On Wed, May 27, 2009 at 10:33, cp <lubensch.proletariat.inc@gmail.com> wrote:

Testing the PIL vs numpy in calculating the mean value of each color channel of an image I timed the following.

impil = Image.open("10.tif") imnum = asarray(impil)

#in PIL for i in range(1,10): stats = ImageStat.Stat(impil) stats.mean

# for numpy for i in range(1,10): imnum.reshape(-1,3).mean(axis=0)

The image I tested initially is 2000x2000 RGB tif ~11mb in size. I set a timer in each for loop and measured the performance of numpy 7 times slower than PIL. When I did the the same with an 10x10 RGB tif and with 1000 cycles in for, numpy was 25 times faster than PIL. Why is that? Does mean or reshape, make a copy?

reshape() might if the array wasn't contiguous. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco