prewitt.py

import cv2
import numpy as np
#define the vertical filter
vertical_filter = [[-1,-1,-1], [0,0,0], [1,1,1]]
#define the horizontal filter
horizontal_filter = [[-1,0,1], [-1,0,1], [-1,0,1]]
#read image
img = cv2.imread(r'C:\Users\MOSALAS\Pictures\elephant.jpg')
#get the dimensions of the image
n,m,d = img.shape
#initialize the edges image
edges_img = img.copy()
#loop over all pixels in the image
for row in range(3, n-2):
    for col in range(3, m-2):
        #create little local 3x3 box
        local_pixels = img[row-1:row+2, col-1:col+2, 0]
        #apply the vertical filter
        vertical_transformed_pixels = vertical_filter*local_pixels
        #remap the vertical score
        vertical_score = (vertical_transformed_pixels.sum()+3)/6
        #apply the horizontal filter
        horizontal_transformed_pixels = horizontal_filter*local_pixels
        #remap the horizontal score
        horizontal_score = (horizontal_transformed_pixels.sum()+3)/6
        #combine the horizontal and vertical scores into a total edge score
        edge_score = (vertical_score**2 + horizontal_score**2)**.5
        #insert this edge score into the edges image
        edges_img[row, col] = [edge_score]
cv2.imshow('prewitt',edges_img)
cv2.waitkey(0)