2d convolution using python and numpy

Question

Hi

I am trying to perform a 2d convolution in python using numpy

I have a 2d array as follows with kernel H_r for the rows and H_c for the columns

data = np.zeros((nr, nc), dtype=np.float32)

#fill array with some data here then convolve

for r in range(nr):
    data[r,:] = np.convolve(data[r,:], H_r, 'same')

for c in range(nc):
    data[:,c] = np.convolve(data[:,c], H_c, 'same')

data = data.astype(np.uint8);

It does not produce the output that I was expecting, does this code look OK, I think the problem is with the casting from float32 to 8bit. Whats the best way to do this

Thanks

Answer 1

Since you already have your kernel separated you should simply use the sepfir2d function from scipy:

from scipy.signal import sepfir2d
convolved = sepfir2d(data, H_r, H_c)

On the other hand, the code you have there looks all right ...