在 OpenCV python 中将白色像素转换为黑色 [英] Convert White Pixels to Black in OpenCV python

问题描述

我正在尝试使用 python OpenCV 将输入图像的白色背景转换为黑色.但所有白色像素并未完全转换为黑色.我附上了输入和输出图像.

输入图像:

输出图像:

我使用了以下代码进行转换:

img[np.where((img==[255,255,255]).all(axis=2))] = [0,0,0];

我该怎么办?

解决方案

我知道这已经得到了回答.我有一个编码的 python 解决方案给你.

首先我发现了

另一个测试图像:

编辑这是一种更好、更短的方法.在@ZdaR 评论循环遍历图像矩阵后，我查看了它.

[更新代码]

img = cv2.imread("图片/test.pnt")灰色 = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)ret, thresh = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)img[thresh == 255] = 0内核 = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))侵蚀= cv2.erode(img，内核，迭代= 1)cv2.namedWindow('图像', cv2.WINDOW_NORMAL)cv2.imshow(图像"，侵蚀)cv2.waitKey(0)cv2.destroyAllWindows()

来源

[旧代码]

img = cv2.imread("Images/test.png")灰色 = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)ret, thresh = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)white_px = np.asarray([255, 255, 255])black_px = np.asarray([0, 0, 0])(row, col) = thresh.shapeimg_array = np.array(img)对于范围(行)中的 r:对于范围(col)中的c:像素 = 阈值 [r][c]如果全部(px == white_px):img_array[r][c] = black_px内核 = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))侵蚀= cv2.erode(img_array，内核，迭代= 1)cv2.namedWindow('图像', cv2.WINDOW_NORMAL)cv2.imshow(图像"，侵蚀)cv2.waitKey(0)cv2.destroyAllWindows()

使用的其他来源:OpenCV 形态变换

I am trying to convert the white background of the input image into black using python OpenCV.But all the white pixels are not completely getting converted to black. I have attached the input and output images.

Input Image :

Output Image:

I have used the following code for conversion:

img[np.where((img==[255,255,255]).all(axis=2))] = [0,0,0];

What should I do?

解决方案

I know this has already been answered. I have a coded python solution for you.

Firstly I found this thread explaining how to remove white pixels.

The Result:

Another Test img:

Edit This is a way better and shorter method. I looked into it after @ZdaR commented on looping over an images matrix.

[Updated Code]

img = cv2.imread("Images/test.pnt")

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

ret, thresh = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)

img[thresh == 255] = 0

kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
erosion = cv2.erode(img, kernel, iterations = 1)

cv2.namedWindow('image', cv2.WINDOW_NORMAL)
cv2.imshow("image", erosion)
cv2.waitKey(0)
cv2.destroyAllWindows()

Source

[Old Code]

img = cv2.imread("Images/test.png")

gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

ret, thresh = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)

white_px = np.asarray([255, 255, 255])
black_px = np.asarray([0, 0, 0])

(row, col) = thresh.shape
img_array = np.array(img)

for r in range(row):
    for c in range(col):
        px = thresh[r][c]
        if all(px == white_px):
            img_array[r][c] = black_px

kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
erosion = cv2.erode(img_array, kernel, iterations = 1)

cv2.namedWindow('image', cv2.WINDOW_NORMAL)
cv2.imshow("image", erosion)
cv2.waitKey(0)
cv2.destroyAllWindows()

Other Sources used: OpenCV Morphological Transformations

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