blocks|key|195262|text|*编辑-已更新以处理具有alpha通道的图像。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|195263|这对我很有效：|195264|195265|制作一个全黑(全蒙版)的蒙版|unordered-list-item|195266|在感兴趣区域的形状中用白色填充多边形|195267|将蒙版和图像组合在一起，以获得其他所有地方都是黑色的感兴趣区域|195268|195269|对于接受掩码的函数，您可能只想将图像和掩码分开。然而，我相信这做了您特别要求的：|195270|import+cv2
import+numpy+as+np

#+original+image
#+-1+loads+as-is+so+if+it+will+be+3+or+4+channel+as+the+original
image+=+cv2.imread('image.png',+-1)
#+mask+defaulting+to+black+for+3-channel+and+transparent+for+4-channel
#+(of+course+replace+corners+with+yours)
mask+=+np.zeros(image.shape,+dtype=np.uint8)
roi_corners+=+np.array([[(10,10),+(300,300),+(10,300)]],+dtype=np.int32)
#+fill+the+ROI+so+it+doesn't+get+wiped+out+when+the+mask+is+applied
channel_count+=+image.shape[2]++#+i.e.+3+or+4+depending+on+your+image
ignore_mask_color+=+(255,)*channel_count
cv2.fillPoly(mask,+roi_corners,+ignore_mask_color)
#+from+Masterfool:+use+cv2.fillConvexPoly+if+you+know+it's+convex

#+apply+the+mask
masked_image+=+cv2.bitwise_and(image,+mask)

#+save+the+result
cv2.imwrite('image_masked.png',+masked_image)|code-block|syntax|javascript|195271|entityMap^0|0|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|V|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|W|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|X|8|@]|9|@]|A|$]]|$1|E|3|F|5|G|7|Y|8|@]|9|@]|A|$]]|$1|H|3|I|5|G|7|Z|8|@]|9|@]|A|$]]|$1|J|3|K|5|G|7|10|8|@]|9|@]|A|$]]|$1|L|3|-4|5|6|7|11|8|@]|9|@]|A|$]]|$1|M|3|N|5|6|7|12|8|@]|9|@]|A|$]]|$1|O|3|P|5|Q|7|13|8|@]|9|@]|A|$R|S]]|$1|T|3|-4|5|6|7|14|8|@]|9|@]|A|$]]]|U|$]]

*edit - updated to work with images that have an alpha channel.

This worked for me:

<ul>
<li>Make a mask with all black (all masked)</li>
<li>Fill a polygon with white in the shape of your ROI</li>
<li>combine the mask and your image to get the ROI with black everywhere else</li>
</ul>

You probably just want to keep the image and mask separate for functions that accept masks. However, I believe this does what you specifically asked for:

<pre><code>import cv2
import numpy as np

# original image
# -1 loads as-is so if it will be 3 or 4 channel as the original
image = cv2.imread('image.png', -1)
# mask defaulting to black for 3-channel and transparent for 4-channel
# (of course replace corners with yours)
mask = np.zeros(image.shape, dtype=np.uint8)
roi_corners = np.array([[(10,10), (300,300), (10,300)]], dtype=np.int32)
# fill the ROI so it doesn't get wiped out when the mask is applied
channel_count = image.shape[2] # i.e. 3 or 4 depending on your image
ignore_mask_color = (255,)*channel_count
cv2.fillPoly(mask, roi_corners, ignore_mask_color)
# from Masterfool: use cv2.fillConvexPoly if you know it's convex

# apply the mask
masked_image = cv2.bitwise_and(image, mask)

# save the result
cv2.imwrite('image_masked.png', masked_image)
</code></pre>

blocks|key|197421|text|以下代码将有助于裁剪图像并将其置于白色背景中。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|197422|import+cv2
import+numpy+as+np

#+load+the+image
image_path+=+'input+image+path'
image+=+cv2.imread(image_path)

#+create+a+mask+with+white+pixels
mask+=+np.ones(image.shape,+dtype=np.uint8)
mask.fill(255)

#+points+to+be+cropped
roi_corners+=+np.array([[(0,+300),+(1880,+300),+(1880,+400),+(0,+400)]],+dtype=np.int32)
#+fill+the+ROI+into+the+mask
cv2.fillPoly(mask,+roi_corners,+0)

