blocks|key|1454292|text|请张贴您输入图像的无损版本。丢失的图像修改像素的值，创建影响处理的工件。我重新创建了您的图像，并将其保存为无损PNF文件。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1454293|我正在使用OpenCV来获得您想要的结果。我用原始输入的非零元素创建了一个掩码。然后，我用洪水填筑来填充你想要的颜色。如果两个图像都是AND，则可以获得最终图像。|style|CODE|1454294|让我们看看代码：|1454295|#+import+opencv:
import+cv2

#+image+path
path+=+"D://opencvImages//"
fileName+=+"rectsLossless.png"

#+Reading+an+image+in+default+mode:
inputImage+=+cv2.imread(path+%2B+fileName)

#+Grayscale+image:
grayscaleImage+=+cv2.cvtColor(inputImage,+cv2.COLOR_BGR2GRAY)

#+Get+non-zero+mask:
binaryThresh+=+1
_,+binaryMask+=+cv2.threshold(grayscaleImage,+binaryThresh,+255,+cv2.THRESH_BINARY)|code-block|syntax|javascript|1454296|此位创建非零像素掩码：|1454297|📷|atomic|1454298|这将有助于使所有非白色元素为零。那张照片是面具的第一部分。现在，让我们用红色填充外部形状。这分三个步骤实现：|1454299|#+Get+image+dimensions:
(imageHeight,+imageWidth)+=+inputImage.shape[:2]

#+Get+image+center:
xCenter+=+int(0.5+*+imageWidth)
yCenter+=+int(0.5+*+imageHeight)

#+Get+flood-fill+target+color
floodColor+=+inputImage[yCenter,+xCenter]
print("Flood+Color:+%25s"+%25+floodColor)
#+numpy+array+to+tuple
floodColor+=+(int(floodColor[0]),+int(floodColor[1]),+int(floodColor[2]))|1454300|第一步得到实际的填充颜色。我认为红色或多或少位于图像的中心。然后，第二步是用白色填充所有“前景”像素。让我们在左上角播种：|1454301|#+Flood+fill+at+top+left+corner:
leftCorner+=+(1,+1)
whiteColor+=+(255,+255,+255)
cv2.floodFill(inputImage,+None,+leftCorner,+whiteColor)|1454302|其结果是：|1454303|1454304|注意，部分位于红色矩形之外的形状现在都是用白色连接起来的。让我们再填一次，但这次使用我之前提取的红色：|1454305|#+Second+Flood-fill
cv2.floodFill(inputImage,+None,+leftCorner,+floodColor)|1454306|这将产生以下图像：|1454307|1454308|让我们通过使用原始非零掩码对此结果进行AND来创建最终图像：|1454309|#+Create+final+image:
outImage+=+cv2.bitwise_and(inputImage,+inputImage,+mask=binaryMask)|1454310|这是最后的结果：|1454311|1454312|entityMap|0|LINK|mutability|MUTABLE|url|https://i.imgur.com/DoznLz6.png|1|https://www.programmersought.com/article/38404456179/|2|IMAGE|IMMUTABLE|imageUrl|https://developer.qcloudimg.com/http-save/yehe-900000/e528998a64f44d2d53e55758246875da.png|imageAlt|3|https://developer.qcloudimg.com/http-save/yehe-900000/1ece79d1632da3916eba1ee2ea104de3.png|4|https://developer.qcloudimg.com/http-save/yehe-900000/c6097830c4621d32c939521e4ba07b14.png|5|https://developer.qcloudimg.com/http-save/yehe-900000/74e9b56f30d337b3a01c4c33d78440d2.png^0|1H|7|0|0|1V|3|19|4|1|0|0|0|0|0|1|2|0|0|0|0|0|0|0|1|3|0|0|0|0|0|1|4|0|J|3|0|0|0|0|1|5|0^^$0|@$1|2|3|4|5|6|7|24|8|@]|9|@$A|25|B|26|1|27]]|C|$]]|$1|D|3|E|5|6|7|28|8|@$A|29|B|2A|F|G]]|9|@$A|2B|B|2C|1|2D]]|C|$]]|$1|H|3|I|5|6|7|2E|8|@]|9|@]|C|$]]|$1|J|3|K|5|L|7|2F|8|@]|9|@]|C|$M|N]]|$1|O|3|P|5|6|7|2G|8|@]|9|@]|C|$]]|$1|Q|3|R|5|S|7|2H|8|@]|9|@$A|2I|B|2J|1|2K]]|C|$]]|$1|T|3|U|5|6|7|2L|8|@]|9|@]|C|$]]|$1|V|3|W|5|L|7|2M|8|@]|9|@]|C|$M|N]]|$1|X|3|Y|5|6|7|2N|8|@]|9|@]|C|$]]|$1|Z|3|10|5|L|7|2O|8|@]|9|@]|C|$M|N]]|$1|11|3|12|5|6|7|2P|8|@]|9|@]|C|$]]|$1|13|3|R|5|S|7|2Q|8|@]|9|@$A|2R|B|2S|1|2T]]|C|$]]|$1|14|3|15|5|6|7|2U|8|@]|9|@]|C|$]]|$1|16|3|17|5|L|7|2V|8|@]|9|@]|C|$M|N]]|$1|18|3|19|5|6|7|2W|8|@]|9|@]|C|$]]|$1|1A|3|R|5|S|7|2X|8|@]|9|@$A|2Y|B|2Z|1|30]]|C|$]]|$1|1B|3|1C|5|6|7|31|8|@$A|32|B|33|F|G]]|9|@]|C|$]]|$1|1D|3|1E|5|L|7|34|8|@]|9|@]|C|$M|N]]|$1|1F|3|1G|5|6|7|35|8|@]|9|@]|C|$]]|$1|1H|3|R|5|S|7|36|8|@]|9|@$A|37|B|38|1|39]]|C|$]]|$1|1I|3|-4|5|6|7|3A|8|@]|9|@]|C|$]]]|1J|$1K|$5|1L|1M|1N|C|$1O|1P]]|1Q|$5|1L|1M|1N|C|$1O|1R]]|1S|$5|1T|1M|1U|C|$1V|1W|1X|-4]]|1Y|$5|1T|1M|1U|C|$1V|1Z|1X|-4]]|20|$5|1T|1M|1U|C|$1V|21|1X|-4]]|22|$5|1T|1M|1U|C|$1V|23|1X|-4]]]]

