"""
# @Time  : 2020/4/3
# @Author : JMChen
"""
import cv2 as cv

img1 = cv.imread('logo.png')
img2 = cv.imread('lena.png')
# 在lena.png获取和logo.png大小相同的ROI
rows, cols, channels = img1.shape
img_ROI1 = img2[0:rows, 0:cols]

img_ROI2 = cv.addWeighted(img1, 0.7, img_ROI1, 0.3, 0)
img2[0:rows, 0:cols] = img_ROI2

# 显示混合后的图片
cv.imshow('img2', img2)
cv.waitKey(0)

# 将两幅图像（lena.png）+ (logo.png)进行融合
img2 = cv.imread('lena.png')
# 1，在lena.png获取和logo.png大小相同的ROI
img_ROI1 = img2[0:rows, 0:cols]

# 2，基于logo.png的灰度图，利用简单的阈值分割创建一个掩模
img1_gray = cv.cvtColor(img1, cv.COLOR_BGR2GRAY)
ret, mask = cv.threshold(img1_gray, 10, 255, cv.THRESH_BINARY)
mask_inv = cv.bitwise_not(mask)

# 3，与掩模进行按位与操作，去掉logo中非0部分，得到新的图
new_img2 = cv.bitwise_and(img_ROI1, img_ROI1, mask=mask_inv)

# 4，将新图与logo相加，然后将这一部分替换掉原始图像的img_ROI1部分
dst = cv.add(img1, new_img2)
img2[0:rows, 0:cols] = dst

cv.imshow('res', img2)
cv.waitKey(0)
cv.destroyAllWindows()

# 实现另一种融合
img2 = cv.imread('lena.png')
img_ROI1 = img2[0:rows, 0:cols]

dst_1 = cv.addWeighted(img_ROI1, 0.55, dst, 0.45, 0)
img2[0:rows, 0:cols] = dst_1

cv.imshow('res_2', img2)
cv.waitKey(0)
cv.destroyAllWindows()