python+cv2实现图片加水印

网上好多都是直接用写txt的方式实现的&＃xff0c;其实实际中美工会提供水印图片&＃xff0c;让添加进去。用cv2读取水印图片的时候&＃xff0c;后面的参数设置为-1即可读出透明度通道&＃xff0c;然后在原图的指定位置将水印图片和原图像的像素进行融合即可。

import cv2
import numpy as npdef watermark(src_path, mask_path, alpha &＃61; 0.3):img &＃61; cv2.imread(src_path)h,w &＃61; img.shape[0], img.shape[1]mask &＃61; cv2.imread(mask_path, -1)if w > h:rate &＃61; int(w * 0.1) / mask.shape[1]else:rate &＃61; int(h * 0.1) / mask.shape[0]mask &＃61; cv2.resize(mask, None, fx&＃61;rate, fy&＃61;rate)mask_h, mask_w &＃61; mask.shape[0], mask.shape[1]mask_channels &＃61; cv2.split(mask)dst_channels &＃61; cv2.split(img)b, g, r, a &＃61; cv2.split(mask)# 计算mask在图片的坐标ul_points &＃61; (int(h * 0.9), int(int(w/2) - mask_w / 2))dr_points &＃61; (int(h * 0.9) &＃43; mask_h, int(int(w/2) &＃43; mask_w / 2))for i in range(3):dst_channels[i][ul_points[0] : dr_points[0], ul_points[1] : dr_points[1]] &＃61; dst_channels[i][ul_points[0] : dr_points[0], ul_points[1] : dr_points[1]] * (255.0 - a * alpha) / 255dst_channels[i][ul_points[0]: dr_points[0], ul_points[1]: dr_points[1]] &＃43;&＃61; np.array(mask_channels[i] * (a * alpha / 255), dtype&＃61;np.uint8)dst_img &＃61; cv2.merge(dst_channels)# cv2.imwrite(r&＃39;d:\1_1.jpg&＃39;, dst_img)return dst_img


原图
水印图&＃xff1a;

合成之后的图&＃xff0c;分别选择alpha&＃61;1 和 alpha&＃61;0.3