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import cv2

import numpy as np

# 读取原图和水印蒙版

src = cv2.imread('image_with_watermark.jpg')

mask = cv2.imread('watermark_mask.png', cv2.IMREAD_GRAYSCALE)

# 执行图像修复

dst = cv2.inpaint(src, mask, 3, cv2.INPAINT_TELEA)

# 显示结果

cv2.imshow('Original Image', src)

cv2.imshow('Watermark Mask', mask)

cv2.imshow('Restored Image', dst)

cv2.waitKey(0)

cv2.destroyAllWindows()

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import cv2

import numpy as np

img = cv2.imread('image_with_watermark.jpg')

h, w, l = img.shape

for j in range(h):

    for k in range(w):

        # 删除浅灰色水印

        if (img[j][k][0] > 240 and img[j][k][1] > 240 and img[j][k][2] > 240):

            img[j][k] = [255, 255, 255]  # 设置为白色

cv2.imshow("Image Without Watermark", img)

cv2.waitKey(0)

cv2.destroyAllWindows()

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import cv2

import numpy as np

src = cv2.imread('image_with_watermark.jpg')

mask = cv2.imread('white_background_watermark.png')

save = np.zeros(src.shape, np.uint8)  # 创建一张空图像用于保存

for row in range(src.shape[0]):

    for col in range(src.shape[1]):

        for channel in range(src.shape[2]):

            if mask[row, col, channel] != 0:

                reverse_val = 255 - src[row, col, channel]

                val = 255 - int(reverse_val * 256 / mask[row, col, channel])

                if val < 0:

                    val = 0

                save[row, col, channel] = val

cv2.imshow('Restored Image', save)

cv2.waitKey(0)

cv2.destroyAllWindows()