python opencv去除简易水印——去除红色效果最好

短命女 2022-10-16 07:47 547阅读 0赞

去水印是个麻烦事，水印的方式千奇百怪，下面的方法并不一定适用你。

# opencv去图片中红色部分，保留其他 #

这个方式需要你的图像水印比较简单，且为纯色的红色。

## 效果图 ##

原图  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hb19odWlfZmVp_size_16_color_FFFFFF_t_70]  
处理结果图  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hb19odWlfZmVp_size_16_color_FFFFFF_t_70 1]

## 代码 ##

import cv2
    import numpy as np
    
    imgs = cv2.imread("4.jpg")
    image = imgs.copy()
    images = imgs.copy()
    print(image.shape)
    rows, cols = image.shape[:2]
    print(rows, cols)
    red_minus_blue = image[:, :, 2] - image[:, :, 0]
    red_minus_green = image[:, :, 2] - image[:, :, 1]
    
    red_minus_blue = red_minus_blue >= 20
    red_minus_green = red_minus_green >= 20
    
    red = image[:, :, 2] >= np.mean(image[:, :, 2]) / 2
    
    mask = red_minus_green & red_minus_blue & red
    print(mask)
    images[mask, :] = 255
    mask = (1 - mask).astype(np.bool)
    print(mask)
    image[mask, :] = 255
    
    stack = np.vstack([imgs, image, images])
    cv2.imshow("stack", stack)
    cv2.imwrite("result.jpg", stack)
    cv2.imshow("orgin", imgs)
    cv2.imshow("red", image)
    
    cv2.imshow("delete_red", images)
    cv2.imwrite("delete_red.jpg", images)
    
    cv2.waitKey()
    
    # 红色像素值最大，且大于阈值（中值）
    # 其他通道像素值的距离比较小，且与红色像素值的距离比率较大，且大于阈值（自己调）。

# 代码2 #

## 效果图 ##

原图如上，效果图如下，可以看到虽然把红色水印去了，但是图像变成了灰度图。  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hb19odWlfZmVp_size_16_color_FFFFFF_t_70 2]

import numpy as np
    import cv2 as cv
    
    im = cv.imread('4.jpg')
    
    image = im.copy()
    # print(imgs)
    cv.namedWindow("image", cv.WINDOW_NORMAL)
    cv.imshow('image',image[:, :, 2])
    cv.imwrite("image.jpg", image[:, :, 2])
    cv.waitKey(0)==ord('q')

# 代码3 #

这个虽然也能去除水印，但是图像其他较深的地方也被去除

## 效果图 ##

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L21hb19odWlfZmVp_size_16_color_FFFFFF_t_70 3]

## 源码 ##

import cv2
    import numpy as np
    
    if __name__ =='__main__':
        img_path = "4.jpg"
        im = cv2.imread(img_path)
    
        gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
    
        background = gray.copy()
        for i in range(1,5):
            kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(2*i+1,2*i+1))
            #kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (1 * 4 + 1,1 * 4 + 1))
            print('kernel size is ',kernel)
            background = cv2.morphologyEx(background,cv2.MORPH_CLOSE,kernel)
            background = cv2.morphologyEx(background,cv2.MORPH_CLOSE,kernel)
    
        diff = background - gray # 计算差距
        print('diff size is ', diff)
        cv2.namedWindow('diff',cv2.WINDOW_FREERATIO) # 获取图像中前景背景之差
        cv2.imshow('diff',background)
        # 阈值分割获取黑色字体
        _,bw = cv2.threshold(diff,0,255,cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)
        # 阈值分割获取黑色区域
        cv2.namedWindow('bw_before', cv2.WINDOW_FREERATIO)
        cv2.imshow('bw_before', bw)
    
    
        _,dark = cv2.threshold(background,0,255,cv2.THRESH_BINARY_INV|cv2.THRESH_OTSU)
    
        darkpix = cv2.countNonZero(dark)# 获取 dark非0d图像像素个数
        darkpix = [0]*darkpix
        index = 0
        cv2.namedWindow('gray', cv2.WINDOW_FREERATIO)
        cv2.imshow('gray', gray)
    
    
    
        for r in range(dark.shape[0]):
            for c in range(dark.shape[1]):
                if(dark[r][c]):
                    darkpix[index]  = gray[r][c]
                    index = index +1
    
        # 阈值分割 dark 区域 因此我们在里面得到更深的像素
        darkpix = np.array(darkpix)
        _,darkpix = cv2.threshold(darkpix,0,255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)
    
        cv2.namedWindow('darkpix', cv2.WINDOW_FREERATIO)
        cv2.imshow('darkpix', darkpix)
    
        # 把 取到的像素粘贴到 其渠道的 darker pixels
    
        cv2.namedWindow('dark',cv2.WINDOW_FREERATIO)
        cv2.imshow('dark',dark)
    
        index = 0
        for r in range(dark.shape[0]):
            for c in range(dark.shape[1]):
                if (dark[r][c]):
                    bw[r][c] =  darkpix[index]
                    index = index +1
    
        cv2.namedWindow('bw',cv2.WINDOW_FREERATIO)
        cv2.imshow('bw',bw)
        cv2.waitKey(0

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