botcs - 1 year ago 143

Python Question

Here is my code which I used for checking the correctness of convolve2d

`import numpy as np`

from scipy.signal import convolve2d

X = np.random.randint(5, size=(10,10))

K = np.random.randint(5, size=(3,3))

print "Input's top-left corner:"

print X[:3,:3]

print 'Kernel:'

print K

print 'Hardcording the calculation of a valid convolution (top-left)'

print (X[:3,:3]*K)

print 'Sums to'

print (X[:3,:3]*K).sum()

print 'However the top-left value of the convolve2d result'

Y = convolve2d(X, K, 'valid')

print Y[0,0]

On my computer this results in the following:

`Input's top-left (3x3) corner:`

[[0 0 0]

[1 1 2]

[1 3 0]]

Kernel:

[[4 1 1]

[0 3 3]

[2 1 2]]

Hardcording the calculation of a valid convolution (top-left)

[[0 0 0]

[0 3 6]

[2 3 0]]

Sums to

14

However the top-left value of the convolve2d result

10

Answer Source

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()`