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Types & classes108 in github.com/JunMa11/SegLossOdyssey

⨍ Functions 250◇ Types & classes 108
↓ 7 callersClassSoftDiceLoss
test/nnUNetV2/loss_functions/dice_loss.py:159
↓ 6 callersClassWeightedCrossEntropyLoss
Network has to have NO NONLINEARITY!
test/nnUNetV1/loss_functions/ND_Crossentropy.py:106
↓ 5 callersClassExpLog_loss
paper: 3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes https://arxiv.org/pdf/1809.00076.pdf
test/nnUNetV1/loss_functions/dice_loss.py:546
↓ 5 callersClassSoftDiceLoss
test/nnUNetV1/loss_functions/dice_loss.py:249
↓ 4 callersClassRobustCrossEntropyLoss
this is just a compatibility layer because my target tensor is float and has an extra dimension
test/nnUNetV2/loss_functions/crossentropy.py:4
↓ 4 callersClassSoftDiceLossSquared
test/nnUNetV2/loss_functions/dice_loss.py:286
↓ 4 callersClassTopKLoss
Network has to have NO LINEARITY!
test/nnUNetV2/loss_functions/TopK_loss.py:20
↓ 3 callersClassSoftDiceLoss
losses_pytorch/dice_loss.py:255
↓ 2 callersClassCrossentropyND
Network has to have NO NONLINEARITY!
test/nnUNetV1/loss_functions/ND_Crossentropy.py:24
↓ 2 callersClassDC_and_BD_loss
test/nnUNetV1/loss_functions/boundary_loss.py:176
↓ 2 callersClassFocalLoss
copy from: https://github.com/Hsuxu/Loss_ToolBox-PyTorch/blob/master/FocalLoss/FocalLoss.py This is a implementation of Focal Loss with smoot
test/nnUNetV1/loss_functions/focal_loss.py:7
↓ 2 callersClassFocalLoss
copy from: https://github.com/Hsuxu/Loss_ToolBox-PyTorch/blob/master/FocalLoss/FocalLoss.py This is a implementation of Focal Loss with smoot
test/nnUNetV2/loss_functions/focal_loss.py:7
↓ 2 callersClassSoftDiceLoss
test/nnUNetV1/loss_functions/boundary_loss.py:64
↓ 2 callersClassTopKLoss
Network has to have NO LINEARITY!
test/nnUNetV1/loss_functions/TopK_loss.py:20
↓ 2 callersClassTverskyLoss
test/nnUNetV1/loss_functions/dice_loss.py:399
↓ 1 callersClassAsymLoss
test/nnUNetV1/loss_functions/dice_loss.py:456
↓ 1 callersClassBDLoss
test/nnUNetV1/loss_functions/boundary_loss.py:131
↓ 1 callersClassBDLoss
losses_pytorch/boundary_loss.py:82
↓ 1 callersClassCrossentropyND
Network has to have NO NONLINEARITY!
losses_pytorch/ND_Crossentropy.py:11
↓ 1 callersClassDC_and_CE_loss
test/nnUNetV1/loss_functions/dice_loss.py:495
↓ 1 callersClassDC_and_Focal_loss
test/nnUNetV2/loss_functions/dice_loss.py:470
↓ 1 callersClassDC_and_HD_loss
test/nnUNetV1/loss_functions/boundary_loss.py:286
↓ 1 callersClassDC_and_topk_loss
test/nnUNetV1/loss_functions/dice_loss.py:528
↓ 1 callersClassDC_and_topk_loss
test/nnUNetV2/loss_functions/dice_loss.py:450
↓ 1 callersClassDC_topk_ce_loss
test/nnUNetV2/loss_functions/dice_loss.py:484
↓ 1 callersClassDC_topk_focal_loss
test/nnUNetV2/loss_functions/dice_loss.py:506
↓ 1 callersClassFocalTversky_loss
paper: https://arxiv.org/pdf/1810.07842.pdf author code: https://github.com/nabsabraham/focal-tversky-unet/blob/347d39117c24540400dfe80d106d2
test/nnUNetV1/loss_functions/dice_loss.py:440
↓ 1 callersClassGDL
test/nnUNetV2/loss_functions/dice_loss.py:26
↓ 1 callersClassGDiceLoss
test/nnUNetV1/loss_functions/dice_loss.py:78
↓ 1 callersClassGDiceLoss
losses_pytorch/dice_loss.py:84
↓ 1 callersClassGDiceLossV2
test/nnUNetV1/loss_functions/dice_loss.py:137
↓ 1 callersClassHDLoss
test/nnUNetV1/loss_functions/boundary_loss.py:236
↓ 1 callersClassIoULoss
test/nnUNetV1/loss_functions/dice_loss.py:359
↓ 1 callersClassLovaszSoftmax
test/nnUNetV1/loss_functions/lovasz_loss.py:22
↓ 1 callersClassPenaltyGDiceLoss
paper: https://openreview.net/forum?id=H1lTh8unKN
test/nnUNetV1/loss_functions/dice_loss.py:511
↓ 1 callersClassSSLoss
test/nnUNetV1/loss_functions/dice_loss.py:186
↓ 1 callersClassSoftDiceLoss
losses_pytorch/boundary_loss.py:109
↓ 1 callersClassTopKLoss
Network has to have NO LINEARITY!
