Fastest 2D convolution or image filter in Python

Question

Several users have asked about the speed or memory consumption of image convolutions in numpy or scipy [1, 2, 3, 4]. From the responses and my experience using Numpy, I bel

Answer 1

On my machine, a hand-crafted circular convolution using FFTs seems to be fasted:

import numpy
x = numpy.random.random((2048, 2048)).astype(numpy.float32)
y = numpy.random.random((32, 32)).astype(numpy.float32)
z = numpy.fft.irfft2(numpy.fft.rfft2(x) * numpy.fft.rfft2(y, x.shape))

Note that this might treat the areas close to the edges differently than other ways, because it's a circular convolution.