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Functions197 in github.com/Jun-CEN/Open-world-3D-semantic-segmentation

⨍ Functions 197◇ Types & classes 27
Method__getitem__
(self, index)
dataloader/dataset_nuscenes.py:410
Method__init__
(self)
utils/lovasz_losses.py:133
Method__init__
Initialization
dataloader/dataset_semantickitti.py:37
Method__init__
(self, in_dataset, grid_size, rotate_aug=False, flip_aug=False, ignore_label=255, return_test=False,
dataloader/dataset_semantickitti.py:145
Method__init__
(self, in_dataset, grid_size, rotate_aug=False, flip_aug=False, ignore_label=255, return_test=False,
dataloader/dataset_semantickitti.py:279
Method__init__
(self, in_dataset, grid_size, rotate_aug=False, flip_aug=False, ignore_label=255, return_test=False,
dataloader/dataset_semantickitti.py:413
Method__init__
(self, in_dataset, grid_size, rotate_aug=False, flip_aug=False, ignore_label=255, return_test=False,
dataloader/dataset_semantickitti.py:569
Method__init__
(self, in_dataset, grid_size, rotate_aug=False, flip_aug=False, ignore_label=255, return_test=False,
dataloader/dataset_semantickitti.py:732
Method__init__
(self, data_path, imageset='demo', return_ref=True, label_mapping="semantic-kitti.yaml", demo
dataloader/pc_dataset.py:31
Method__init__
(self, data_path, imageset='train', return_ref=False, label_mapping="semantic-kitti.yaml", nu
dataloader/pc_dataset.py:66
Method__init__
(self, data_path, imageset='train', return_ref=False, label_mapping="semantic-kitti.yaml", nu
dataloader/pc_dataset.py:114
Method__init__
(self, data_path, imageset='train', return_ref=False, label_mapping="semantic-kitti.yaml", nu
dataloader/pc_dataset.py:156
Method__init__
(self, data_path, imageset='train', return_ref=False, label_mapping="nuscenes.yaml", nusc=Non
dataloader/pc_dataset.py:211
Method__init__
(self, data_path, imageset='train', return_ref=False, label_mapping="nuscenes.yaml", nusc=Non
dataloader/pc_dataset.py:250
Method__init__
(self, data_path, imageset='train', return_ref=False, label_mapping="nuscenes.yaml", nusc=Non
dataloader/pc_dataset.py:301
Method__init__
(self, data_path, imageset='train',return_ref=False, label_mapping="semantic-kitti-multiscan.yaml")
dataloader/pc_dataset.py:369
Method__init__
Initialization
dataloader/dataset_nuscenes.py:26
Method__init__
Initialization
dataloader/dataset_nuscenes.py:138
Method__init__
Initialization
dataloader/dataset_nuscenes.py:250
Method__init__
Initialization
dataloader/dataset_nuscenes.py:385
Method__init__
(self, grid_size, fea_dim=3, out_pt_fea_dim=64, max_pt_per_encode=64, fea_compre=None)
network/cylinder_fea_generator.py:15
Method__init__
(self, cylin_model, segmentator_spconv, sparse_shape,
network/cylinder_spconv_3d.py:27
Method__init__
(self, in_filters, out_filters, kernel_size=(3, 3, 3), stride=1, indice_key=None)
network/segmentator_3d_asymm_spconv.py:47
Method__init__
(self, in_filters, out_filters, dropout_rate, kernel_size=(3, 3, 3), stride=1, pooling=True,
network/segmentator_3d_asymm_spconv.py:95
Method__init__
(self, in_filters, out_filters, kernel_size=(3, 3, 3), stride=1, indice_key=None)
network/segmentator_3d_asymm_spconv.py:216
Method__init__
(self, in_filters, out_filters, kernel_size=(3, 3, 3), stride=1, indice_key=None)
network/segmentator_3d_asymm_spconv.py:249
Method__init__
