Keras, binary segmentation, add weight to loss function

Question

I\'m solving a binary segmentation problem with Keras (w. tf backend). How can I add more weight to the center of each area of mask?

I\'ve tried dice coef with adde

Answer 1

I'm implementing this solution but I wonder what should be the ground truth that we must give to the network. That is, now the output is the loss, and we want the loss to be 0, so should we train the network as follows?

model = get_unet_w_lambda_loss()
model.fit([inputs, weights, masks], zero_images)