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Functions419 in github.com/black0017/MedicalZooPytorch

⨍ Functions 419◇ Types & classes 94
Functionconv_block_1
(in_dim, out_dim)
lib/medzoo/HyperDensenet.py:74
Functionconv_block_3
(in_dim, out_dim, act_fn)
lib/medzoo/HyperDensenet.py:211
Functionconv_block_3_3
(in_dim, out_dim)
lib/medzoo/HyperDensenet.py:139
Functionconv_block_Asym
(in_dim, out_dim, kernelSize)
lib/medzoo/HyperDensenet.py:83
Functionconv_block_Asym_ERFNet
(in_dim, out_dim, kernelSize, padding, drop, dilation)
lib/medzoo/HyperDensenet.py:121
Functionconv_block_Asym_Inception
(in_dim, out_dim, kernel_size, padding, dilation=1)
lib/medzoo/HyperDensenet.py:93
Functionconv_block_Asym_Inception_WithIncreasedFeatMaps
(in_dim, mid_dim, out_dim, kernel_size, padding, dilation=1)
lib/medzoo/HyperDensenet.py:107
Functionconv_decod_block
(in_dim, out_dim, act_fn)
lib/medzoo/HyperDensenet.py:149
Methodcount_params
r""" Computes the number of parameters in this model. Args: None Returns: int: Total number of weight parameters
lib/medzoo/BaseModelClass.py:112
Functioncreate_model
(args)
lib/medzoo/__init__.py:20
Methoddice
(self, input, target, weight)
lib/losses3D/generalized_dice.py:19
Functiondilation_conv_block
(in_dim, out_dim, act_fn, stride_val, dil_val)
lib/medzoo/HyperDensenet.py:158
Functionfind3Dlabel_boundaries
(segmentation_map)
lib/medloaders/medical_loader_utils.py:226
Methodforward
(self, input, target)
lib/losses3D/weight_cross_entropy.py:14
Methodforward
Args: input (torch.tensor): embeddings predicted by the network (NxExDxHxW) (E - embedding dims) target (torch.tens
lib/losses3D/ContrastiveLoss.py:99
Methodforward
Expand to one hot added extra for consistency reasons
lib/losses3D/BaseClass.py:41
Methodforward
(self, input, target, weights)
lib/losses3D/pixel_wise_cross_entropy.py:13
Methodforward
(self, input, target)
lib/losses3D/__init__.py:68
Methodforward
(self, input, target)
lib/losses3D/__init__.py:91
Methodforward
(self, input, target)
lib/losses3D/Dice2D.py:48
Methodforward
(self, input, target)
lib/losses3D/BCE_dice.py:18
Methodforward
(self, inputs, targets, weight=None)
lib/losses3D/tags_angular_loss.py:14
Methodforward
(self, input, target)
lib/losses3D/weight_smooth_l1.py:15
Methodforward
(self, x)
lib/medzoo/ResNet3DMedNet.py:72
Methodforward
(self, x)
lib/medzoo/ResNet3DMedNet.py:106
Methodforward
(self, x)
lib/medzoo/ResNet3DMedNet.py:166
Methodforward
(self, x)
lib/medzoo/SkipDenseNet3D.py:30
Methodforward
(self, x)
lib/medzoo/HighResNet3D.py:23
Methodforward
(self, x)
lib/medzoo/HighResNet3D.py:41
Methodforward
(self, x)
lib/medzoo/HighResNet3D.py:56
Methodforward
(self, x)
lib/medzoo/HighResNet3D.py:72
Methodforward
(self, x)
lib/medzoo/HighResNet3D.py:88
Methodforward
(self, x)
lib/medzoo/Densenet3D.py:22
Methodforward
(self, x)
lib/medzoo/Vnet.py:33
Methodforward
(self, x)
lib/medzoo/Vnet.py:57
Methodforward
(self, x)
lib/medzoo/Vnet.py:79
Methodforward
(self, x, skipx)
lib/medzoo/Vnet.py:101
Methodforward
(self, x)
lib/medzoo/Vnet.py:121
Methodforward
(self, x)
lib/medzoo/ResNet3D_VAE.py:34
Methodforward
(self, x)
lib/medzoo/ResNet3D_VAE.py:49
Methodforward
(self, x)
lib/medzoo/ResNet3D_VAE.py:60
Methodforward
(self, x)
lib/medzoo/ResNet3D_VAE.py:74
Methodforward
(self, x)
lib/medzoo/ResNet3D_VAE.py:87
Methodforward
(self, x)
lib/medzoo/ResNet3D_VAE.py:130
Methodforward
(self, x1, x2, x3, x4)
lib/medzoo/ResNet3D_VAE.py:172
Methodforward
(self, x)
lib/medzoo/ResNet3D_VAE.py:233
Methodforward
(self, x)
lib/medzoo/Unet2D.py:21
Methodforward
(self, x)
lib/medzoo/Unet2D.py:31
Methodforward
(self, x)
lib/medzoo/Unet2D.py:44
Methodforward
(self, x1, x2)
lib/medzoo/Unet2D.py:60
Methodforward
(self, x)
lib/medzoo/Unet2D.py:78