Please, post lossless versions of your input images. Lossy images modify the value of the pixels, creating artifacts that affect processing. I recreated your image and saved it as a <a href="https://i.imgur.com/DoznLz6.png" rel="nofollow noreferrer">lossless PNF file</a>.
I'm using OpenCV to get the result you want. I created a mask with the non-zero elements of your original input. Then, I used <a href="https://www.programmersought.com/article/38404456179/" rel="nofollow noreferrer">Flood-fill</a> to fill the outer shapes with the color you want. The final image can be obtained if you <code>AND</code> both images.
Let's see the code:
<pre><code># import opencv:
import cv2

# image path
path = &quot;D://opencvImages//&quot;
fileName = &quot;rectsLossless.png&quot;

# Reading an image in default mode:
inputImage = cv2.imread(path + fileName)

# Grayscale image:
grayscaleImage = cv2.cvtColor(inputImage, cv2.COLOR_BGR2GRAY)

# Get non-zero mask:
binaryThresh = 1
_, binaryMask = cv2.threshold(grayscaleImage, binaryThresh, 255, cv2.THRESH_BINARY)
</code></pre>
This bit creates the non-zero pixels mask:
<img src="https://i.imgur.com/PG37JN5.png" width="300" />
This will help to zero all the elements that are non-white. That image is the first part of the mask. Now, let's fill the outer shapes with red color. This is achieved in three steps:
<pre><code># Get image dimensions:
(imageHeight, imageWidth) = inputImage.shape[:2]

