Python - Local Normalization in OpenCV -

i trying implement in python same function on post: link

however, can't smooth result, whatever try, though tried both implementation, corrected 1 of op , second answer provided.

i missing small can't figure out what.

def local_norm(img, sigma_1, sigma_2):      float_gray = img * cv2.cv_32fc1 / 255.0     blur_1 = int(2 * np.ceil(- norm.ppf(0.05, loc=0, scale=sigma_1)) + 1)     blurred_1 = cv2.gaussianblur(float_gray, (blur_1, blur_1), sigma_1, sigma_1)     temp_1 = float_gray - blurred_1      temp_2 = cv2.pow(temp_1, 2.0)     blur_2 = int(2 * np.ceil(- norm.ppf(0.05, loc=0, scale=sigma_2)) + 1)     blurred_2 = cv2.gaussianblur(temp_2, (blur_2, blur_2), sigma_2, sigma_2)     temp_2 = cv2.pow(blurred_2, 0.5)      float_gray = temp_1 / temp_2     res = cv2.normalize(float_gray, 0, 255, cv2.norm_minmax)     res = res * cv2.cv_32s     return res 

i must precise @ end, use cv2.cv_32s because op's encoding end black image. rest, use same sigma, 2.0 , 20.0.

there errors in implementation, here correctly translated code in python:

import cv2 import numpy np  img = cv2.imread('lena.png')  gray = cv2.cvtcolor(img, cv2.color_bgr2gray)  float_gray = gray.astype(np.float32) / 255.0  blur = cv2.gaussianblur(float_gray, (0, 0), sigmax=2, sigmay=2) num = float_gray - blur  blur = cv2.gaussianblur(num*num, (0, 0), sigmax=20, sigmay=20) den = cv2.pow(blur, 0.5)  gray = num / den  cv2.normalize(gray, dst=gray, alpha=0.0, beta=1.0, norm_type=cv2.norm_minmax)  cv2.imwrite("./debug.png", gray * 255) 

output: