I was able to solve this issue by changing the Reshape args for last layers of the model.
Instead of the current model definition in unet.py (notice the input_shape arg for the Keras Reshape):
reshape = Reshape((self.img_rows * self.img_cols, 12), input_shape=(self.img_rows, self.img_cols, 12))(conv9)
print("reshape shape:", reshape.shape)
# permute = Permute((2, 1))(reshape)
# print("permute shape:", permute.shape)
activation = Activation('softmax')(reshape)
After 10 epochs I got this result:
Originally posted by @shabtayor in #1 (comment)
I was able to solve this issue by changing the Reshape args for last layers of the model.
Instead of the current model definition in unet.py (notice the input_shape arg for the Keras Reshape):
After 10 epochs I got this result:
Originally posted by @shabtayor in #1 (comment)