import cv2

img1 = cv2.imread('1.jpg')
img2 = cv2.imread('9.jpg')

dst = cv2.addWeighted(img1, 0.7, img2, 0.3, 0)
# dst = cv2.add(img1,img2)

cv2.imshow('dst', dst)
cv2.waitKey(0)

import cv2

img1 = cv2.imread('1.jpg')
img2 = cv2.imread('9.jpg')

rows, cols, channels = img2.shape
roi = img1[0:rows, 0:cols]

img2gray = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
ret, mask = cv2.threshold(img2gray, 10, 255, cv2.THRESH_BINARY)
mask_inv = cv2.bitwise_not(mask)

# cv2.imshow("mask_inv",mask_inv)

img1_bg = cv2.bitwise_and(roi, roi, mask=mask_inv)
# cv2.imshow("img1_bg",img1_bg)

img2_fg = cv2.bitwise_and(img2, img2, mask=mask)
# cv2.imshow("img2_fg",img2_fg)

dst = cv2.add(img1_bg, img2_fg)
img1[0:rows, 0:cols] = dst

cv2.imshow('res', img1)
cv2.waitKey(0)

import cv2
import numpy as np

A = cv2.imread('3.jpg')
B = cv2.imread('4.jpg')

G = A.copy()
gpA = [G]
for i in range(6):
    G = cv2.pyrDown(G)
    gpA.append(G)

G = B.copy()
gpB = [G]
for i in range(6):
    G = cv2.pyrDown(G)
    gpB.append(G)

# generate Laplacian Pyramid for A
lpA = [gpA[5]]
for i in range(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 range(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 range(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.imshow('Pyramid_blending.jpg', ls_)
cv2.imshow('Direct_blending.jpg', real)

cv2.waitKey(0)