On Mon, May 4, 2009 at 12:31 AM, Chris Colbert <sccolb...@gmail.com> wrote: > this actually sort of worked. Thanks for putting me on the right track. > > Here is what I ended up with. > > this is what I ended up with: > > def hist3d(imgarray): > histarray = N.zeros((16, 16, 16)) > temp = imgarray.copy() > bins = N.arange(0, 257, 16) > histarray = N.histogramdd((temp[:,:,0].ravel(), temp[:,:,1].ravel(), > temp[:,:,2].ravel()), bins=(bins, bins, bins))[0] > return histarray > > this creates a 3d histogram of rgb image values in the range 0,255 using 16 > bins per component color. > > on a 640x480 image, it executes in 0.3 seconds vs 4.5 seconds for a for > loop. > > not quite framerate, but good enough for prototyping. >
I don't think your copy to temp is necessary, and use reshape(-1,3) as in the example of Stefan, which will avoid copying the array 3 times. If you need to gain some more speed, then rewriting histogramdd and removing some of the unnecessary checks and calculations looks possible. Josef _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
