Edge Dedection Exp-6

import cv2

import matplotlib.pyplot as plt

import numpy as np

# Canny

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

# converting the image to grayscale

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

blur = cv2.GaussianBlur(gray, (5, 5), 0) # the second parm is the size of the kernel

# wider the threshold range, more the edges

canny = cv2.Canny(img, threshold1=180, threshold2=200)

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

titles = ['Original', 'Grayscale', 'Gaussian Blur', 'Canny']

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(cv2.cvtColor(gray, None))

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

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

axs[1, 0].imshow(cv2.cvtColor(blur, None))

axs[1, 0].set_title(titles[2])

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

axs[1, 1].imshow(cv2.cvtColor(canny, None))

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

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

# Sobel

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

axis

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

axis

sobelxy = cv2.Sobel(src=blur, ddepth=cv2.CV_64F, dx=1, dy=1, ksize=3) # Combined X & Y

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

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

and Y axis']

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(sobelxy, 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')

# Prewitt

# Defining the kernels

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

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

# Applying convolution

img_prewittx = cv2.filter2D(blur, -1, kernelx)

img_prewitty = cv2.filter2D(blur, -1, kernely)

img_prewitt = img_prewittx + img_prewitty

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

titles = ['Original', 'Kernel X', 'Kernel Y', 'Kernel X and Y']

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(img_prewitt, cmap='gray')

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

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

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

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

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

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

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

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