repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
3DTrans | 3DTrans-master/tools/ssl_utils/iou_match_3d.py | import torch
from .semi_utils import reverse_transform, load_data_to_gpu, construct_pseudo_label
from pcdet.models.model_utils.model_nms_utils import class_agnostic_nms
@torch.no_grad()
def iou_match_3d_filter(batch_dict, cfgs):
batch_size = batch_dict['batch_size']
pred_dicts = []
for index in range(batch... | 3,447 | 38.181818 | 130 | py |
3DTrans | 3DTrans-master/tools/ssl_utils/sess.py | import torch
import torch.nn.functional as F
import numpy as np
from .semi_utils import reverse_transform, load_data_to_gpu, filter_boxes
def get_consistency_loss(teacher_boxes, student_boxes):
center_losses, size_losses, cls_losses = [], [], []
batch_normalizer = 0
for teacher_box, student_box in zip(teac... | 6,566 | 54.184874 | 148 | py |
3DTrans | 3DTrans-master/tools/ssl_utils/se_ssd.py | import torch
import torch.nn.functional as F
import numpy as np
from .semi_utils import reverse_transform, load_data_to_gpu, filter_boxes
from pcdet.ops.iou3d_nms.iou3d_nms_utils import boxes_iou3d_gpu
def get_iou_consistency_loss(teacher_boxes, student_boxes):
box_losses, cls_losses = [], []
batch_normalizer ... | 5,617 | 51.018519 | 148 | py |
3DTrans | 3DTrans-master/tools/ssl_utils/pseudo_label.py | import torch
from .semi_utils import reverse_transform, load_data_to_gpu, construct_pseudo_label
def pseudo_label(teacher_model, student_model,
ld_teacher_batch_dict, ld_student_batch_dict,
ud_teacher_batch_dict, ud_student_batch_dict,
cfgs, epoch_id, dist
... | 2,249 | 42.269231 | 130 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_active_CLUE.py | import glob
import os
import pickle
from symbol import parameters
import torch
import tqdm
import time
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils, commu_utils, self_training_utils
from pcdet.models import load_data_to_gpu
from pcdet.datasets import build_dataloader, build_dataloade... | 11,006 | 41.334615 | 170 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_active_source_utils.py | from dis import dis
import glob
import os
import pickle
import torch
import tqdm
import time
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils, commu_utils, self_training_utils
from pcdet.models import load_data_to_gpu
from pcdet.datasets import build_dataloader, build_dataloader_ada
from... | 29,688 | 43.31194 | 175 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_st_utils.py | import torch
import os
import glob
import tqdm
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils
from pcdet.utils import self_training_utils
from pcdet.config import cfg
from .train_utils import save_checkpoint, checkpoint_state
def train_one_epoch_st(model, optimizer, source_reader, tar... | 8,582 | 46.41989 | 125 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_utils.py | import glob
import os
import torch
import tqdm
import time
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils, commu_utils
def train_one_epoch(model, optimizer, train_loader, model_func, lr_scheduler, accumulated_iter, optim_cfg,
rank, tbar, total_it_each_epoch, datal... | 6,737 | 38.174419 | 132 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_active_target_utils.py | import glob
import os
import pickle
import torch
import tqdm
import time
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils, commu_utils
from pcdet.utils import active_learning_utils
from pcdet.datasets import build_dataloader_ada
from pcdet.models import load_data_to_gpu
def train_detect... | 15,815 | 40.952255 | 167 | py |
3DTrans | 3DTrans-master/tools/train_utils/active_with_st3d_utils.py | import glob
import os
import torch
import tqdm
import time
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils, commu_utils
from pcdet.utils import active_learning_utils, self_training_utils
from pcdet.datasets import build_dataloader_ada
from pcdet.models import load_data_to_gpu
def tra... | 32,330 | 41.318063 | 167 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_semi_utils.py | import glob
import os
import math
import torch
import tqdm
from torch.nn.utils import clip_grad_norm_
def train_one_epoch(model, optimizer, train_loader, model_func, lr_scheduler, accumulated_iter, cur_epoch, optim_cfg,
