image_blending_using_pyramids_opencv.py

import cv2
import numpy as np

apple = cv2.imread('test_images/apple.jpg')
orange = cv2.imread('test_images/orange.jpg')

# print(apple.shape)
# print(orange.shape)

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



# Gaussian pyramid for apple image
apple_copy = apple.copy()

gp_apple = [apple_copy]

for i in range(6):
    apple_copy = cv2.pyrDown(apple_copy)
    gp_apple.append(apple_copy)

# Gaussian pyramid for Orange image
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_extended = cv2.pyrUp(gp_apple[i])
    laplacian = cv2.subtract(gp_apple[i-1],gaussian_extended)
    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_extended = cv2.pyrUp(gp_orange[i])
    laplacian = cv2.subtract(gp_orange[i-1],gaussian_extended)
    lp_orange.append(laplacian)





# Now add left and right halvas of images in each level.
apple_orange_pyramid = []
n = 0
for apple_lap , orange_lap in zip(lp_apple, lp_orange):
    n += 1
    rows , cols , ch = apple_lap.shape
    laplacian = np.hstack((apple_lap[: , 0:int(cols/2)] ,orange_lap[: , int(cols/2):]))
    apple_orange_pyramid.append(laplacian)





# Now Reconsturct the image
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_reconstruct',apple_orange_reconstruct)

cv2.waitKey(0)
cv2.destroyAllWindows()