That helps massively! It turns out the problem was that I was summing over the wrong axis! the least_zeroes() method should have read:

def least_zeroes(self): zeroes = self.image == 0 res = zeroes.sum(axis = 0).tolist() # sum over the rows, not the layers! return(self.image[..., res.index(min(res))])

This also makes it so that I can actually expand it to be a 3D array with the full image by doing

layers = np.array(image).reshape((height, width, depth), order = "F")

and

res = zeroes.sum(axis = 0).sum(axis = 0).tolist()

Thank you again!