[Python] Difference between convolve2d and filter2D. Why is there a difference in output...

I need to perform a 2D convolution. I have a similarity matrix of shape 100, 100 and a filter of shape 5,5.

If I do using scipy:

scipy.signal.convolve2d(similarity_matrix, np.diag(filter))


I get 104,104 matrix in response.

But if I do using OpenCV's filter2D method:

cv2.filter2D(similarity_matrix, -1, np.diag(filter))


I get a 100,100 matrix in response.

• What is happening here? Why is there a difference in shape?
• With convolve2d why do I get 4 extra rows and 4 extra columns?

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