I think you mean the Shannon entropy, check this out:

import numpy as np

import math

import timeit

from collections import Counter

from scipy.stats import entropy

def get_file_bytes(file_path):

with open(file_path, 'rb') as f:

return bytearray(f.read());

return None;

def entropy_shannon(labels, base=None):

value, counts = np.unique(labels, return_counts=True)

return entropy(counts, base=base)

# Loading target file

file_path = "../data/images/image1.png"

image_byte_list = get_file_bytes(file_path)

print(len(image_byte_list ), 'Bytes')

print(entropy_shannon(image_byte_list ))