rank, tbar, total_it_each_epoch, dataloader_iter, tb_log=None, leave_pbar=False... | 6,704 | 37.757225 | 117 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_active_utils.py | from dis import dis
import glob
import os
import pickle
import torch
import tqdm
import time
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils, commu_utils, self_training_utils
from pcdet.models import load_data_to_gpu
from pcdet.datasets import build_dataloader, build_dataloader_ada
from... | 37,649 | 41.067039 | 167 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_pseudo_label_utils.py | import glob
import os
import torch
import tqdm
import time
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils, commu_utils
from pcdet.utils import self_training_utils
def train_detector(model, model_func, optimizer, lr_scheduler, labeled_loader, unlabeled_loader, labeled_loader_iter,
... | 8,615 | 40.423077 | 151 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_multi_db_utils_3cls.py | import glob
import os
import torch
import tqdm
import time
import math
import copy
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils, commu_utils
from pcdet.utils import self_training_utils
from pcdet.config import cfg
def train_one_epoch(model, optimizer, train_loader_1, train_loader_2... | 8,627 | 39.317757 | 163 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_multi_db_loss_merge.py | import torch
import os
import glob
import tqdm
from torch.nn.utils import clip_grad_norm_
def visualize_boxes_batch(batch):
import visualize_utils as vis
import mayavi.mlab as mlab
for b_idx in range(batch['batch_size']):
points = batch['points'][batch['points'][:, 0] == b_idx][:, 1:]
if ... | 8,641 | 40.152381 | 133 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_multi_db_utils.py | import glob
import os
import torch
import tqdm
import time
import math
import copy
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils, commu_utils
from pcdet.utils import self_training_utils
from pcdet.config import cfg
def train_one_epoch(model, optimizer, train_loader_1, train_loader_2... | 10,562 | 43.758475 | 163 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_active_TQS.py | import glob
import os
import pickle
from symbol import parameters
import torch
import tqdm
import time
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils, commu_utils, self_training_utils
from pcdet.models import load_data_to_gpu
from pcdet.datasets import build_dataloader, build_dataloade... | 23,288 | 39.362218 | 170 | py |
3DTrans | 3DTrans-master/tools/train_utils/train_random_utils.py | import glob
import os
import torch
import tqdm
import time
from torch.nn.utils import clip_grad_norm_
from pcdet.utils import common_utils, commu_utils, active_learning_utils
def train_one_epoch(model, optimizer, train_source_loader, train_target_loader, model_func, lr_scheduler, accumulated_iter, optim_cfg,
... | 15,415 | 42.548023 | 134 | py |
3DTrans | 3DTrans-master/tools/train_utils/optimization/fastai_optim.py | # This file is modified from https://github.com/traveller59/second.pytorch
try:
from collections.abc import Iterable
except:
from collections import Iterable
import torch
from torch import nn
from torch._utils import _unflatten_dense_tensors
from torch.nn.utils import parameters_to_vector
bn_types = (nn.Batc... | 10,535 | 38.758491 | 117 | py |
3DTrans | 3DTrans-master/tools/train_utils/optimization/learning_schedules_fastai.py | # This file is modified from https://github.com/traveller59/second.pytorch
import math
from functools import partial
import numpy as np
import torch.optim.lr_scheduler as lr_sched
from .fastai_optim import OptimWrapper
class LRSchedulerStep(object):
def __init__(self, fai_optimizer: OptimWrapper, total_step, l... | 4,169 | 35.26087 | 118 | py |
3DTrans | 3DTrans-master/tools/train_utils/optimization/__init__.py | from functools import partial
import torch.nn as nn
import torch.optim as optim
import torch.optim.lr_scheduler as lr_sched
from .fastai_optim import OptimWrapper
from .learning_schedules_fastai import CosineWarmupLR, OneCycle
def build_optimizer(model, optim_cfg):
if optim_cfg.OPTIMIZER == 'adam':
opti... | 2,401 | 36.53125 | 113 | py |
3DTrans | 3DTrans-master/tools/visual_utils/open3d_vis_utils.py | """
Open3d visualization tool box
Written by Jihan YANG
All rights preserved from 2021 - present.
