blocks|key|749143|text|你的X，Y坐标颠倒了。Python/OpenCV需要将它们列为X、Y(即使您将它们定义为numpy值)。必须指定给getPerspectiveTransform的数组必须将它们列为X，Y。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|749144|输入：|749145|​|749146|📷|atomic|offset|length|749147|749148|import+numpy+as+np
import+cv2

#+read+input
img+=+cv2.imread("sudoku.jpg")

#+specify+desired+output+size+
width+=+350
height+=+350

#+specify+conjugate+x,y+coordinates+(not+y,x)
input+=+np.float32([[62,71],+[418,59],+[442,443],+[29,438]])
output+=+np.float32([[0,0],+[width-1,0],+[width-1,height-1],+[0,height-1]])

#+compute+perspective+matrix
matrix+=+cv2.getPerspectiveTransform(input,output)

print(matrix.shape)
print(matrix)

#+do+perspective+transformation+setting+area+outside+input+to+black
imgOutput+=+cv2.warpPerspective(img,+matrix,+(width,height),+cv2.INTER_LINEAR,+borderMode=cv2.BORDER_CONSTANT,+borderValue=(0,0,0))
print(imgOutput.shape)

#+save+the+warped+output
cv2.imwrite("sudoku_warped.jpg",+imgOutput)

#+show+the+result
cv2.imshow("result",+imgOutput)
cv2.waitKey(0)
cv2.destroyAllWindows()|code-block|syntax|javascript|749149|749150|结果：|749151|749152|749153|749154|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://developer.qcloudimg.com/http-save/yehe-900000/d80423b18e0543e595d3cba2d88bf987.jpg|imageAlt|1|https://developer.qcloudimg.com/http-save/yehe-900000/c7044677a0fbce4ffa8632d4ec59ed91.jpg^0|0|0|0|0|1|0|0|0|0|0|0|0|0|1|1|0|0^^$0|@$1|2|3|4|5|6|7|17|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|18|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|19|8|@]|9|@]|A|$]]|$1|F|3|G|5|H|7|1A|8|@]|9|@$I|1B|J|1C|1|1D]]|A|$]]|$1|K|3|E|5|6|7|1E|8|@]|9|@]|A|$]]|$1|L|3|M|5|N|7|1F|8|@]|9|@]|A|$O|P]]|$1|Q|3|E|5|6|7|1G|8|@]|9|@]|A|$]]|$1|R|3|S|5|6|7|1H|8|@]|9|@]|A|$]]|$1|T|3|E|5|6|7|1I|8|@]|9|@]|A|$]]|$1|U|3|G|5|H|7|1J|8|@]|9|@$I|1K|J|1L|1|1M]]|A|$]]|$1|V|3|E|5|6|7|1N|8|@]|9|@]|A|$]]|$1|W|3|-4|5|6|7|1O|8|@]|9|@]|A|$]]]|X|$Y|$5|Z|10|11|A|$12|13|14|-4]]|15|$5|Z|10|11|A|$12|16|14|-4]]]]

You have your X,Y coordinates reversed. Python/OpenCV requires them listed as X,Y (even though you define them as numpy values). The array you must specify to getPerspectiveTransform must list them as X,Y.
Input:
<a href="https://i.stack.imgur.com/IJVMR.jpg" rel="noreferrer"><img src="https://i.stack.imgur.com/IJVMR.jpg" alt="enter image description here" /></a>
<pre><code>import numpy as np
import cv2

# read input
img = cv2.imread(&quot;sudoku.jpg&quot;)

# specify desired output size 
width = 350
height = 350

# specify conjugate x,y coordinates (not y,x)
input = np.float32([[62,71], [418,59], [442,443], [29,438]])
output = np.float32([[0,0], [width-1,0], [width-1,height-1], [0,height-1]])

# compute perspective matrix
matrix = cv2.getPerspectiveTransform(input,output)

print(matrix.shape)
print(matrix)

