# -*- coding: utf-8 -*- import cv2 import numpy as np def add_alpha_channel(img): """ 为jpg图像添加alpha通道 """ b_channel, g_channel, r_channel = cv2.split(img) # 剥离jpg图像通道 alpha_channel = np.ones(b_channel.shape, dtype=b_channel.dtype) * 255 # 创建Alpha通道 img_new = cv2.merge((b_channel, g_channel, r_channel, alpha_channel)) # 融合通道 return img_new def merge_img(jpg_img, png_img, y1, y2, x1, x2): """ 将png透明图像与jpg图像叠加 y1,y2,x1,x2为叠加位置坐标值 """ # 判断jpg图像是否已经为4通道 if jpg_img.shape[2] == 3: jpg_img = add_alpha_channel(jpg_img) ''' 当叠加图像时，可能因为叠加位置设置不当，导致png图像的边界超过背景jpg图像，而程序报错 这里设定一系列叠加位置的限制，可以满足png图像超出jpg图像范围时，依然可以正常叠加 ''' yy1 = 0 yy2 = png_img.shape[0] xx1 = 0 xx2 = png_img.shape[1] # if x1 < 0: # xx1 = -x1 # x1 = 0 # if y1 < 0: # yy1 = - y1 # y1 = 0 # if x2 > jpg_img.shape[1]: # xx2 = png_img.shape[1] - (x2 - jpg_img.shape[1]) # x2 = jpg_img.shape[1] # if y2 > jpg_img.shape[0]: # yy2 = png_img.shape[0] - (y2 - jpg_img.shape[0]) # y2 = jpg_img.shape[0] # 获取要覆盖图像的alpha值，将像素值除以255，使值保持在0-1之间 alpha_png = png_img[yy1:yy2, xx1:xx2, 3] / 255.0 alpha_jpg = 1 - alpha_png # 开始叠加 for c in range(0, 3): jpg_img[y1:y2, x1:x2, c] = ((alpha_jpg * jpg_img[y1:y2, x1:x2, c]) + (alpha_png * png_img[yy1:yy2, xx1:xx2, c])) return jpg_img if __name__ == '__main__': # 定义图像路径 img_jpg_path = 'img/3.jpg' # 读者可自行修改文件路径 img_png_path = 'img/3.png' # 读者可自行修改文件路径 # 读取图像 img_jpg = cv2.imread(img_jpg_path, cv2.IMREAD_UNCHANGED) img_png = cv2.imread(img_png_path, cv2.IMREAD_UNCHANGED) # 设置叠加位置坐标 x1 = 0 y1 = 0 x2 = x1 + img_png.shape[1] y2 = y1 + img_png.shape[0] # 开始叠加 res_img = merge_img(img_jpg, img_png, y1, y2, x1, x2) # 显示结果图像 # cv2.imshow('result', res_img) # 保存结果图像，读者可自行修改文件路径 cv2.imwrite('img/res.jpg', res_img) # 定义程序退出方式：鼠标点击显示图像的窗口后，按ESC键即可退出程序 if cv2.waitKey(0) & 0xFF == 27: cv2.destroyAllWindows()