import os
import cv2
import numpy as np
import random
if __name__ == '__main__':
dir_a=r'E:\lian'
debug_show=False
mask_paths = ['%s/%s' % (i[0].replace("\\", "/"), j) for i in os.walk(dir_a) for j in i[-1] if j.endswith((f'_mask.jpg', 'jpega', 'JPGa'))]
mask_paths = sorted(mask_paths, key=lambda x: os.path.getmtime(x))
for index, mask_path in enumerate(mask_paths):
img_path=mask_path.replace('_mask.jpg','_img.jpg')
img_o = cv2.imread(img_path)
img=img_o.copy()
mask = cv2.imread(mask_path, cv2.IMREAD_GRAYSCALE)
# 在二值图像中找到白色区域的位置
white_pixels = np.where(mask == 255)
# 计算白色区域的面积
white_area = len(white_pixels[0])
# 确定新区域的面积,小于白色区域的90%
new_area = int(white_area * 0.9)
# 生成随机形状和大小的结
python随机把图像填充最暗颜色
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转载自blog.csdn.net/jacke121/article/details/130893785
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