how to make the network work well with num_class=2

[rachel]

Hi, originally it work well with num_class=256...

but when I edited img = img.astype('float32') / 255.0, seg = seg.astype('float32') / 255.0 in segmentation_dataset.py, and target = target//255 in trainer.py to adapt the train to num_class=2only(for binary seg),

then the network can not train well and predict nothing (black), did I do something wrong?

you are so kind and sorry to bother you again...