scipy convolve2d outputs wrong values
I think the problem is that you did not do what SciPy implemented. I won't dwell on the details or the foundations but only provide you with a solution:
Reverse the kernel.
>>> import numpy as np>>> arr = np.array([[0, 0, 0], [1, 1, 2], [1, 3, 0]])>>> kernel = np.array([[4, 1, 1], [0, 3, 3], [2, 1, 2]])>>> from scipy.signal import convolve2d>>> convolve2d(arr, kernel[::-1, ::-1])array([[ 0, 0, 0, 0, 0], [ 2, 3, 7, 4, 4], [ 5, 13, 14, 12, 0], [ 4, 14, 16, 6, 8], [ 1, 4, 7, 12, 0]])>>> convolve2d(arr, kernel[::-1, ::-1], 'valid')array([[14]])
The expression (X[:3,:3]*K).sum() is not correct. For convolution, you have to reverse the kernel, e.g. (X[:3,:3]*K[::-1,::-1]).sum()