#+The+mask+image
cv2.imwrite('image_masked.png',+mask)

#+applying+th+mask+to+original+image
masked_image+=+cv2.bitwise_or(image,+mask)

#+The+resultant+image
cv2.imwrite('new_masked_image.png',+masked_image)|code-block|syntax|javascript|197423|输入图像：|197424|📷|atomic|offset|length|197425|​|197426|遮罩图像：|197427|197428|197429|结果输出图像：|197430|197431|197432|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/253a02df95f6ab4c8f4fb2ca0c4ba7d4.jpeg|imageAlt|1|https://ask.qcloudimg.com/http-save/yehe-900000/e4f6b95676d992a5890a1e022d7f1b39.png|2|https://ask.qcloudimg.com/http-save/yehe-900000/d6ea6e65888aff47a60c216c847f2e8f.png^0|0|0|0|0|1|0|0|0|0|0|1|1|0|0|0|0|1|2|0|0^^$0|@$1|2|3|4|5|6|7|1A|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|1B|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|1C|8|@]|9|@]|A|$]]|$1|I|3|J|5|K|7|1D|8|@]|9|@$L|1E|M|1F|1|1G]]|A|$]]|$1|N|3|O|5|6|7|1H|8|@]|9|@]|A|$]]|$1|P|3|Q|5|6|7|1I|8|@]|9|@]|A|$]]|$1|R|3|J|5|K|7|1J|8|@]|9|@$L|1K|M|1L|1|1M]]|A|$]]|$1|S|3|O|5|6|7|1N|8|@]|9|@]|A|$]]|$1|T|3|U|5|6|7|1O|8|@]|9|@]|A|$]]|$1|V|3|J|5|K|7|1P|8|@]|9|@$L|1Q|M|1R|1|1S]]|A|$]]|$1|W|3|O|5|6|7|1T|8|@]|9|@]|A|$]]|$1|X|3|-4|5|6|7|1U|8|@]|9|@]|A|$]]]|Y|$Z|$5|10|11|12|A|$13|14|15|-4]]|16|$5|10|11|12|A|$13|17|15|-4]]|18|$5|10|11|12|A|$13|19|15|-4]]]]

The following code would be helpful for cropping the images and get them in a white background.

<pre><code>import cv2
import numpy as np

# load the image
image_path = 'input image path'
image = cv2.imread(image_path)

# create a mask with white pixels
mask = np.ones(image.shape, dtype=np.uint8)
mask.fill(255)

# points to be cropped
roi_corners = np.array([[(0, 300), (1880, 300), (1880, 400), (0, 400)]], dtype=np.int32)
# fill the ROI into the mask
cv2.fillPoly(mask, roi_corners, 0)

# The mask image
cv2.imwrite('image_masked.png', mask)

# applying th mask to original image
masked_image = cv2.bitwise_or(image, mask)

# The resultant image
cv2.imwrite('new_masked_image.png', masked_image)
</code></pre>

Input Image:
<a href="https://i.stack.imgur.com/cBK1h.jpg" rel="noreferrer"><img src="https://i.stack.imgur.com/cBK1h.jpg" alt="input image"></a>

Mask Image:
<a href="https://i.stack.imgur.com/lmYra.png" rel="noreferrer"><img src="https://i.stack.imgur.com/lmYra.png" alt="mask image"></a>

Resultant output image:
<a href="https://i.stack.imgur.com/gfKaH.png" rel="noreferrer"><img src="https://i.stack.imgur.com/gfKaH.png" alt="enter image description here"></a>

I have a set of points that make a shape (closed polyline). Now I want to copy/crop all pixels from some image inside this shape, leaving the rest black/transparent. How do I do this? 

For example, I have this: 

<img src="https://i.stack.imgur.com/2QXbO.jpg" alt="enter image description here">

and I want to get this: 

<img src="https://i.stack.imgur.com/Y20wb.png" alt="enter image description here">

NumPy/OpenCV 2: how do I crop non-rectangular region?

我有一组构成闭合多段线形状()的点。现在我想复制/裁剪这个shape中某个图像中的所有像素，剩下的则是黑色/透明的。我该怎么做呢？例如，我有这样的例子：​​我想要得到的是：​​

问NumPy/OpenCV 2:如何裁剪非矩形区域？
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