"""
import open3d
import torch
import matplotlib
import numpy as np
box_colormap = [
[1, 1, 1],
[0, 1, 0],
[0, 1, 1],
[1, 1, 0],
]
def get_coor_colors(obj_labels):
"""
Args:
obj_labels: 1... | 3,413 | 28.179487 | 126 | py |
3DTrans | 3DTrans-master/tools/visual_utils/visualize_utils.py | import mayavi.mlab as mlab
import numpy as np
import torch
box_colormap = [
[1, 1, 1],
[0, 1, 0],
[0, 1, 1],
[1, 1, 0],
]
def check_numpy_to_torch(x):
if isinstance(x, np.ndarray):
return torch.from_numpy(x).float(), True
return x, False
def rotate_points_along_z(points, angle):
... | 8,540 | 38.541667 | 121 | py |
3DTrans | 3DTrans-master/pcdet/config.py | from pathlib import Path
import yaml
from easydict import EasyDict
def log_config_to_file(cfg, pre='cfg', logger=None):
for key, val in cfg.items():
if isinstance(cfg[key], EasyDict):
logger.info('\n%s.%s = edict()' % (pre, key))
log_config_to_file(cfg[key], pre=pre + '.' + key, l... | 2,770 | 31.22093 | 94 | py |
3DTrans | 3DTrans-master/pcdet/__init__.py | import subprocess
from pathlib import Path
from .version import __version__
__all__ = [
'__version__'
]
def get_git_commit_number():
if not (Path(__file__).parent / '../.git').exists():
return '0000000'
cmd_out = subprocess.run(['git', 'rev-parse', 'HEAD'], stdout=subprocess.PIPE)
git_commi... | 535 | 20.44 | 82 | py |
3DTrans | 3DTrans-master/pcdet/models/__init__.py | from collections import namedtuple
import numpy as np
import torch
from .detectors import build_detector, build_detector_multi_db, build_detector_multi_db_3
try:
import kornia
except:
pass
# print('Warning: kornia is not installed. This package is only required by CaDDN')
def build_network(model_cfg, n... | 2,525 | 33.135135 | 139 | py |
3DTrans | 3DTrans-master/pcdet/models/mdf_models/dense_2d_moe_add_wo_SE.py | import copy
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from pcdet.utils import common_utils
def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
"""3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
... | 8,239 | 39 | 121 | py |
3DTrans | 3DTrans-master/pcdet/models/mdf_models/dense_2d_moe_add_wo_attention.py | import copy
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from pcdet.utils import common_utils
def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
"""3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
... | 7,968 | 38.450495 | 121 | py |
3DTrans | 3DTrans-master/pcdet/models/mdf_models/dense_3d_cr.py | import copy
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from pcdet.utils import common_utils
def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
"""3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
... | 7,057 | 38.430168 | 121 | py |
3DTrans | 3DTrans-master/pcdet/models/mdf_models/dense_cr.py | import copy
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from pcdet.utils import common_utils
def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
"""3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
... | 16,634 | 40.175743 | 121 | py |
3DTrans | 3DTrans-master/pcdet/models/mdf_models/__init__.py |
from .dense_3d_cr import DENSE_3D_CR
from .dense_3d_cr import DENSE_3D_DT
from .dense_cr import DENSE_2D_DT
from .dense_cr import DENSE_2D_CR_ADD
from .dense_cr import DENSE_CR
from .dense_cr import DENSE_2D_CR_ADD_SIM
from .dense_2d_moe_add_wo_SE import DENSE_2D_MoE_ADD_wo_SE
from .dense_2d_moe_add_wo_attention impo... | 672 | 29.590909 | 65 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/point_rcnn.py | from .detector3d_template import Detector3DTemplate
class PointRCNN(Detector3DTemplate):
def __init__(self, model_cfg, num_class, dataset):
super().__init__(model_cfg=model_cfg, num_class=num_class, dataset=dataset)
self.module_list = self.build_networks()
def forward(self, batch_dict):
... | 999 | 31.258065 | 83 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/pointpillar.py | from .detector3d_template import Detector3DTemplate
class PointPillar(Detector3DTemplate):
def __init__(self, model_cfg, num_class, dataset):
super().__init__(model_cfg=model_cfg, num_class=num_class, dataset=dataset)
self.module_list = self.build_networks()
def forward(self, batch_dict):
... | 1,018 | 28.114286 | 83 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/second_net.py | from .detector3d_template import Detector3DTemplate
class SECONDNet(Detector3DTemplate):
def __init__(self, model_cfg, num_class, dataset):
super().__init__(model_cfg=model_cfg, num_class=num_class, dataset=dataset)
self.module_list = self.build_networks()
def forward(self, batch_dict):
... | 1,016 | 28.057143 | 83 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/detector3d_template_IASSD.py | import os
import torch
import torch.nn as nn
from ...ops.iou3d_nms import iou3d_nms_utils
from ...utils.spconv_utils import find_all_spconv_keys
from .. import backbones_2d, backbones_3d, dense_heads, roi_heads
from ..backbones_2d import map_to_bev
from ..backbones_3d import pfe, vfe
from ..model_utils import model_n... | 19,155 | 45.382567 | 119 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/detector3d_template.py | import os
import torch
import torch.nn as nn
from ...ops.iou3d_nms import iou3d_nms_utils
from ...utils.spconv_utils import find_all_spconv_keys
