pyr.tar.gz_For You I Will_blending_pyramid

import cv2 import numpy as np,sys A = cv2.imread('f1.jpg') B = cv2.imread('f2.jpg') cv2.imshow('A',A) cv2.imshow('B',B) cv2.waitKey() cv2.destroyAllWindows() # generate Gaussian pyramid for A G = A.copy() gpA = [G] for i in xrange(5): G = cv2.pyrDown(G) gpA.append(G) # generate Gaussian pyramid for B G = B.copy() gpB = [G] for i in xrange(5): G = cv2.pyrDown(G) gpB.append(G) # generate Laplacian Pyramid for A lpA = [gpA[5]] for i in xrange(5,0,-1): GE = cv2.pyrUp(gpA[i]) L = cv2.subtract(gpA[i-1],GE) lpA.append(L) # generate Laplacian Pyramid for B lpB = [gpB[5]] for i in xrange(5,0,-1): GE = cv2.pyrUp(gpB[i]) L = cv2.subtract(gpB[i-1],GE) lpB.append(L) # Now add left and right halves of images in each level LS = [] for la,lb in zip(lpA,lpB): rows,cols,dpt = la.shape ls = np.hstack((la[:,0:cols/2], lb[:,cols/2:])) LS.append(ls) # now reconstruct ls_ = LS[0] for i in xrange(1,6): ls_ = cv2.pyrUp(ls_) ls_ = cv2.add(ls_, LS[i]) # image with direct connecting each half real = np.hstack((A[:,:cols/2],B[:,cols/2:])) cv2.imwrite('Pyramid_blending2.jpg',ls_) cv2.imwrite('Direct_blending.jpg',real) #Working Of the Algorithm # 1.Load the two images # 2.Find the Gaussian Pyramids for images (in this particular example, number of levels is 5) # 3.From Gaussian Pyramids, find their Laplacian Pyramids # 4.Now join the left half of apple and right half of image in each levels of Laplacian Pyramids # 5.Finally from this joint image pyramids, reconstruct the original image.