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python-3.x - 如何删除图像的某个部分？

问题描述

我有一张图片： 原始图片

我想删除图像的灰色网格部分而不影响图像的其余部分，即黑色圆圈内的部分。我为此写了一个代码

import cv2
import numpy as np
from PIL import Image
imag = Image.open('results.jpg')
imag.show()

pixelMap = imag.load()

img = Image.new( imag.mode, imag.size)
pixelsNew = img.load()

for i in range(img.size[0]):
    for j in range(img.size[1]):        
        if (( pixelMap[i,j]> (200,0,0)) and (pixelMap[i,j]< (240,0,0))):
            pixelsNew[i,j] = (255,255,255)
        else:
            pixelsNew[i,j] = pixelMap[i,j]
img.show()

使用此代码，我得到以下输出图像： 输出图像

但是，黑色圆圈内的一些像素也变成了白色，这不是我想要的。我想知道如何解决这个问题。

标签： python-3.ximage-processingpython-imaging-libraryrgb

解决方案

您可以找到黑色圆圈的索引并将值分配给黑色圆圈左侧或右侧的像素。下面是这个的示例代码

import cv2
import numpy as np

# read the image
img = cv2.imread('original.png')
cv2.imshow("Image", img)

# convert image to numpy array and also to grayscale
img = np.array(img)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# get height and width of image
[rows, cols] = gray.shape

# now extract one row from image, find indices of black circle
# and make those pixels white which are to the left/right
# of black cirlce
for i in range(rows):
    row = gray[i, :] # extract row of image
    indices = np.where(row == 0)    # find indices of black circle
    indices = indices[0]

    # if indices are not empty
    if len(indices) > 0:
        # find starting/ending column index
        si = indices[0]
        ei = indices[len(indices)-1]

        # assign values to the range of pixels
        img[i, 0:si-1] = [255, 255, 255]
        img[i, ei+1:] = [255, 255, 255]
    # if indices is empty then make whole row white
    else:
        img[i,:] = [255, 255, 255]

cv2.imshow("Modified Image", img)
cv2.waitKey(0)
cv2.destroyAllWindows()

输入图像

输入图像

输出图像

输出图像

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