Computer Vision Course: Image Blending using Pyramids in open CV 

import cv2

import numpy as np

apple = cv2.imread('apple.jpg')

orange = cv2.imread('orange.jpg')

print(apple.shape)

print(orange.shape)

apple_orange = np.hstack((apple[:, :256], orange[:, 256:]))

# generate Gaussian pyramid for apple

apple_copy = apple.copy()

gp_apple = [apple_copy]

for i in range(6):

    apple_copy = cv2.pyrDown(apple_copy)       

    gp_apple.append(apple_copy)       

# generate Gaussian pyramid for orange

orange_copy = orange.copy()

gp_orange = [orange_copy]

for i in range(6):

    orange_copy = cv2.pyrDown(orange_copy)      

    gp_orange.append(orange_copy)      

# generate Laplacian Pyramid for apple

apple_copy = gp_apple[5]

lp_apple = [apple_copy]

for i in range(5, 0, -1):

    gaussian_expanded = cv2.pyrUp(gp_apple[i])      

    laplacian = cv2.subtract(gp_apple[i-1], gaussian_expanded)      

    lp_apple.append(laplacian)      

# generate Laplacian Pyramid for orange

orange_copy = gp_orange[5]

lp_orange = [orange_copy]

for i in range(5, 0, -1):

    gaussian_expanded = cv2.pyrUp(gp_orange[i])      

    laplacian = cv2.subtract(gp_orange[i-1], gaussian_expanded)      

    lp_orange.append(laplacian)      

# Now add left and right halves of images in each level

apple_orange_pyramid = []

n = 0

for apple_lap, orange_lap in zip(lp_apple, lp_orange):

    n += 1      

    cols, rows, ch = apple_lap.shape     

    laplacian = np.hstack((apple_lap[:, 0:int(cols/2)], orange_lap[:, int(cols/2):]))     

    apple_orange_pyramid.append(laplacian)     

# now reconstruct

apple_orange_reconstruct = apple_orange_pyramid[0]

for i in range(1, 6):

    apple_orange_reconstruct = cv2.pyrUp(apple_orange_reconstruct)       

    apple_orange_reconstruct = cv2.add(apple_orange_pyramid[i], apple_orange_reconstruct)       

cv2.imshow("apple", apple)

cv2.imshow("orange", orange)

cv2.imshow("apple_orange", apple_orange)

cv2.imshow("apple_orange_reconstruct", apple_orange_reconstruct)

cv2.waitKey(0)

cv2.destroyAllWindows()#close window

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data used in this video

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