losses_pytorch/ND_Crossentropy.py:34
↓ 1 callersClassTverskyLoss
losses_pytorch/dice_loss.py:333
↓ 1 callersClassWeightedCrossEntropyLoss
Network has to have NO NONLINEARITY!
losses_pytorch/ND_Crossentropy.py:50
ClassAsymLoss
losses_pytorch/dice_loss.py:390
ClassCrossentropyNDTopK
Network has to have NO NONLINEARITY!
test/nnUNetV1/loss_functions/ND_Crossentropy.py:47
ClassDC_and_BCE_loss
test/nnUNetV2/loss_functions/dice_loss.py:405
ClassDC_and_BD_loss
losses_pytorch/boundary_loss.py:147
ClassDC_and_CE_loss
test/nnUNetV2/loss_functions/dice_loss.py:345
ClassDC_and_CE_loss
losses_pytorch/dice_loss.py:429
ClassDC_and_Focal_loss
test/nnUNetV1/loss_functions/dice_loss.py:571
ClassDC_and_topk_loss
losses_pytorch/dice_loss.py:462
ClassDisPenalizedCE
Only for binary 3D segmentation Network has to have NO NONLINEARITY!
losses_pytorch/ND_Crossentropy.py:168
ClassDistBinaryDiceLoss
Distance map penalized Dice loss Motivated by: https://openreview.net/forum?id=B1eIcvS45V Distance Map Loss Penalty Term for Semantic
losses_pytorch/boundary_loss.py:192
ClassDistPenalizedCE
Only for binary 3D segmentation Network has to have NO NONLINEARITY!
test/nnUNetV1/loss_functions/ND_Crossentropy.py:224
ClassExpLog_loss
paper: 3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes https://arxiv.org/pdf/1809.00076.pdf
losses_pytorch/dice_loss.py:480
ClassFocalLoss
copy from: https://github.com/Hsuxu/Loss_ToolBox-PyTorch/blob/master/FocalLoss/FocalLoss.py This is a implementation of Focal Loss with smo
losses_pytorch/focal_loss.py:7
ClassFocalTversky_loss
paper: https://arxiv.org/pdf/1810.07842.pdf author code: https://github.com/nabsabraham/focal-tversky-unet/blob/347d39117c24540400dfe80d106
losses_pytorch/dice_loss.py:374
ClassGDL_and_CE_loss
test/nnUNetV2/loss_functions/dice_loss.py:433
ClassGDiceLossV2
losses_pytorch/dice_loss.py:143
ClassHausdorffDTLoss
Binary Hausdorff loss based on distance transform
losses_pytorch/hausdorff.py:19
ClassHausdorffERLoss
Binary Hausdorff loss based on morphological erosion
losses_pytorch/hausdorff.py:83
ClassIoULoss
test/nnUNetV2/loss_functions/dice_loss.py:198
ClassIoULoss
losses_pytorch/dice_loss.py:293
ClassLovaszSoftmax
losses_pytorch/lovasz_loss.py:22
ClassMCCLoss
test/nnUNetV2/loss_functions/dice_loss.py:238
ClassNetworkTrainer
test/nnUNetV1/network_training/network_trainer.py:25
ClassPenaltyGDiceLoss
paper: https://openreview.net/forum?id=H1lTh8unKN
losses_pytorch/dice_loss.py:445
ClassSSLoss
losses_pytorch/dice_loss.py:192
ClassSoftDiceLossV2
test/nnUNetV1/loss_functions/dice_loss.py:319
ClassTopKThreshold
Network has to have NO LINEARITY!
