def define_criterion(self, name):
     if name.lower() == 'bce+dice':
         self.criterion = Loss.BCE_Dice()
     elif name.lower() == 'dice':
         self.criterion = Loss.DiceLoss()
     elif name.lower() == 'bce':
         self.criterion = nn.BCEWithLogitsLoss()
     elif name.lower() == 'robustfocal':
         self.criterion = Loss.RobustFocalLoss2d()
     elif name.lower() == 'lovasz-hinge' or name.lower() == 'lovasz':
         self.criterion = Loss.Lovasz_Hinge(per_image=True)
     elif name.lower() == 'bce+lovasz':
         self.criterion = Loss.BCE_Lovasz(per_image=True)
     else:
         raise NotImplementedError(
             'Loss {} is not implemented'.format(name))
Example #2
0
 def define_criterion(self, name):
     if name.lower() == 'bce+dice':
         self.criterion = Loss.BCE_Dice()
     elif name.lower() == 'dice':
         self.criterion = Loss.DiceLoss()
     elif name.lower() == 'bce':
         # self.criterion = nn.BCEWithLogitsLoss()
         # self.criterion = nn.CrossEntropyLoss(size_average=False, reduction='sum')
         self.criterion = nn.CrossEntropyLoss()
         # self.criterion = Loss.CE_SOFT()
     elif name.lower() == 'robustfocal':
         self.criterion = Loss.RobustFocalLoss2d()
     elif name.lower() == 'lovasz-hinge' or name.lower() == 'lovasz':
         self.criterion = Loss.Lovasz_Hinge(per_image=True)
     elif name.lower() == 'bce+lovasz':
         self.criterion = Loss.BCE_Lovasz(per_image=True)
     else:
         raise NotImplementedError(
             'Loss {} is not implemented'.format(name))