(self, output_shape, use_norm=True, num_input_features=128,
network/segmentator_3d_asymm_spconv.py:289
Method__len__
Denotes the total number of samples
dataloader/dataset_semantickitti.py:50
Method__len__
Denotes the total number of samples
dataloader/dataset_semantickitti.py:165
Method__len__
Denotes the total number of samples
dataloader/dataset_semantickitti.py:299
Method__len__
Denotes the total number of samples
dataloader/dataset_semantickitti.py:434
Method__len__
Denotes the total number of samples
dataloader/dataset_semantickitti.py:591
Method__len__
Denotes the total number of samples
dataloader/dataset_semantickitti.py:746
Method__len__
Denotes the total number of samples
dataloader/pc_dataset.py:46
Method__len__
Denotes the total number of samples
dataloader/pc_dataset.py:86
Method__len__
Denotes the total number of samples
dataloader/pc_dataset.py:134
Method__len__
Denotes the total number of samples
dataloader/pc_dataset.py:184
Method__len__
Denotes the total number of samples
dataloader/pc_dataset.py:226
Method__len__
Denotes the total number of samples
dataloader/pc_dataset.py:273
Method__len__
Denotes the total number of samples
dataloader/pc_dataset.py:317
Method__len__
Denotes the total number of samples
dataloader/pc_dataset.py:399
Method__len__
(self)
dataloader/dataset_nuscenes.py:46
Method__len__
(self)
dataloader/dataset_nuscenes.py:158
Method__len__
(self)
dataloader/dataset_nuscenes.py:271
Method__len__
(self)
dataloader/dataset_nuscenes.py:407
Functionbinary_xloss
Binary Cross entropy loss logits: [B, H, W] Variable, logits at each pixel (between -\infty and +\infty) labels: [B, H, W] Tensor, bi
utils/lovasz_losses.py:141
Functionbuild
(dataset_config, train_dataloader_config, val_dataloader_config, grid_size=[480,
builder/data_builder.py:10
Functionbuild
(model_config)
builder/model_builder.py:10
Functionbuild
(wce=True, lovasz=True, num_class=20, ignore_label=0)
builder/loss_builder.py:9
Functionbuild_ood
(wce=True, lovasz=True, num_class=20, ignore_label=0, weight=1)
builder/loss_builder.py:22
Functioncollate_fn_BEV
(data)
dataloader/dataset_semantickitti.py:857
Functioncollate_fn_BEV
(data)
dataloader/dataset_nuscenes.py:543
Functioncollate_fn_BEV_incre
(data)
dataloader/dataset_semantickitti.py:848
Functioncollate_fn_BEV_test
(data)
dataloader/dataset_semantickitti.py:874
Functioncollate_fn_BEV_val
(data)
dataloader/dataset_semantickitti.py:865
Functionconv1x1
(in_planes, out_planes, stride=1, indice_key=None)
network/segmentator_3d_asymm_spconv.py:41
Methodforward
(self, input, target)
utils/lovasz_losses.py:135
Methodforward
(self, pt_fea, xy_ind)
network/cylinder_fea_generator.py:55
Methodforward
(self, x)
network/segmentator_3d_asymm_spconv.py:73
Methodforward
(self, x)
network/segmentator_3d_asymm_spconv.py:132
Methodforward
(self, x, skip)
network/segmentator_3d_asymm_spconv.py:190
Methodforward
(self, x)
network/segmentator_3d_asymm_spconv.py:230
Methodforward
(self, x)
network/segmentator_3d_asymm_spconv.py:266
Methodforward
(self, voxel_features, coors, batch_size)
network/segmentator_3d_asymm_spconv.py:323
Methodforward_DML
(self, voxel_features, coors, batch_size)
network/segmentator_3d_asymm_spconv.py:573
Methodforward_dropout
(self, voxel_features, coors, batch_size)
network/segmentator_3d_asymm_spconv.py:601
Methodforward_dropout_eval