Methodforward
(self, input)
lib/medzoo/COVIDNet.py:8
Methodforward
(self, x)
lib/medzoo/COVIDNet.py:44
Methodforward
(self, x)
lib/medzoo/COVIDNet.py:94
Methodforward
(self, x)
lib/medzoo/COVIDNet.py:191
Methodforward
(self, input)
lib/medzoo/HyperDensenet.py:53
Methodforward
(self, x)
lib/medzoo/DenseVoxelNet.py:38
Methodforward
(self, x)
lib/medzoo/DenseVoxelNet.py:68
Methodforward_large_net
(self, x)
lib/medzoo/COVIDNet.py:97
Methodforward_small_net
(self, x)
lib/medzoo/COVIDNet.py:142
Functiongenerate_datasets
(args, path='.././datasets')
lib/medloaders/__init__.py:16
Methodgenerate_train_labels
(self)
lib/medloaders/miccai_2019_pathology.py:125
Functionget_all_sub_volumes
(*ls, dataset_name, mode, samples, full_vol_dim, crop_size, sub_vol_path, normalizatio
lib/medloaders/medical_loader_utils.py:132
Functioninit_weights
The weights were randomly initialized with a Gaussian distribution (µ = 0, σ = 0.01)
lib/medzoo/DenseVoxelNet.py:16
Methodixi
(self)
tests/test_dataloaders.py:57
Functionload_2d_image
(img_path, resize_dim=0, type='RGB')
lib/medloaders/medical_image_process.py:105
Functionload_affine_matrix
Reads an path to nifti file and returns the affine matrix as numpy array 4x4
lib/medloaders/medical_image_process.py:97
Functionload_checkpoint
(checkpoint_path, model)
lib/utils/save_old.py:35
Functionload_list
(name)
lib/utils/general.py:120
Functionloss_vae
see Appendix B from VAE paper: Kingma and Welling. Auto-Encoding Variational Bayes. ICLR, 2014 # https://arxiv.org/abs/1312.6114 # 0.
lib/losses3D/VAEloss.py:7
Functionmake_dirs
(path)
lib/utils/general.py:107
Functionmaxpool
()
lib/medzoo/HyperDensenet.py:167
Functionmaxpool_1_16
()
lib/medzoo/HyperDensenet.py:202
Functionmaxpool_1_32
()
lib/medzoo/HyperDensenet.py:207
Functionmaxpool_1_4
()
lib/medzoo/HyperDensenet.py:192
Functionmaxpool_1_8
()
lib/medzoo/HyperDensenet.py:197
Functionmedical_image_transform
(img_tensor, type=None, normalization="full_volume_mean",
lib/medloaders/medical_image_process.py:50
Functionoverlap_2d_image
()
lib/visual3D_temp/viz_2d.py:122
Functionpassthrough
(x, **kwargs)
lib/medzoo/Vnet.py:14
Functionplot_confusion_matrix
(cm, target_names, title='Confusion matrix', cmap=None,
lib/visual3D_temp/conf_matrix.py:11
Functionplot_segm
Saves predicted and ground truth segmentation into a PNG files (one per channel). :param segm: 4D ndarray (CDHW) :param ground_truth: 4D
lib/visual3D_temp/viz_2d.py:92
Methodprint_all_metrics
(self)
lib/utils/covid_utils.py:61
Functionprint_stats
(args, epoch, num_samples, trainloader, metrics)
lib/utils/covid_utils.py:13
Functionprint_summary
(args, epoch, num_samples, metrics, mode='')
lib/utils/covid_utils.py:24
Functionreproducibility
(args, seed)
lib/utils/general.py:13
Functionsave_arguments
(args, path)
lib/utils/general.py:24
Functionsave_list
(name, list)
lib/utils/general.py:115
Functionsave_model
(model, args, dice_loss, epoch, best_pred_loss)
lib/utils/save_old.py:18
Functionselect_full_volume_for_infer
(args, path='.././datasets')
lib/medloaders/__init__.py:133
Functionshuffle_lists
(*ls, seed=777)
lib/utils/general.py:35
Methodtest
(self,device='cpu')
lib/medzoo/Unet3D.py:208
Methodtest
(self)
lib/medzoo/ResNet3DMedNet.py:284
Methodtest
(self,device='cpu')
lib/medzoo/SkipDenseNet3D.py:171
Methodtest
(self)
lib/medzoo/HighResNet3D.py:190
Methodtest
(self,device='cpu')
lib/medzoo/Densenet3D.py:133
Methodtest
(self,device='cpu')
lib/medzoo/Densenet3D.py:221
Methodtest
(self,device='cpu')
lib/medzoo/Densenet3D.py:299
Methodtest
(self,device='cpu')
lib/medzoo/Vnet.py:162
Methodtest
(self,device='cpu')
lib/medzoo/Vnet.py:203
Methodtest
(self)
lib/medzoo/ResNet3D_VAE.py:274
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