import cv2 as cv
import numpy as np

img = np.array([[5,7,9,11,13,15,17,19,21,23],
                [9,11,13,15,17,19,21,23,25,27], 
                [18,20,22,24,26,28,30,32,34,36], 
                [34,36,38,40,42,44,46,48,50,52], 
                [59,61,63,65,67,69,71,73,75,77], 
                [95,97,99,101,103,105,107,109,111,113], 
                [144,146,148,150,152,154,156,158,160,162], 
                [208,210,212,214,216,218,220,222,224,226], 
                [59,61,63,65,67,69,71,73,75,77], 
                [9,11,13,15,17,19,21,23,25,27]]) 
sigmax = 0.56
kernelSizex = 3
kernelSizey = 3 
sigmay = 0.56
print("GaussianBlur test with SigmaX: ", sigmax)
print("Src Image: ", img)
dst = cv.GaussianBlur(np.uint8(img), (kernelSizex,kernelSizey), sigmax, sigmaY=sigmay, borderType = cv.BORDER_REPLICATE)
print("Dst Image (sigmaY = %f): " % sigmay, dst)
sigmay = 0.36
dst = cv.GaussianBlur(np.uint8(img), (kernelSizex,kernelSizey), sigmax, sigmaY=sigmay, borderType = cv.BORDER_REPLICATE)
print("Dst Image (sigmaY = %f): " % sigmay, dst)
sigmay = 0.76
dst = cv.GaussianBlur(np.uint8(img), (kernelSizex,kernelSizey), sigmax, sigmaY=sigmay, borderType = cv.BORDER_REPLICATE)
print("Dst Image (sigmaY = %f): " % sigmay, dst)