from .. import backbones_2d, backbones_3d, dense_heads, roi_heads
from ..backbones_2d import map_to_bev
from ..backbones_3d import pfe, vfe
from ..model_utils import model_n... | 19,470 | 45.030733 | 119 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/pv_rcnn_plusplus.py | from .detector3d_template import Detector3DTemplate
from .detector3d_template_multi_db import Detector3DTemplate_M_DB
from pcdet.utils import common_utils
import numpy as np
class PVRCNNPlusPlus(Detector3DTemplate):
def __init__(self, model_cfg, num_class, dataset):
super().__init__(model_cfg=model_cfg, nu... | 14,722 | 44.301538 | 115 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/voxel_rcnn.py | from .detector3d_template import Detector3DTemplate
from .detector3d_template_ada import ActiveDetector3DTemplate
from .detector3d_template_multi_db import Detector3DTemplate_M_DB
from .detector3d_template_multi_db_3 import Detector3DTemplate_M_DB_3
from pcdet.utils import common_utils
from pcdet.config import cfg
cla... | 18,381 | 41.550926 | 138 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/caddn.py | from .detector3d_template import Detector3DTemplate
class CaDDN(Detector3DTemplate):
def __init__(self, model_cfg, num_class, dataset):
super().__init__(model_cfg=model_cfg, num_class=num_class, dataset=dataset)
self.module_list = self.build_networks()
def forward(self, batch_dict):
f... | 1,164 | 28.871795 | 83 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/detector3d_template_ada.py | import os
import torch
import torch.nn as nn
import torch.nn.functional as F
from ...ops.iou3d_nms import iou3d_nms_utils
from ...utils.spconv_utils import find_all_spconv_keys
from .. import backbones_2d, backbones_3d, dense_heads, roi_heads, active_models
from ..backbones_2d import map_to_bev
from ..backbones_3d im... | 23,013 | 47.348739 | 138 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/detector3d_template_multi_db.py | import os
import torch
import torch.nn as nn
from ...ops.iou3d_nms import iou3d_nms_utils
from ...utils.spconv_utils import find_all_spconv_keys
from .. import backbones_2d, backbones_3d, dense_heads, roi_heads, mdf_models
from ..backbones_2d import map_to_bev
from ..backbones_3d import pfe, vfe
from ..model_utils im... | 23,645 | 45.455796 | 119 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/PartA2_net.py | from .detector3d_template import Detector3DTemplate
class PartA2Net(Detector3DTemplate):
def __init__(self, model_cfg, num_class, dataset):
super().__init__(model_cfg=model_cfg, num_class=num_class, dataset=dataset)
self.module_list = self.build_networks()
def forward(self, batch_dict):
... | 1,072 | 32.53125 | 83 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/IASSD.py | from .detector3d_template_IASSD import Detector3DTemplate_IASSD
class IASSD(Detector3DTemplate_IASSD):
def __init__(self, model_cfg, num_class, dataset):
super().__init__(model_cfg=model_cfg, num_class=num_class, dataset=dataset)
self.module_list = self.build_networks()
def forward(self, batch... | 946 | 32.821429 | 83 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/pv_rcnn.py | import torch
from .detector3d_template import Detector3DTemplate
from .detector3d_template_multi_db import Detector3DTemplate_M_DB
from .detector3d_template_multi_db_3 import Detector3DTemplate_M_DB_3
from .detector3d_template_ada import ActiveDetector3DTemplate
from pcdet.utils import common_utils
class PVRCNN(Detect... | 23,337 | 43.880769 | 138 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/__init__.py | from .detector3d_template import Detector3DTemplate
from .detector3d_template_ada import ActiveDetector3DTemplate
from .detector3d_template_multi_db import Detector3DTemplate_M_DB
from .PartA2_net import PartA2Net
from .point_rcnn import PointRCNN
from .pointpillar import PointPillar
from .pv_rcnn import PVRCNN
from .p... | 3,713 | 36.14 | 140 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/detector3d_template_multi_db_3.py | import os
import torch
import torch.nn as nn
from ...ops.iou3d_nms import iou3d_nms_utils
from ...utils.spconv_utils import find_all_spconv_keys
from .. import backbones_2d, backbones_3d, dense_heads, roi_heads, mdf_models
from ..backbones_2d import map_to_bev
from ..backbones_3d import pfe, vfe
from ..model_utils im... | 26,507 | 45.916814 | 133 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/second_net_iou.py | import torch
from .detector3d_template import Detector3DTemplate
from .detector3d_template_ada import ActiveDetector3DTemplate
from ..model_utils.model_nms_utils import class_agnostic_nms, class_agnostic_nms_with_roi
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
import torch.nn.functional as F
class SECOND... | 17,487 | 43.161616 | 127 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/semi_second.py | import torch
from .detector3d_template import Detector3DTemplate
from ..model_utils.model_nms_utils import class_agnostic_nms
class SemiSECOND(Detector3DTemplate):
def __init__(self, model_cfg, num_class, dataset):
super().__init__(model_cfg=model_cfg, num_class=num_class, dataset=dataset)
self.mod... | 8,060 | 37.385714 | 112 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/centerpoint.py | from .detector3d_template import Detector3DTemplate
from .detector3d_template_multi_db import Detector3DTemplate_M_DB
from pcdet.utils import common_utils
class CenterPoint(Detector3DTemplate):
def __init__(self, model_cfg, num_class, dataset):
super().__init__(model_cfg=model_cfg, num_class=num_class, dat... | 8,824 | 35.770833 | 122 | py |
3DTrans | 3DTrans-master/pcdet/models/detectors/unsupervised_model/pvrcnn_plus_backbone.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from ..detector3d_template import Detector3DTemplate
from ....ops.pointnet2.pointnet2_stack import pointnet2_modules as pointnet2_stack_modules
from ....ops.pointnet2.pointnet2_stack import pointnet2_utils as pointnet2_stack_utils
fr... | 26,396 | 45.555556 | 152 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/IASSD_backbone.py | import torch
import torch.nn as nn
from ...ops.pointnet2.pointnet2_batch import pointnet2_modules
import os
class IASSD_Backbone(nn.Module):
""" Backbone for IA-SSD"""
def __init__(self, model_cfg, num_class, input_channels, **kwargs):
super().__init__()
self.model_cfg = model_cfg
sel... | 8,693 | 45.491979 | 150 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/spconv_unet.py | from functools import partial
import torch
import torch.nn as nn
from ...utils.spconv_utils import replace_feature, spconv
from ...utils import common_utils
from .spconv_backbone import post_act_block
class SparseBasicBlock(spconv.SparseModule):
expansion = 1
def __init__(self, inplanes, planes, stride=1, ... | 8,602 | 39.389671 | 117 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/spconv_backbone_unibn.py | from functools import partial
import torch.nn as nn
from ...utils.spconv_utils import replace_feature, spconv
from ...utils import uni3d_norm_2_in
def post_act_block(in_channels, out_channels, kernel_size, indice_key=None, stride=1, padding=0,
conv_type='subm'):
if conv_type == 'subm':
... | 14,619 | 37.072917 | 144 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/spconv_backbone.py | from functools import partial
import torch.nn as nn
from ...utils.spconv_utils import replace_feature, spconv
def post_act_block(in_channels, out_channels, kernel_size, indice_key=None, stride=1, padding=0,
conv_type='subm', norm_fn=None):
if conv_type == 'subm':
conv = spconv.SubMCo... | 20,640 | 37.581308 | 152 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/__init__.py | from .pointnet2_backbone import PointNet2Backbone, PointNet2MSG
from .spconv_backbone import VoxelBackBone8x, VoxelResBackBone8x, VoxelWideResBackBone8x, VoxelWideResBackBone_L8x
from .spconv_backbone_unibn import VoxelBackBone8x_UniBN, VoxelResBackBone8x_UniBN
from .spconv_unet import UNetV2
from .IASSD_backbone impor... | 830 | 40.55 | 114 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/pointnet2_backbone.py | import torch
import torch.nn as nn
from ...ops.pointnet2.pointnet2_batch import pointnet2_modules
from ...ops.pointnet2.pointnet2_stack import pointnet2_modules as pointnet2_modules_stack
from ...ops.pointnet2.pointnet2_stack import pointnet2_utils as pointnet2_utils_stack
class PointNet2MSG(nn.Module):
def __in... | 8,540 | 40.26087 | 132 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/pfe/unet_scn.py | from functools import partial
import torch
import torch.nn as nn
from pcdet.utils.spconv_utils import replace_feature, spconv
from pcdet.utils import common_utils
from pcdet.models.backbones_3d.spconv_backbone import post_act_block
class SparseBasicBlock(spconv.SparseModule):
expansion = 1
def __init__(sel... | 8,709 | 39.138249 | 117 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/pfe/point_t_trans.py | import copy
import numpy as np
import torch
import torch.nn as nn
from ....utils import uni3d_norm_2_in
class POINT_T(nn.Module):
def __init__(self, model_cfg, **kwargs):
super().__init__()
self.model_cfg = model_cfg
# using the domain-specific norm
self.scale_bn =... | 1,448 | 33.5 | 89 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/pfe/__init__.py | from .voxel_set_abstraction import VoxelSetAbstraction
from .point_t_trans import POINT_T
from .unet_scn import UNetSCN
__all__ = {
'VoxelSetAbstraction': VoxelSetAbstraction,
'POINT_T':POINT_T,
'UNetSCN':UNetSCN,
}
| 229 | 22 | 54 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/pfe/voxel_set_abstraction.py | import math
import numpy as np
import torch
import torch.nn as nn
from ....ops.pointnet2.pointnet2_stack import pointnet2_modules as pointnet2_stack_modules
from ....ops.pointnet2.pointnet2_stack import pointnet2_utils as pointnet2_stack_utils
from ....utils import common_utils
from ....utils import uni3d_norm
def b... | 18,045 | 39.920635 | 130 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/vfe_template.py | import torch.nn as nn
class VFETemplate(nn.Module):
def __init__(self, model_cfg, **kwargs):
super().__init__()
self.model_cfg = model_cfg
def get_output_feature_dim(self):
raise NotImplementedError
def forward(self, **kwargs):
"""
Args:
**kwargs:
... | 470 | 19.478261 | 45 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/dynamic_mean_vfe.py | import torch
from .vfe_template import VFETemplate
try:
import torch_scatter
except Exception as e:
