How do I find Wally with Python?

Here’s an implementation with mahotas

from pylab import imshow
import numpy as np
import mahotas
wally = mahotas.imread('DepartmentStore.jpg')

wfloat = wally.astype(float)
r,g,b = wfloat.transpose((2,0,1))

Split into red, green, and blue channels. It’s better to use floating point arithmetic below, so we convert at the top.

w = wfloat.mean(2)

w is the white channel.

pattern = np.ones((24,16), float)
for i in xrange(2):
    pattern[i::4] = -1

Build up a pattern of +1,+1,-1,-1 on the vertical axis. This is wally’s shirt.

v = mahotas.convolve(r-w, pattern)

Convolve with red minus white. This will give a strong response where the shirt is.

mask = (v == v.max())
mask = mahotas.dilate(mask, np.ones((48,24)))

Look for the maximum value and dilate it to make it visible. Now, we tone down the whole image, except the region or interest:

wally -= .8*wally * ~mask[:,:,None]
imshow(wally)

And we get !