# Get image center:
xCenter = int(0.5 * imageWidth)
yCenter = int(0.5 * imageHeight)

# Get flood-fill target color
floodColor = inputImage[yCenter, xCenter]
print(&quot;Flood Color: %s&quot; % floodColor)
# numpy array to tuple
floodColor = (int(floodColor[0]), int(floodColor[1]), int(floodColor[2]))
</code></pre>
The first step gets the actual filling color. I suppose that the red is located more or less at the center of the image. Then, the second step involves filling all the &quot;foreground&quot; pixels with white. Let's seed at the top left corner:
<pre><code># Flood fill at top left corner:
leftCorner = (1, 1)
whiteColor = (255, 255, 255)
cv2.floodFill(inputImage, None, leftCorner, whiteColor)
</code></pre>
This is the result:
<img src="https://i.imgur.com/WKL2w42.png" width="300" />
Note how the shapes that are partially outside of the red rectangle are all now connected by the white color. Let's fill again, but this time using the red color I extracted previously:
<pre><code># Second Flood-fill
cv2.floodFill(inputImage, None, leftCorner, floodColor)
</code></pre>
This yields the following image:
<img src="https://i.imgur.com/SLWNPIk.png" width="300" />
Let's create the final image by <code>AND</code>ing this result with the original non-zero mask:
<pre><code># Create final image:
outImage = cv2.bitwise_and(inputImage, inputImage, mask=binaryMask)
</code></pre>
This is the final result:
<img src="https://i.imgur.com/ABfjlSI.png" width="300" />

blocks|key|1454546|text|这个问题非常接近这个问题。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1454547|我的解决方案也很接近..。|1454548|假设颜色是黑色、白色和红色(一般情况下可能比较棘手)，我们可以使用以下步骤：|1454549|用白色填充黑色背景(使用cv2.floodFill)。
红色边界上的白色对象与背景合并。|unordered-list-item|style|CODE|1454550|用黑色填充白色背景(使用cv2.floodFill)。
红色边界上的白色物体将是黑色的。|1454551|将红色通道从原始图像复制到“填充”图像。
白色像素的红色通道是255，因此黑白变成红色。|1454552|代码示例：|1454553|import+cv2
import+numpy+as+np

img+=+cv2.imread('red_white_black.jpg')

#+Copy+the+original+image+to+img2
img2+=+img.copy()

#+Fill+the+black+background+with+white+color
cv2.floodFill(img2,+None,+seedPoint=(0,+0),+newVal=(255,+255,+255),+loDiff=(50,+50,+50),+upDiff=(50,+50,+50))

cv2.imshow('black+background',+img2)++#+Show+img2+for+testing


#+Fill+the+white+background+with+black+color
cv2.floodFill(img2,+None,+seedPoint=(0,+0),+newVal=(0,+0,+0),+loDiff=(50,+50,+50),+upDiff=(50,+50,+50))

cv2.imshow('white+background',+img2)++#+Show+img2+for+testing


#+Copy+the+red+color+channel+from+the+original+image+to+img2
img2[:,+:,+2]+=+img[:,+:,+2]

cv2.imshow('img2',+img2)++#+Show+img2+for+testing
cv2.waitKey()
cv2.destroyAllWindows()|code-block|syntax|javascript|1454554|结果：|1454555|黑色背景：|1454556|📷|atomic|1454557|​|1454558|白色背景：|1454559|1454560|1454561|img2|1454562|1454563|1454564|红色周围的黑色边距，是因为原来的图像是JPEG而不是PNG+(颜色不是纯的)，而红色不是纯红色。|1454565|我们可以使用以下代码修复它(代码中的代码不太优雅).|1454566|red+=+img[:,+:,+2]
r+=+np.median(img[:,+:,+2][red+>+50])
g+=+np.median(img[:,+:,+1][red+>+50])
b+=+np.median(img[:,+:,+0][red+>+50])