# Incase someone doesn't want to use dynamic pillar vfe and hasn't installed torch_scatter
pass
from .vfe_template import VFETemplate
class DynamicMeanVFE(VFETemplate):
def __init__(self, model_cfg, ... | 2,980 | 37.714286 | 106 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/mean_vfe.py | import torch
from .vfe_template import VFETemplate
class MeanVFE(VFETemplate):
def __init__(self, model_cfg, num_point_features, **kwargs):
super().__init__(model_cfg=model_cfg)
self.num_point_features = num_point_features
def get_output_feature_dim(self):
return self.num_point_featu... | 1,038 | 31.46875 | 99 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/dynamic_pillar_vfe.py | import torch
import torch.nn as nn
import torch.nn.functional as F
try:
import torch_scatter
except Exception as e:
# Incase someone doesn't want to use dynamic pillar vfe and hasn't installed torch_scatter
pass
from .vfe_template import VFETemplate
class PFNLayerV2(nn.Module):
def __init__(self,
... | 5,614 | 38.265734 | 118 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/pillar_vfe.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from .vfe_template import VFETemplate
class PFNLayer(nn.Module):
def __init__(self,
in_channels,
out_channels,
use_norm=True,
last_layer=False):
super().__init__()
... | 5,099 | 40.129032 | 137 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/__init__.py | from .mean_vfe import MeanVFE
from .pillar_vfe import PillarVFE
from .dynamic_mean_vfe import DynamicMeanVFE
from .dynamic_pillar_vfe import DynamicPillarVFE
from .image_vfe import ImageVFE
from .vfe_template import VFETemplate
__all__ = {
'VFETemplate': VFETemplate,
'MeanVFE': MeanVFE,
'PillarVFE': Pillar... | 425 | 25.625 | 48 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe.py | import torch
from .vfe_template import VFETemplate
from .image_vfe_modules import ffn, f2v
class ImageVFE(VFETemplate):
def __init__(self, model_cfg, grid_size, point_cloud_range, depth_downsample_factor, **kwargs):
super().__init__(model_cfg=model_cfg)
self.grid_size = grid_size
self.pc_... | 2,526 | 28.383721 | 99 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/__init__.py | 0 | 0 | 0 | py | |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/depth_ffn.py | import torch.nn as nn
import torch.nn.functional as F
from . import ddn, ddn_loss
from pcdet.models.model_utils.basic_block_2d import BasicBlock2D
class DepthFFN(nn.Module):
def __init__(self, model_cfg, downsample_factor):
"""
Initialize frustum feature network via depth distribution estimation... | 3,778 | 35.336538 | 96 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/__init__.py | from .depth_ffn import DepthFFN
__all__ = {
'DepthFFN': DepthFFN
}
| 72 | 11.166667 | 31 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/ddn/ddn_deeplabv3.py | from .ddn_template import DDNTemplate
try:
import torchvision
except:
pass
class DDNDeepLabV3(DDNTemplate):
def __init__(self, backbone_name, **kwargs):
"""
Initializes DDNDeepLabV3 model
Args:
backbone_name: string, ResNet Backbone Name [ResNet50/ResNet101]
"... | 674 | 26 | 77 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/ddn/__init__.py | from .ddn_deeplabv3 import DDNDeepLabV3
__all__ = {
'DDNDeepLabV3': DDNDeepLabV3
}
| 88 | 13.833333 | 39 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/ddn/ddn_template.py | from collections import OrderedDict
from pathlib import Path
from torch import hub
import torch
import torch.nn as nn
import torch.nn.functional as F
try:
from kornia.enhance.normalize import normalize
except:
pass
# print('Warning: kornia is not installed. This package is only required by CaDDN')
c... | 5,941 | 35.453988 | 106 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/ddn_loss/balancer.py | import torch
import torch.nn as nn
from pcdet.utils import loss_utils
class Balancer(nn.Module):
def __init__(self, fg_weight, bg_weight, downsample_factor=1):
"""
Initialize fixed foreground/background loss balancer
Args:
fg_weight: float, Foreground loss weight
b... | 1,806 | 34.431373 | 102 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/ddn_loss/__init__.py | from .ddn_loss import DDNLoss
__all__ = {
"DDNLoss": DDNLoss
}
| 68 | 10.5 | 29 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/ffn/ddn_loss/ddn_loss.py | import torch
import torch.nn as nn
from .balancer import Balancer
from pcdet.utils import transform_utils
try:
from kornia.losses.focal import FocalLoss
except:
pass
# print('Warning: kornia is not installed. This package is only required by CaDDN')
class DDNLoss(nn.Module):
def __init__(self... | 2,428 | 30.960526 | 97 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/frustum_to_voxel.py | import torch
import torch.nn as nn
from .frustum_grid_generator import FrustumGridGenerator
from .sampler import Sampler
class FrustumToVoxel(nn.Module):
def __init__(self, model_cfg, grid_size, pc_range, disc_cfg):
"""
Initializes module to transform frustum features to voxel features via 3D tr... | 2,338 | 41.527273 | 109 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/frustum_grid_generator.py | import torch
import torch.nn as nn
try:
from kornia.utils.grid import create_meshgrid3d
from kornia.geometry.linalg import transform_points
except Exception as e:
