Computer vision: Canny Edge Detection in OpenCV Arabic

Code 1

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import cv2

import numpy as np

from matplotlib import pyplot as plt

img = cv2.imread("lena.jpg")

img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

canny = cv2.Canny(img, 100, 200)

titles = ['image', 'canny']

images = [img, canny]

for i in range(2):

    plt.subplot(1, 2, i+1), plt.imshow(images[i], 'gray')     

    plt.title(titles[i])     

    plt.xticks([]),plt.yticks([])#ticks     

plt.show()#show

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Code 2 

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import cv2

import numpy as np

from matplotlib import pyplot as plt

img = cv2.imread("messi5.jpg", cv2.IMREAD_GRAYSCALE)

lap = cv2.Laplacian(img, cv2.CV_64F, ksize=3)

lap = np.uint8(np.absolute(lap))

sobelX = cv2.Sobel(img, cv2.CV_64F, 1, 0)

sobelY = cv2.Sobel(img, cv2.CV_64F, 0, 1)

edges = cv2.Canny(img,100,200)

sobelX = np.uint8(np.absolute(sobelX))

sobelY = np.uint8(np.absolute(sobelY))

sobelCombined = cv2.bitwise_or(sobelX, sobelY)

titles = ['image', 'Laplacian', 'sobelX', 'sobelY', 'sobelCombined', 'Canny']

images = [img, lap, sobelX, sobelY, sobelCombined, edges]

for i in range(6):

    plt.subplot(2, 3, i+1), plt.imshow(images[i], 'gray')      

    plt.title(titles[i])      

    plt.xticks([]),plt.yticks([])#ticks      

plt.show()#show

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data used in this video

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