# do perspective transformation setting area outside input to black
imgOutput = cv2.warpPerspective(img, matrix, (width,height), cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT, borderValue=(0,0,0))
print(imgOutput.shape)

# save the warped output
cv2.imwrite(&quot;sudoku_warped.jpg&quot;, imgOutput)

# show the result
cv2.imshow(&quot;result&quot;, imgOutput)
cv2.waitKey(0)
cv2.destroyAllWindows()
</code></pre>
 
Results:
<a href="https://i.stack.imgur.com/ZO0jf.jpg" rel="noreferrer"><img src="https://i.stack.imgur.com/ZO0jf.jpg" alt="enter image description here" /></a>

blocks|key|1559731|text|你应该注意到：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1559732|height|1559733|Destination：|unordered-list-item|1559734|坐标反转:宽度，缩放:第一位比:宽/高第二位比:+height/width|ordered-list-item|1559735|Order点坐标不重要，但源点和目的地点应该是相互对应的。|1559736|1559737|1559738|1559739|entityMap^0|0|0|0|1|1|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|R|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|S|8|@]|9|@]|A|$]]|$1|G|3|H|5|I|7|T|8|@]|9|@]|A|$]]|$1|J|3|K|5|I|7|U|8|@]|9|@]|A|$]]|$1|L|3|-4|5|6|7|V|8|@]|9|@]|A|$]]|$1|M|3|-4|5|6|7|W|8|@]|9|@]|A|$]]|$1|N|3|-4|5|6|7|X|8|@]|9|@]|A|$]]|$1|O|3|-4|5|6|7|Y|8|@]|9|@]|A|$]]]|P|$]]

You should note that:
<ol>
<li>Coordinate are reversed: width, height</li>
<li>Destination is scaled:
First Place Ratio: width/height
Second Place Ratio: height/width</li>
<li>Order of points coordinate do not matter but Source and Destination points should be correspondent to each other.</li>
</ol>

I am trying to perform a perspective transform of a sudoku puzzle. The expected transformation is happening only on the left side. Please help me by pointing out my mistake.
Input Image:
<a href="https://i.stack.imgur.com/WZ3wq.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/WZ3wq.jpg" alt="enter image description here" /></a>
Expected Output Image:
<a href="https://i.stack.imgur.com/b2nZ0.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/b2nZ0.jpg" alt="enter image description here" /></a>
The output I am getting:
<a href="https://i.stack.imgur.com/QikY4.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/QikY4.jpg" alt="enter image description here" /></a>
The corners of the sudoku puzzle found using cv2.approxpolydp() are as follows:
<pre><code>top_left = [71,62]
top_right = [59, 418]
bottom_right = [443, 442]
bottom_left = [438, 29]
</code></pre>
The shape of the output image is [300,300].
The corresponding output coordinates are :
<pre><code>output_top_left = [0,0]
output_top_right = [0, 299]
output_bottom_right = [299, 299]
output_bottom_left = [299,0]
</code></pre>
The following is the code I used for perspective transform:
<pre class="lang-py prettyprint-override"><code>#corners = [[71,62], [59, 418], [443, 442], [438, 29]]
new = np.float32([[0,0], [0,299], [299,299], [299,0]])
M = cv2.getPerspectiveTransform(np.float32(corners), new)
dst = cv2.warpPerspective(gray, M, (300,300))
</code></pre>
The generated Transformation Matrix is :
<pre><code>[[ 9.84584842e-01 3.31882531e-02 -7.19631955e+01]
 [ 8.23993265e-02 9.16380389e-01 -6.26659363e+01]
 [ 4.58051741e-04 1.45318012e-04 1.00000000e+00]]
</code></pre>

Perspective Transform in OPENCV PYTHON

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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我正在尝试对sudoku拼图进行透视转换。预期的转换只发生在左侧。请帮我指出我的错误。输入图像：​​预期输出图像：​​我得到的输出：​​使用cv2.approxpolydp()发现的sudoku难题的角落如下：top_left = [71,62]top_right = [59, 418]bottom_right = [...

问OPENCV PYTHON中的透视变换
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