: 📚 Documentation
description: Report an issue related to the documentation.
labels: "kind/doc,status/unconfirmed"
title: "[Docs] "
body:
- type: dropdown
id: branch
attributes:
label: Branch
description: This issue is related to the
options:
- master branch https://mmdetection.readthedocs.... | 834 | 22.857143 | 68 | yml |
mmdetection | mmdetection-master/.github/ISSUE_TEMPLATE/5-reimplementation.yml | name: "💥 Reimplementation Questions"
description: "Ask about questions during model reimplementation"
labels: "kind/enhancement,status/unconfirmed"
title: "[Reimplementation] "
body:
- type: markdown
attributes:
value: |
We strongly appreciate you creating a PR to implement this feature [here](htt... | 4,281 | 46.577778 | 441 | yml |
mmdetection | mmdetection-master/.github/ISSUE_TEMPLATE/config.yml | blank_issues_enabled: true
contact_links:
- name: 💬 Forum
url: https://github.com/open-mmlab/mmdetection/discussions
about: Ask general usage questions and discuss with other MMDetection community members
- name: 🌐 Explore OpenMMLab
url: https://openmmlab.com/
about: Get know more about OpenMMLab... | 319 | 31 | 91 | yml |
mmdetection | mmdetection-master/.github/workflows/build.yml | name: build
on:
push:
paths-ignore:
- ".dev_scripts/**"
- ".github/**.md"
- "demo/**"
- "docker/**"
- "tools/**"
- "README.md"
- "README_zh-CN.md"
pull_request:
paths-ignore:
- ".dev_scripts/**"
- ".github/**.md"
- "demo/**"
- "docker/**"
... | 11,161 | 37.891986 | 166 | yml |
mmdetection | mmdetection-master/.github/workflows/build_pat.yml | name: build_pat
on: push
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
permissions:
contents: read
jobs:
build_parrots:
runs-on: ubuntu-latest
container:
image: ghcr.io/zhouzaida/parrots-mmcv:1.3.4
credentials:
username: zhouzaida
p... | 783 | 23.5 | 69 | yml |
mmdetection | mmdetection-master/.github/workflows/deploy.yml | name: deploy
on: push
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
permissions:
contents: read
jobs:
build-n-publish:
runs-on: ubuntu-latest
if: startsWith(github.event.ref, 'refs/tags')
steps:
- uses: actions/checkout@v2
- name: Set up Python... | 765 | 22.9375 | 74 | yml |
mmdetection | mmdetection-master/.github/workflows/lint.yml | name: lint
on: [push, pull_request]
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
permissions:
contents: read
jobs:
lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- name: Set up Python 3.7
uses: actions/setup-python@v2
... | 761 | 23.580645 | 135 | yml |
mmdetection | mmdetection-master/.github/workflows/stale.yml | name: 'Close stale issues and PRs'
on:
schedule:
# check issue and pull request once every day
- cron: '25 11 * * *'
permissions:
contents: read
jobs:
invalid-stale-close:
permissions:
issues: write
pull-requests: write
runs-on: ubuntu-latest
steps:
- uses: actions/stale@v... | 1,598 | 48.96875 | 260 | yml |
mmdetection | mmdetection-master/.github/workflows/test_mim.yml | name: test-mim
on:
push:
paths:
- 'model-index.yml'
- 'configs/**'
pull_request:
paths:
- 'model-index.yml'
- 'configs/**'
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
permissions:
contents: read
jobs:
build_cpu:
runs-on: ubun... | 1,293 | 24.372549 | 148 | yml |
mmdetection | mmdetection-master/configs/_base_/default_runtime.py | checkpoint_config = dict(interval=1)
# yapf:disable
log_config = dict(
interval=50,
hooks=[
dict(type='TextLoggerHook'),
# dict(type='TensorboardLoggerHook')
])
# yapf:enable
custom_hooks = [dict(type='NumClassCheckHook')]
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = No... | 791 | 27.285714 | 67 | py |
mmdetection | mmdetection-master/configs/_base_/datasets/cityscapes_detection.py | # dataset settings
dataset_type = 'CityscapesDataset'
data_root = 'data/cityscapes/'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Resize'... | 1,937 | 33 | 79 | py |
mmdetection | mmdetection-master/configs/_base_/datasets/cityscapes_instance.py | # dataset settings
dataset_type = 'CityscapesDataset'
data_root = 'data/cityscapes/'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
dict(
... | 1,963 | 33.45614 | 79 | py |
mmdetection | mmdetection-master/configs/_base_/datasets/coco_detection.py | # dataset settings
dataset_type = 'CocoDataset'
data_root = 'data/coco/'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='Resize', img_scale=(1333, 80... | 1,711 | 33.24 | 77 | py |
mmdetection | mmdetection-master/configs/_base_/datasets/coco_instance.py | # dataset settings
dataset_type = 'CocoDataset'
data_root = 'data/coco/'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
dict(type='Resize', img... | 1,737 | 33.76 | 77 | py |
mmdetection | mmdetection-master/configs/_base_/datasets/coco_instance_semantic.py | # dataset settings
dataset_type = 'CocoDataset'
data_root = 'data/coco/'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='LoadAnnotations', with_bbox=True, with_mask=True, with_seg=True),
... | 1,922 | 33.963636 | 79 | py |
mmdetection | mmdetection-master/configs/_base_/datasets/coco_panoptic.py | # dataset settings
dataset_type = 'CocoPanopticDataset'
data_root = 'data/coco/'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='LoadPanopticAnnotations',
with_bbox=True,
wit... | 2,079 | 33.666667 | 79 | py |
mmdetection | mmdetection-master/configs/_base_/datasets/deepfashion.py | # dataset settings
dataset_type = 'DeepFashionDataset'
data_root = 'data/DeepFashion/In-shop/'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
d... | 1,888 | 33.981481 | 79 | py |
mmdetection | mmdetection-master/configs/_base_/datasets/lvis_v0.5_instance.py | # dataset settings
_base_ = 'coco_instance.py'
dataset_type = 'LVISV05Dataset'
data_root = 'data/lvis_v0.5/'
data = dict(
samples_per_gpu=2,
workers_per_gpu=2,
train=dict(
_delete_=True,
type='ClassBalancedDataset',
oversample_thr=1e-3,
dataset=dict(
type=dataset_... | 786 | 30.48 | 68 | py |
mmdetection | mmdetection-master/configs/_base_/datasets/lvis_v1_instance.py | # dataset settings
_base_ = 'coco_instance.py'
dataset_type = 'LVISV1Dataset'
data_root = 'data/lvis_v1/'
data = dict(
samples_per_gpu=2,
workers_per_gpu=2,
train=dict(
_delete_=True,
type='ClassBalancedDataset',
oversample_thr=1e-3,
dataset=dict(
type=dataset_typ... | 736 | 28.48 | 66 | py |
mmdetection | mmdetection-master/configs/_base_/datasets/objects365v1_detection.py | # dataset settings
dataset_type = 'Objects365V1Dataset'
data_root = 'data/Objects365/Obj365_v1/'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='Resi... | 1,714 | 33.3 | 77 | py |
mmdetection | mmdetection-master/configs/_base_/datasets/objects365v2_detection.py | # dataset settings
dataset_type = 'Objects365V2Dataset'
data_root = 'data/Objects365/Obj365_v2/'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='Resi... | 1,723 | 33.48 | 77 | py |