I am currently working with some python code and one piece of code keeps ruining my day:
print(img.shape) # prints (4, 64, 64, 3)
scaled = np.array(img, copy=True)
test = np.array(img, copy=True) / 255
scaled[:, :, :, :3] = scaled[:, :, :, :3] / 255.0
print(np.all(scaled == test)) # prints false
My problem here is that the slice operation seems to change the value of the operation. As far as I understand it, scaled and test should be the same. Am I just missing something or where exactly lies my error?
>Solution :
numpy is stricter about data types than Python. img is an integer datatype, so scaled is also an integer data type. test is created as a float data type. When you do the in-place division, it does a floating divide, then casts the result back to integer to store it in the array.
If you had printed out the two arrays, this would have been obvious.