Lauri Love (nsh) wrote:
Let me know if there is any faster solution short of coding in some
distance functions to the C modules
You might do better with numpy and/or scipy.ndimage.
You can convert a PIL RGB image to a numpy array very easily. I think
it's as simple as:
import numpy as np
a
Ok, I found a reasonable solution using the ImageStat module to get the sum
of pixels of the difference image. This gives the manhattan distance when
divided by the pixel count and averaged over RGB.
In [151]: def idiff(im1,im2):
return
array(ImageStat.Stat(ImageChops.difference(im1,im2)).sum)
