Open hydxqing opened 5 years ago
Because the denominator may be 0 in the calculate of iou and dice, you can replace the np.mean() with np.nanmean().
I am also have a problem with the loss_G and loss_D, actually, I changed the symbol of the loss_D, but the results do not seem to differ. Is anyone could explain it?
This shouldn't be happening, maybe you can try to train with the adversarial loss alone (i.e., w/o the dice loss, which was put there to help stabilize the adversarial training). In that case, changing the symbol should just make the whole training fail.
Why do my output loss_G and loss_D are opposite to each other? In your code, loss_G and loss_D are just symbols different. And after this training is completed, the predictions are all nan. Why is this so? I really hope to hear from you.