mask+=+np.logical_and(img[:,+:,+0]+>+100,+img2[:,+:,+0]+<=+100)
img3+=+img2.copy()
img3[:,+:,+2][mask]+=+r
img3[:,+:,+1][mask]+=+g
img3[:,+:,+0][mask]+=+b
img3[:,+:,+2]+=+cv2.morphologyEx(img3[:,+:,+2],+cv2.MORPH_CLOSE,+np.ones((3,+3),+np.uint8))
img3[:,+:,+1]+=+cv2.morphologyEx(img3[:,+:,+1],+cv2.MORPH_OPEN,+np.ones((3,+3),+np.uint8))
img3[:,+:,+0]+=+cv2.morphologyEx(img3[:,+:,+0],+cv2.MORPH_OPEN,+np.ones((3,+3),+np.uint8))
cv2.imshow('img3',+img3)
cv2.waitKey()
cv2.destroyAllWindows()|1454567|1454568|1454569|1454570|entityMap|0|LINK|mutability|MUTABLE|url|https://stackoverflow.com/questions/71665090/change-pixel-colors-between-two-different-colors|1|IMAGE|IMMUTABLE|imageUrl|https://developer.qcloudimg.com/http-save/yehe-900000/ac1985b282d548ab57b42458dd265fce.png|imageAlt|2|https://developer.qcloudimg.com/http-save/yehe-900000/892db7a3a696ef22c66f61dcc9e18e23.png|3|https://developer.qcloudimg.com/http-save/yehe-900000/3db3d979b94a5f50f20f5ecacdbb187f.png|4|https://developer.qcloudimg.com/http-save/yehe-900000/2311f6520f931e25995bd45127c94cab.png^0|8|4|0|0|0|0|C|D|0|C|D|0|0|0|0|0|0|0|1|1|0|0|0|0|1|2|0|0|0|4|0|0|1|3|0|0|0|0|0|0|0|1|4|0|0^^$0|@$1|2|3|4|5|6|7|27|8|@]|9|@$A|28|B|29|1|2A]]|C|$]]|$1|D|3|E|5|6|7|2B|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|2C|8|@]|9|@]|C|$]]|$1|H|3|I|5|J|7|2D|8|@$A|2E|B|2F|K|L]]|9|@]|C|$]]|$1|M|3|N|5|J|7|2G|8|@$A|2H|B|2I|K|L]]|9|@]|C|$]]|$1|O|3|P|5|J|7|2J|8|@]|9|@]|C|$]]|$1|Q|3|R|5|6|7|2K|8|@]|9|@]|C|$]]|$1|S|3|T|5|U|7|2L|8|@]|9|@]|C|$V|W]]|$1|X|3|Y|5|6|7|2M|8|@]|9|@]|C|$]]|$1|Z|3|10|5|6|7|2N|8|@]|9|@]|C|$]]|$1|11|3|12|5|13|7|2O|8|@]|9|@$A|2P|B|2Q|1|2R]]|C|$]]|$1|14|3|15|5|6|7|2S|8|@]|9|@]|C|$]]|$1|16|3|17|5|6|7|2T|8|@]|9|@]|C|$]]|$1|18|3|12|5|13|7|2U|8|@]|9|@$A|2V|B|2W|1|2X]]|C|$]]|$1|19|3|15|5|6|7|2Y|8|@]|9|@]|C|$]]|$1|1A|3|1B|5|6|7|2Z|8|@$A|30|B|31|K|L]]|9|@]|C|$]]|$1|1C|3|12|5|13|7|32|8|@]|9|@$A|33|B|34|1|35]]|C|$]]|$1|1D|3|15|5|6|7|36|8|@]|9|@]|C|$]]|$1|1E|3|1F|5|6|7|37|8|@]|9|@]|C|$]]|$1|1G|3|1H|5|6|7|38|8|@]|9|@]|C|$]]|$1|1I|3|1J|5|U|7|39|8|@]|9|@]|C|$V|W]]|$1|1K|3|Y|5|6|7|3A|8|@]|9|@]|C|$]]|$1|1L|3|12|5|13|7|3B|8|@]|9|@$A|3C|B|3D|1|3E]]|C|$]]|$1|1M|3|15|5|6|7|3F|8|@]|9|@]|C|$]]|$1|1N|3|-4|5|6|7|3G|8|@]|9|@]|C|$]]]|1O|$1P|$5|1Q|1R|1S|C|$1T|1U]]|1V|$5|1W|1R|1X|C|$1Y|1Z|20|-4]]|21|$5|1W|1R|1X|C|$1Y|22|20|-4]]|23|$5|1W|1R|1X|C|$1Y|24|20|-4]]|25|$5|1W|1R|1X|C|$1Y|26|20|-4]]]]

The question is very close to <a href="https://stackoverflow.com/questions/71665090/change-pixel-colors-between-two-different-colors">this question</a>. 
My solution is close too...
Assuming the colors are black white and red (the general case may be trickier), we may use the following stages:
<ul>
<li>Fill the black background with white color (using <code>cv2.floodFill</code>). 
The white object on the red boundary are merged with the background.</li>
<li>Fill the white background with black color (using <code>cv2.floodFill</code>). 
The white object on the red boundary are going to be black.</li>
<li>Copy the red color channel from the original image to &quot;filled&quot; image. 
The red channel of a white pixel is 255, so black and white becomes red.</li>
</ul>
<hr />
Code sample:
<pre><code>import cv2
import numpy as np