(self, voxel_features, coors, batch_size)
network/segmentator_3d_asymm_spconv.py:628
Methodforward_dummy
(self, train_pt_fea_ten, train_vox_ten, batch_size, ood_num)
network/cylinder_spconv_3d.py:48
Methodforward_dummy
(self, voxel_features, coors, batch_size, ood_num)
network/segmentator_3d_asymm_spconv.py:375
Methodforward_dummy_2
(self, train_pt_fea_ten, train_vox_ten, batch_size, ood_num, point_label_tensor)
network/cylinder_spconv_3d.py:55
Methodforward_dummy_2
(self, voxel_features, coors, batch_size, ood_num, point_label_tensor)
network/segmentator_3d_asymm_spconv.py:407
Methodforward_dummy_3
(self, train_pt_fea_ten, train_vox_ten, batch_size, ood_num)
network/cylinder_spconv_3d.py:62
Methodforward_dummy_3
(self, voxel_features, coors, batch_size, ood_num)
network/segmentator_3d_asymm_spconv.py:452
Methodforward_dummy_4
(self, train_pt_fea_ten, train_vox_ten, batch_size, ood_num)
network/cylinder_spconv_3d.py:69
Methodforward_dummy_4
(self, voxel_features, coors, batch_size, ood_num)
network/segmentator_3d_asymm_spconv.py:486
Methodforward_dummy_final
(self, voxel_features, coors, batch_size, ood_num)
network/segmentator_3d_asymm_spconv.py:522
Methodforward_dummy_upper
(self, train_pt_fea_ten, train_vox_ten, batch_size, ood_num)
network/cylinder_spconv_3d.py:83
Methodforward_dummy_upper
(self, voxel_features, coors, batch_size, ood_num)
network/segmentator_3d_asymm_spconv.py:539
Methodforward_incremental
(self, voxel_features, coors, batch_size, incre_cls=None)
network/segmentator_3d_asymm_spconv.py:662
Functionhinge_jaccard_loss
Multi-class Hinge Jaccard loss probas: [B, C, H, W] Variable, class probabilities at each prediction (between 0 and 1). Inter
utils/lovasz_losses.py:261
Functioniou
Array of IoU for each (non ignored) class
utils/lovasz_losses.py:56
Functioniou_binary
IoU for foreground class binary: 1 foreground, 0 background
utils/lovasz_losses.py:36
Functionisnan
(x)
utils/lovasz_losses.py:298
Functionjaccard_loss
Something wrong with this loss Multi-class Lovasz-Softmax loss probas: [B, C, H, W] Variable, class probabilities at each prediction (b
utils/lovasz_losses.py:233
Functionlovasz_hinge
Binary Lovasz hinge loss logits: [B, H, W] Variable, logits at each pixel (between -\infty and +\infty) labels: [B, H, W] Tensor, bin
utils/lovasz_losses.py:81
Functionregister_dataset
(cls, name=None)
dataloader/dataset_semantickitti.py:20
Functionregister_dataset
(cls, name=None)
dataloader/pc_dataset.py:15
Functionregister_model
(cls, name=None)
network/cylinder_spconv_3d.py:10
Methodrotation_points_single_angle
(self, points, angle, axis=0)
dataloader/dataset_semantickitti.py:169
Methodrotation_points_single_angle
(self, points, angle, axis=0)
dataloader/dataset_semantickitti.py:303
Methodrotation_points_single_angle
(self, points, angle, axis=0)
dataloader/dataset_semantickitti.py:438
Methodrotation_points_single_angle
(self, points, angle, axis=0)
dataloader/dataset_semantickitti.py:595
Functionsave_config_data
(data: dict, path: str)
config/config.py:102
Functionsave_to_log
(logdir, logfile, message)
utils/log_util.py:6
Functionset_bn_eval
(m)
semantickitti_scripts/val_cylinder_asym_dropout.py:28
Functionset_bn_eval
(m)
nuScenes_scripts/val_cylinder_asym_nusc_dropout.py:28
Functionxloss
Cross entropy loss
utils/lovasz_losses.py:227
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