U-Net 2D ValueError when preparing data for training about zerocostdl4mic HOT 1 CLOSED

Hi @shoyip ,

Without the data I can not really tell 100%, but I imagine that what is happening is that one of your masks have all the same values in it. This is making the normalizeMinMax function to return NaN values as np.amax(x) - np.amin(x) of an image with the all the values being the same is zero, then the division between zero returns Nan.

# Simple normalization to min/max for the Mask
def normalizeMinMax(x, dtype=np.float32):
  x = x.astype(dtype,copy=False)
  x = (x - np.amin(x)) / (np.amax(x) - np.amin(x))
  return x

Therefore, to solve it, in 021c2c0 I have added a really small value to avoid divisions between zero and with this NaN values.

# Simple normalization to min/max for the Mask
def normalizeMinMax(x, dtype=np.float32):
  x = x.astype(dtype,copy=False)
  x = (x - np.amin(x)) / (np.amax(x) - np.amin(x) + 1e-10)
  return x

Thank you very much for your issue and helping us to solve this problem.
Please try the new notebook and if the problem persist, fell free to comment it again in the issue.

Iván

from zerocostdl4mic.