抠像 原图 和 标签合并，查看抠像是否准确

合并后的图，是带有 羽化 效果的

import osimport cv2
import numpy as npdef apply_mask_with_feathering(original_image_path, mask_image_path):# 读取原图和mask图original_image = cv2.imread(original_image_path)mask_image = cv2.imread(mask_image_path, cv2.IMREAD_GRAYSCALE)# 检查两个图像的尺寸是否匹配if original_image.shape[:2] != mask_image.shape[:2]:raise ValueError("The dimensions of the original image and the mask image do not match.")# 创建一个带有标签的图像labeled_image = original_image.copy()# 将mask图归一化到0到1之间mask_float = mask_image.astype(float) / 255.0# 创建标签颜色label_color = np.array([0, 0, 255], dtype=float)  # BGR格式，红色# 将标签颜色应用到原图上，同时保留羽化效果for c in range(3):  # 对每个颜色通道进行处理labeled_image[:, :, c] = labeled_image[:, :, c] * (1 - mask_float) + label_color[c] * mask_floatreturn original_image, labeled_imageif __name__ == '__main__':jpg_path = r'C:\Users\hzy\Desktop\1111\20240517'png_path = r'C:\Users\hzy\Desktop\1111\20240517_syl'output_image_path = r'C:\Users\hzy\Desktop\1111\labeled'for root, dirs, files in os.walk(jpg_path):for file in files:filename, ext = os.path.splitext(file)if ext not in ['.png', '.jpg']:continuejpg = os.path.join(root, file)png = os.path.join(png_path, filename + '.png')# 使用示例original_image, labeled_image = apply_mask_with_feathering(jpg, png)# 显示原图和带标签的图像cv2.imshow(file, original_image)cv2.imshow("Labeled Image", labeled_image)# 等待用户按键按下cv2.waitKey(0)cv2.destroyAllWindows()output_img_path = os.path.join(output_image_path, file)# 保存结果图像cv2.imwrite(output_img_path, labeled_image)

效果：

原图

标签图

合并后的图