Kernal implementaion Exp-7

import numpy as np

import cv2

import matplotlib.pyplot as plt

img = cv2.imread('butterfly.jpg')

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

blur = cv2.GaussianBlur(gray, (5, 5), 0)

# Robert Edge Detection

kernelxx = np.array([[1, 0], [0, -1]])

kernelyy = np.array([[0, 1], [-1, 0]])

img_robertx = cv2.filter2D(img, -1, kernelxx)

img_roberty = cv2.filter2D(img, -1, kernelyy)

grad = cv2.addWeighted(img_robertx, 0.5, img_roberty, 0.5, 0)

plt.imshow(grad,cmap='gray')

plt.title("Robert Edge Detection")

plt.axis('off')

# Laplacian

laplacian = cv2.Laplacian(img,cv2.CV_64F)

sobelx = cv2.Sobel(src=blur, ddepth=cv2.CV_64F, dx=1, dy=0, ksize=3)

sobely = cv2.Sobel(src=blur, ddepth=cv2.CV_64F, dx=0, dy=1, ksize=3)

fig, axs = plt.subplots(2, 2)

titles = ['Original', 'Sobel along X-axis', 'Sobel along Y-axis', 'Laplacian']

axs[0, 0].imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))

axs[0, 0].set_title(titles[0])

axs[0, 0].axis('off')

axs[0, 1].imshow(laplacian, cmap='gray')

axs[0, 1].set_title(titles[3])

axs[0, 1].axis('off')

axs[1, 0].imshow(sobelx, cmap='gray')

axs[1, 0].set_title(titles[1])

axs[1, 0].axis('off')

axs[1, 1].imshow(sobely, cmap='gray')

axs[1, 1].set_title(titles[2])

axs[1, 1].axis('off')