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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 os

import cv2
import numpy as np

def 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_float

    return original_image, labeled_image



if __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']:
                continue
            jpg = 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