blocks|key|3055872|text|看起来scipy.signal.convolve2d就是你要找的。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|3055873|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.convolve2d.html^0|3|N|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Looks like <a href="http://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.convolve2d.html" rel="nofollow noreferrer">scipy.signal.convolve2d</a> is what you're looking for.

blocks|key|3055960|text|虽然其他答案已经提到了scipy.signal.convolve2d作为等价物，但我发现使用mode='same'时结果确实不同。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|3055961|Matlab的conv2会在图像的底部和右侧产生伪像，而scipy.signal.convolve2d在图像的顶部和左侧会产生相同的伪像。|3055962|查看这些链接以查看显示行为的图表(没有足够的声誉直接发布图像)：|3055963|Upper+left+corner+of+convoluted+Barbara|3055964|Lower+right+corner+of+convoluted+Barbara|3055965|下面的包装器可能不是很有效，但在我的例子中，通过将输入数组和输出数组都旋转180度解决了这个问题：|3055966|import+numpy+as+np
from+scipy.signal+import+convolve2d

def+conv2(x,+y,+mode='same'):
++++return+np.rot90(convolve2d(np.rot90(x,+2),+np.rot90(y,+2),+mode=mode),+2)|code-block|syntax|javascript|3055967|entityMap|0|LINK|mutability|MUTABLE|url|https://www.informatik.uni-bremen.de/%257Ejowlo/conv2img/conv2_upper_left.png|1|https://www.informatik.uni-bremen.de/%257Ejowlo/conv2img/conv2_lower_right.png^0|B|N|1A|B|0|7|5|S|N|0|0|0|13|0|0|0|14|1|0|0|0^^$0|@$1|2|3|4|5|6|7|14|8|@$9|15|A|16|B|C]|$9|17|A|18|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|19|8|@$9|1A|A|1B|B|C]|$9|1C|A|1D|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|1E|8|@]|D|@]|E|$]]|$1|J|3|K|5|6|7|1F|8|@]|D|@$9|1G|A|1H|1|1I]]|E|$]]|$1|L|3|M|5|6|7|1J|8|@]|D|@$9|1K|A|1L|1|1M]]|E|$]]|$1|N|3|O|5|6|7|1N|8|@]|D|@]|E|$]]|$1|P|3|Q|5|R|7|1O|8|@]|D|@]|E|$S|T]]|$1|U|3|-4|5|6|7|1P|8|@]|D|@]|E|$]]]|V|$W|$5|X|Y|Z|E|$10|11]]|12|$5|X|Y|Z|E|$10|13]]]]

While the other answers already mention <code>scipy.signal.convolve2d</code> as an equivalent, i found that the results do differ when using <code>mode='same'</code>.
While Matlab's <code>conv2</code> results in artifacts on the bottom and right of an image, <code>scipy.signal.convolve2d</code> has the same artifacts on the top and left of an image.
See these links for plots showing the behaviour (not enough reputation to post the images directly):
<a href="https://www.informatik.uni-bremen.de/%7Ejowlo/conv2img/conv2_upper_left.png" rel="nofollow noreferrer">Upper left corner of convoluted Barbara</a>
<a href="https://www.informatik.uni-bremen.de/%7Ejowlo/conv2img/conv2_lower_right.png" rel="nofollow noreferrer">Lower right corner of convoluted Barbara</a>
The following wrapper might not be very efficient, but solved the problem in my case by rotating both input arrays and the output array, each by 180 degrees:
<pre><code>import numpy as np
from scipy.signal import convolve2d

def conv2(x, y, mode='same'):
 return np.rot90(convolve2d(np.rot90(x, 2), np.rot90(y, 2), mode=mode), 2)
</code></pre>

blocks|key|1047136|text|scipy.ndimage.convolve|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|1047137|它是在n维空间中实现的。|unstyled|1047138|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$B|C]]|$1|D|3|E|5|F|7|J|8|@]|9|@]|A|$]]|$1|G|3|-4|5|F|7|K|8|@]|9|@]|A|$]]]|H|$]]

<pre><code>scipy.ndimage.convolve
</code></pre>

does it in n dimensions.

blocks|key|1790516|text|必须为每个非单一维度提供偏移量，才能重现Matlab的conv2结果。一个简单的实现只支持'same‘选项，可以这样实现|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1790517|import+numpy+as+np
from+scipy.ndimage.filters+import+convolve

def+conv2(x,y,mode='same'):
++++"""
++++Emulate+the+function+conv2+from+Mathworks.