test/nnUNetV1/loss_functions/ND_Crossentropy.py:73
ClassWeightedCrossEntropyLossV2
WeightedCrossEntropyLoss (WCE) as described in https://arxiv.org/pdf/1707.03237.pdf Network has to have NO LINEARITY! copy from: https://
test/nnUNetV1/loss_functions/ND_Crossentropy.py:134
ClassWeightedCrossEntropyLossV2
WeightedCrossEntropyLoss (WCE) as described in https://arxiv.org/pdf/1707.03237.pdf Network has to have NO LINEARITY! copy from: https
losses_pytorch/ND_Crossentropy.py:78
ClassnnUNetTrainer
test/nnUNetV1/network_training/nnUNetTrainer.py:26
ClassnnUNetTrainerCE
test/nnUNetV1/network_training/nnUNetTrainerCE.py:5
ClassnnUNetTrainerCascadeFullRes
test/nnUNetV1/network_training/nnUNetTrainerCascadeFullRes.py:17
ClassnnUNetTrainerEDT
test/nnUNetV1/network_training/nnUNetTrainerEDT.py:125
ClassnnUNetTrainerV2_Loss_CE
test/nnUNetV2/network_training/nnUNetTrainerV2_Loss_CE.py:18
ClassnnUNetTrainerV2_Loss_Dice
test/nnUNetV2/network_training/nnUNetTrainerV2_Loss_Dice.py:21
ClassnnUNetTrainerV2_Loss_DiceFocal
test/nnUNetV2/network_training/nnUNetTrainerV2_Loss_DiceFocal.py:5
ClassnnUNetTrainerV2_Loss_DiceTopK10
test/nnUNetV2/network_training/nnUNetTrainerV2_Loss_DiceTopK10.py:20
ClassnnUNetTrainerV2_Loss_DiceTopK10CE
test/nnUNetV2/network_training/nnUNetTrainerV2_Loss_DiceTopK10CE.py:20
ClassnnUNetTrainerV2_Loss_DiceTopK10Focal
test/nnUNetV2/network_training/nnUNetTrainerV2_Loss_DiceTopK10Focal.py:20
ClassnnUNetTrainerV2_Loss_TopK10
test/nnUNetV2/network_training/nnUNetTrainerV2_Loss_TopK10.py:20
ClassnnUNetTrainerWCE
test/nnUNetV1/network_training/nnUNetTrainerWCE.py:6
ClassnnUNetTrainerWCET0
test/nnUNetV1/network_training/nnUNetTrainerWCET0.py:6
ClassnnUNetTrainerWCET1
test/nnUNetV1/network_training/nnUNetTrainerWCET1.py:6
ClassnnUNetTrainerWCET2
test/nnUNetV1/network_training/nnUNetTrainerWCET2.py:6
ClassnnUNetTrainerWCET4
test/nnUNetV1/network_training/nnUNetTrainerWCET4.py:6
ClassnnUNetTrainer_Asym
test/nnUNetV1/network_training/nnUNetTrainer_Asym.py:6
ClassnnUNetTrainer_Dice
test/nnUNetV1/network_training/nnUNetTrainer_Dice.py:6
ClassnnUNetTrainer_DiceBD
test/nnUNetV1/network_training/nnUNetTrainer_DiceBD.py:5
ClassnnUNetTrainer_DiceHD
test/nnUNetV1/network_training/nnUNetTrainer_DiceHD.py:5
ClassnnUNetTrainer_DiceTopK10
test/nnUNetV1/network_training/nnUNetTrainer_DiceTopK10.py:6
ClassnnUNetTrainer_ExpLog
test/nnUNetV1/network_training/nnUNetTrainer_ExpLog.py:6
ClassnnUNetTrainer_ExpLogT0
test/nnUNetV1/network_training/nnUNetTrainer_ExpLogT0.py:6
ClassnnUNetTrainer_ExpLogT1
test/nnUNetV1/network_training/nnUNetTrainer_ExpLogT1.py:6
ClassnnUNetTrainer_ExpLogT2
test/nnUNetV1/network_training/nnUNetTrainer_ExpLogT2.py:6
ClassnnUNetTrainer_ExpLogT4
test/nnUNetV1/network_training/nnUNetTrainer_ExpLogT4.py:6
ClassnnUNetTrainer_Focal
test/nnUNetV1/network_training/nnUNetTrainer_Focal.py:6
ClassnnUNetTrainer_FocalTversky
test/nnUNetV1/network_training/nnUNetTrainer_FocalTversky.py:6
ClassnnUNetTrainer_GDice
test/nnUNetV1/network_training/nnUNetTrainer_GDice.py:7
ClassnnUNetTrainer_HDBinary
test/nnUNetV1/network_training/nnUNetTrainer_HDBinary.py:5
ClassnnUNetTrainer_Iou
test/nnUNetV1/network_training/nnUNetTrainer_Iou.py:6
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