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Types & classes27 in github.com/Pulkit-Khandelwal/medical-mldg-seg

⨍ Functions 153◇ Types & classes 27
↓ 20 callersClassBatchImageGenerator
mldg-seg/data_reader_unet_spine.py:455
↓ 8 callersClassGeneralizedDiceLoss
Computes Generalized Dice Loss (GDL) as described in https://arxiv.org/pdf/1707.03237.pdf
mldg-seg/dice_loss.py:101
↓ 5 callersClassConvD
mldg-seg/Unet3D_meta_learning_orig.py:25
↓ 5 callersClassConvD
mldg-seg/Unet3D_meta_learning.py:25
↓ 4 callersClassConvU
mldg-seg/Unet3D_meta_learning_orig.py:65
↓ 4 callersClassConvU
mldg-seg/Unet3D_meta_learning.py:70
↓ 2 callersClassModel
postprocess/tsne.py:25
↓ 1 callersClassBCELossWrapper
Wrapper around BCE loss functions allowing to pass 'ignore_index' as well as 'skip_last_target' option.
mldg-seg/dice_loss.py:191
↓ 1 callersClassDiceCoeff
Dice coeff for individual examples
mldg-seg/dice_loss.py:12
↓ 1 callersClassDiceLoss
Computes Dice Loss, which just 1 - DiceCoefficient described above. Additionally allows per-class weights to be provided.
mldg-seg/dice_loss.py:61
↓ 1 callersClassMLDG
mldg-seg/meta_learning_spine.py:42
↓ 1 callersClassMSEWithLogitsLoss
This loss combines a `Sigmoid` layer and the `MSELoss` in one single class.
mldg-seg/dice_loss.py:261
↓ 1 callersClassModelBaseline
mldg-seg/fewshot_meta_learning.py:45
↓ 1 callersClassModelBaseline
mldg-seg/fewshot_baseline.py:44
↓ 1 callersClassModelBaseline
mldg-seg/baseline_spine.py:43
↓ 1 callersClassModelBaseline
mldg-seg/upper_bound_spine.py:44
↓ 1 callersClassPixelWiseCrossEntropyLoss
mldg-seg/dice_loss.py:221
↓ 1 callersClassTagsAngularLoss
mldg-seg/dice_loss.py:274
↓ 1 callersClassWeightedCrossEntropyLoss
WeightedCrossEntropyLoss (WCE) as described in https://arxiv.org/pdf/1707.03237.pdf
mldg-seg/dice_loss.py:164
ClassModelBaseline
postprocess/inference.py:25
ClassSubsetRandomSampler
r"""Samples elements randomly, without replacement. Arguments: data_source (Dataset): dataset to sample from
mldg-seg/meta_learning_spine.py:24
ClassSubsetRandomSampler
r"""Samples elements randomly, without replacement. Arguments: data_source (Dataset): dataset to sample from
mldg-seg/fewshot_meta_learning.py:26
ClassSubsetRandomSampler
r"""Samples elements randomly, without replacement. Arguments: data_source (Dataset): dataset to sample from
mldg-seg/fewshot_baseline.py:26
ClassSubsetRandomSampler
r"""Samples elements randomly, without replacement. Arguments: data_source (Dataset): dataset to sample from
mldg-seg/baseline_spine.py:25
ClassSubsetRandomSampler
r"""Samples elements randomly, without replacement. Arguments: data_source (Dataset): dataset to sample from
mldg-seg/upper_bound_spine.py:25
ClassUnet3D
mldg-seg/Unet3D_meta_learning_orig.py:108
ClassUnet3D
mldg-seg/Unet3D_meta_learning.py:115