# Note: Kornia team will fix this import issue to try to allow the usage of lower torch versions.
# print('Warning: kornia is not installed ... | 6,249 | 41.808219 | 201 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/sampler.py | import torch
import torch.nn as nn
import torch.nn.functional as F
class Sampler(nn.Module):
def __init__(self, mode="bilinear", padding_mode="zeros"):
"""
Initializes module
Args:
mode: string, Sampling mode [bilinear/nearest]
padding_mode: string, Padding mode fo... | 980 | 30.645161 | 111 | py |
3DTrans | 3DTrans-master/pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/__init__.py | from .frustum_to_voxel import FrustumToVoxel
__all__ = {
'FrustumToVoxel': FrustumToVoxel
}
| 97 | 15.333333 | 44 | py |
3DTrans | 3DTrans-master/pcdet/models/active_models/discriminator.py | from xml.dom.minidom import DOMImplementation
import torch
import torch.nn as nn
import torch.nn.functional as F
import math
class ActiveDiscriminator(nn.Module):
def __init__(self, model_cfg):
super().__init__()
self.model_cfg = model_cfg
self.fc = nn.Linear(model_cfg['FEATURE_DIM'], 1)
... | 2,477 | 41.724138 | 163 | py |
3DTrans | 3DTrans-master/pcdet/models/active_models/discriminator_from_bev.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class BEVDiscriminator_Conv(nn.Module):
def __init__(self, model_cfg):
super().__init__()
c_in = model_cfg['FEATURE_DIM']
c_out = model_cfg['FEATURE_DIM'] // 4
self.c_out = c_out
self.block = nn.... | 13,106 | 42.115132 | 163 | py |
3DTrans | 3DTrans-master/pcdet/models/active_models/__init__.py | from .discriminator import ActiveDiscriminator
from .discriminator_from_bev import BEVDiscriminator_Conv
from .discriminator_from_bev import BEVDiscriminator_Conv_2
from .discriminator_from_bev import BEVDiscriminator_Center
from .discriminator_from_bev import BEVDiscriminator_TQS
from .discriminator_from_bev import BE... | 698 | 42.6875 | 63 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/anchor_head_single.py | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from .anchor_head_template import AnchorHeadTemplate
class AnchorHeadSingle(AnchorHeadTemplate):
def __init__(self, model_cfg, input_channels, num_class, class_names, grid_size, point_cloud_range,
predict_boxes_... | 14,330 | 41.907186 | 178 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/point_head_template.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
from ...utils import common_utils, loss_utils
class PointHeadTemplate(nn.Module):
def __init__(self, model_cfg, num_class):
super().__init__()
self.model_cfg = model_cfg
... | 9,776 | 45.336493 | 119 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/anchor_head_template.py | import numpy as np
import torch
import torch.nn as nn
from ...utils import box_coder_utils, common_utils, loss_utils
from .target_assigner.anchor_generator import AnchorGenerator
from .target_assigner.atss_target_assigner import ATSSTargetAssigner
from .target_assigner.axis_aligned_target_assigner import AxisAlignedTa... | 12,364 | 43.800725 | 118 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/center_head_semi.py | import copy
import numpy as np
import torch
import torch.nn as nn
from torch.nn.init import kaiming_normal_
from ..model_utils import model_nms_utils
from ..model_utils import centernet_utils
from ...utils import loss_utils
class SeparateHead(nn.Module):
def __init__(self, input_channels, sep_head_dict, init_bias... | 18,189 | 44.588972 | 125 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/anchor_head_multi.py | import numpy as np
import torch
import torch.nn as nn
from ..backbones_2d import BaseBEVBackbone
from .anchor_head_template import AnchorHeadTemplate
class SingleHead(BaseBEVBackbone):
def __init__(self, model_cfg, input_channels, num_class, num_anchors_per_location, code_size, rpn_head_cfg=None,
... | 17,041 | 44.566845 | 117 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/center_head.py | import copy
import numpy as np
import torch
import torch.nn as nn
from torch.nn.init import kaiming_normal_
from ..model_utils import model_nms_utils
from ..model_utils import centernet_utils
from ...utils import loss_utils
class SeparateHead(nn.Module):
def __init__(self, input_channels, sep_head_dict, init_bias... | 30,472 | 45.101362 | 125 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/anchor_head_semi.py | import numpy as np
import torch.nn as nn
from .anchor_head_template import AnchorHeadTemplate
class AnchorHeadSemi(AnchorHeadTemplate):
def __init__(self, model_cfg, input_channels, num_class, class_names, grid_size, voxel_size, point_cloud_range,
predict_boxes_when_training=True):
super(... | 4,321 | 39.018519 | 136 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/point_head_box.py | import torch
from ...utils import box_coder_utils, box_utils
from .point_head_template import PointHeadTemplate
class PointHeadBox(PointHeadTemplate):
"""
A simple point-based segmentation head, which are used for PointRCNN.
