segmentation_models_pytorch_example/losses/constants.py

#: Loss binary mode suppose you are solving binary segmentation task.
#: That mean yor have only one class which pixels are labled as **1**,
#: the rest pixels are background and labeled as **0**.
#: Target mask shape - (N, H, W), model output mask shape (N, 1, H, W).
BINARY_MODE: str = "binary"

#: Loss multiclass mode suppose you are solving multi-**class** segmentation task.
#: That mean you have *C = 1..N* classes which have unique label values,
#: classes are mutually exclusive and all pixels are labeled with theese values.
#: Target mask shape - (N, H, W), model output mask shape (N, C, H, W).  
MULTICLASS_MODE: str = "multiclass"

#: Loss multilabel mode suppose you are solving multi-**label** segmentation task.
#: That mean you have *C = 1..N* classes which pixels are labeled as **1**,
#: classes are not mutually exclusive and each class have its own *channel*,
#: pixels in each channel which are not belong to class labeled as **0**.
#: Target mask shape - (N, C, H, W), model output mask shape (N, C, H, W).
MULTILABEL_MODE: str = "multilabel"