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

# Copy the original image to img2
img2 = img.copy()

# Fill the black background with white color
cv2.floodFill(img2, None, seedPoint=(0, 0), newVal=(255, 255, 255), loDiff=(50, 50, 50), upDiff=(50, 50, 50))

cv2.imshow('black background', img2) # Show img2 for testing


# Fill the white background with black color
cv2.floodFill(img2, None, seedPoint=(0, 0), newVal=(0, 0, 0), loDiff=(50, 50, 50), upDiff=(50, 50, 50))

cv2.imshow('white background', img2) # Show img2 for testing


# Copy the red color channel from the original image to img2
img2[:, :, 2] = img[:, :, 2]

cv2.imshow('img2', img2) # Show img2 for testing
cv2.waitKey()
cv2.destroyAllWindows()
</code></pre>
<hr />
Results: 
Black background: 
<a href="https://i.stack.imgur.com/nXU7g.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/nXU7g.png" alt="enter image description here" /></a>
White background: 
<a href="https://i.stack.imgur.com/6VEqZ.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/6VEqZ.png" alt="enter image description here" /></a>
<code>img2</code>: 
<a href="https://i.stack.imgur.com/xWSkS.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/xWSkS.png" alt="enter image description here" /></a>
The black margins around the red, are because the original image is JPEG and not PNG (colors are not pure), and the red is not pure red.
We may fix it using the following code (the code in not very elegant)...
<pre><code>red = img[:, :, 2]
r = np.median(img[:, :, 2][red &gt; 50])
g = np.median(img[:, :, 1][red &gt; 50])
b = np.median(img[:, :, 0][red &gt; 50])

mask = np.logical_and(img[:, :, 0] &gt; 100, img2[:, :, 0] &lt;= 100)
img3 = img2.copy()
img3[:, :, 2][mask] = r
img3[:, :, 1][mask] = g
img3[:, :, 0][mask] = b
img3[:, :, 2] = cv2.morphologyEx(img3[:, :, 2], cv2.MORPH_CLOSE, np.ones((3, 3), np.uint8))
img3[:, :, 1] = cv2.morphologyEx(img3[:, :, 1], cv2.MORPH_OPEN, np.ones((3, 3), np.uint8))
img3[:, :, 0] = cv2.morphologyEx(img3[:, :, 0], cv2.MORPH_OPEN, np.ones((3, 3), np.uint8))
cv2.imshow('img3', img3)
cv2.waitKey()
cv2.destroyAllWindows()
</code></pre>
<hr />
Result: 
<a href="https://i.stack.imgur.com/XXNC2.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/XXNC2.png" alt="enter image description here" /></a>

Considering this image:
<a href="https://i.stack.imgur.com/lEcxM.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/lEcxM.png" alt="enter image description here" /></a>
I would like to change the set of white pixels in contact with black pixels by red, this way:
<a href="https://i.stack.imgur.com/WN7xQ.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/WN7xQ.png" alt="enter image description here" /></a>
I tried to use this code in <code>python</code>:
<pre><code>import numpy as np
from PIL import Image

im = Image.open('image.png')
data = np.array(im)

r1, g1, b1 = 255, 255, 255 # Original value
r2, g2, b2 = 0, 0, 255 # Value that we want to replace it with

red, green, blue = data[:,:,0], data[:,:,1], data[:,:,2]
mask = (red == r1) &amp; (green == g1) &amp; (blue == b1)
data[:,:,:3][mask] = [r2, g2, b2]

im = Image.fromarray(data)
</code></pre>
But I changed all white pixels by red. But could be an <code>UNIX</code> approach suggestion too.

How to change the set of pixel colors in contatc with black color

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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考虑到这一形象：​​我想用红色更改与黑色像素接触的一组白色像素，这样：​我试图在python中使用这段代码import numpy as npfrom PIL import Imageim = Image.open('image.png')data = np.array(im)r1, g1, b1 = 255, 255...

问如何用黑色更改contatc中的像素颜色集
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