Reference Paper: https://arxiv.org/abs/1812.04244
PointRCNN: 3D Object Propo... | 4,930 | 41.508621 | 106 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/point_head_simple.py | import torch
from ...utils import box_utils
from .point_head_template import PointHeadTemplate
class PointHeadSimple(PointHeadTemplate):
"""
A simple point-based segmentation head, which are used for PV-RCNN keypoint segmentaion.
Reference Paper: https://arxiv.org/abs/1912.13192
PV-RCNN: Point-Voxel ... | 4,255 | 39.150943 | 128 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/point_head_semi.py | import torch
from ...utils import box_utils
from .point_head_template import PointHeadTemplate
class PointHeadSemi(PointHeadTemplate):
"""
A simple point-based segmentation head, which are used for PV-RCNN keypoint segmentaion.
Reference Paper: https://arxiv.org/abs/1912.13192
PV-RCNN: Point-Voxel Fe... | 4,820 | 38.842975 | 128 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/__init__.py | from .anchor_head_multi import AnchorHeadMulti
from .anchor_head_single import AnchorHeadSingle
from .anchor_head_single import ActiveAnchorHeadSingle1
from .anchor_head_single import AnchorHeadSingle_TQS
from .anchor_head_template import AnchorHeadTemplate
from .point_head_box import PointHeadBox
from .point_head_simp... | 1,302 | 39.71875 | 59 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/point_intra_part_head.py | import torch
from ...utils import box_coder_utils, box_utils
from .point_head_template import PointHeadTemplate
class PointIntraPartOffsetHead(PointHeadTemplate):
"""
Point-based head for predicting the intra-object part locations.
Reference Paper: https://arxiv.org/abs/1907.03670
From Points to Part... | 5,568 | 42.507813 | 107 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/IASSD_head.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from ...utils import box_coder_utils, box_utils, loss_utils, common_utils
from .point_head_template import PointHeadTemplate
from ...ops.roiaware_pool3d import roiaware_pool3d_utils
class IASSD_Head(PointHeadTemplate):
"""
A simple point-base... | 42,278 | 49.212589 | 259 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/target_assigner/anchor_generator.py | import torch
class AnchorGenerator(object):
def __init__(self, anchor_range, anchor_generator_config):
super().__init__()
self.anchor_generator_cfg = anchor_generator_config
self.anchor_range = anchor_range
self.anchor_sizes = [config['anchor_sizes'] for config in anchor_generator_... | 3,990 | 48.8875 | 122 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/target_assigner/axis_aligned_target_assigner.py | import numpy as np
import torch
from ....ops.iou3d_nms import iou3d_nms_utils
from ....utils import box_utils
class AxisAlignedTargetAssigner(object):
def __init__(self, model_cfg, class_names, box_coder, match_height=False):
super().__init__()
anchor_generator_cfg = model_cfg.ANCHOR_GENERATOR_C... | 10,465 | 47.453704 | 140 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/target_assigner/atss_target_assigner.py | import torch
from ....ops.iou3d_nms import iou3d_nms_utils
from ....utils import common_utils
class ATSSTargetAssigner(object):
"""
Reference: https://arxiv.org/abs/1912.02424
"""
def __init__(self, topk, box_coder, match_height=False):
self.topk = topk
self.box_coder = box_coder
... | 6,050 | 41.612676 | 117 | py |
3DTrans | 3DTrans-master/pcdet/models/dense_heads/target_assigner/__init__.py | 0 | 0 | 0 | py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.