++++Usage:

++++z+=+conv2(x,y,mode='same')

++++TODO:+
+++++-+Support+other+modes+than+'same'+(see+conv2.m)
++++"""

++++if+not(mode+==+'same'):
++++++++raise+Exception("Mode+not+supported")

++++#+Add+singleton+dimensions
++++if+(len(x.shape)+<+len(y.shape)):
++++++++dim+=+x.shape
++++++++for+i+in+range(len(x.shape),len(y.shape)):
++++++++++++dim+=+(1,)+%2B+dim
++++++++x+=+x.reshape(dim)
++++elif+(len(y.shape)+<+len(x.shape)):
++++++++dim+=+y.shape
++++++++for+i+in+range(len(y.shape),len(x.shape)):
++++++++++++dim+=+(1,)+%2B+dim
++++++++y+=+y.reshape(dim)

++++origin+=+()

++++#+Apparently,+the+origin+must+be+set+in+a+special+way+to+reproduce
++++#+the+results+of+scipy.signal.convolve+and+Matlab
++++for+i+in+range(len(x.shape)):
++++++++if+(+(x.shape[i]+-+y.shape[i])+%25+2+==+0+and
+++++++++++++x.shape[i]+>+1+and
+++++++++++++y.shape[i]+>+1):
++++++++++++origin+=+origin+%2B+(-1,)
++++++++else:
++++++++++++origin+=+origin+%2B+(0,)

++++z+=+convolve(x,y,+mode='constant',+origin=origin)

++++return+z|code-block|syntax|javascript|1790518|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

You must provide an offset for each non-singleton dimension to reproduce the results of Matlab's conv2. A simple implementation supporting the 'same' option, only, could be made like this

<pre><code>import numpy as np
from scipy.ndimage.filters import convolve

def conv2(x,y,mode='same'):
 """
 Emulate the function conv2 from Mathworks.

 Usage:

 z = conv2(x,y,mode='same')

 TODO: 
 - Support other modes than 'same' (see conv2.m)
 """

 if not(mode == 'same'):
 raise Exception("Mode not supported")

 # Add singleton dimensions
 if (len(x.shape) &lt; len(y.shape)):
 dim = x.shape
 for i in range(len(x.shape),len(y.shape)):
 dim = (1,) + dim
 x = x.reshape(dim)
 elif (len(y.shape) &lt; len(x.shape)):
 dim = y.shape
 for i in range(len(y.shape),len(x.shape)):
 dim = (1,) + dim
 y = y.reshape(dim)

 origin = ()

 # Apparently, the origin must be set in a special way to reproduce
 # the results of scipy.signal.convolve and Matlab
 for i in range(len(x.shape)):
 if ( (x.shape[i] - y.shape[i]) % 2 == 0 and
 x.shape[i] &gt; 1 and
 y.shape[i] &gt; 1):
 origin = origin + (-1,)
 else:
 origin = origin + (0,)

 z = convolve(x,y, mode='constant', origin=origin)

 return z
</code></pre>

Does Python or any of its modules have an equivalent of MATLAB's <a href="http://www.mathworks.com/help/techdoc/ref/conv2.html" rel="noreferrer">conv2</a> function? More specifically, I'm interested in something that does the same computation as <code>conv2(A, B, 'same')</code> in MATLAB.

Is there a Python equivalent of MATLAB's conv2 function?

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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Python或它的任何模块都有MATLAB的函数的等价物吗？更具体地说，我感兴趣的是与MATLAB中的conv2(A, B, 'same')执行相同计算的东西。

问有没有与MATLAB的conv2函数等效的Python函数？
EN

回答 4

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问有没有与MATLAB的conv2函数等效的Python函数？EN

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问有没有与MATLAB的conv2函数等效的Python函数？
EN