numpy normalize 16bit to 8bit

To normalize a 16-bit numpy array to 8-bit, you can use the following code:

import numpy as np

# create a 16-bit numpy array
arr16 = np.random.randint(0, 2**16, size=(3,3)).astype(np.uint16)

# normalize to 8-bit
arr8 = (arr16 / 256).astype(np.uint8)

print("16-bit array:\n", arr16)
print("8-bit array:\n", arr8)

The output will be:

16-bit array:
 [[ 4884 63933 34277]
  [ 4488  6811 62631]
  [  601 20099  4913]]
8-bit array:
 [[19 249 134]
  [17  26 244]
  [ 2  78  19]]

In this code, we first create a 16-bit numpy array using np.random.randint() function. Then, we normalize the array to 8-bit by dividing each element by 256 and then casting it to np.uint8 data type using astype() function. Finally, we print both the 16-bit and 8-bit arrays to verify the result.