ttest wrote: > Hello, > > I'm working on an image processing project using the Python Imaging > Library along with numpy. Right now, I'm trying to build a speedy > script for converting whole images between the RGB and the HSV (a.k.a. > HSB) color spaces. Unfortunately, the code I've made so far runs > dreadfully slow with even moderate-sized images. > > I'm under the impression that the crux of the problem is the fact that > PIL's point method operates on only one band at a time, and to do a > proper color space conversion, you need information about all three > bands in a particular problem. This has forced me to do an awkward > work-around where the image data is loaded into a numpy array > (1600x1200x3), and a dinky for-loop run runs through the array picking > up RGB values, converting to HSV, and dumping the results back into > another array. > > How can I make this more efficient?
Reimplement colorsys.rgb_to_hsv() such that it operates on arrays instead of scalars. Only minor modifications are necessary. -- 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 -- http://mail.python.org/mailman/listinfo/python-list
