LIBCVD: http://mi.eng.cam.ac.uk/~er258/cvd/ Have you considered LIBCVD as an alternative to OpenCV? It is highly optimized for frame-rate real-time applications but also has a nice, succinct, simple (almost pythonic) syntax. For example, Image<float> img = img_load("lena.png") Image<float> out(img.size()); convolveGaussian(img, out, 3.0); loads an image from a file and convolves a Gaussian with it. LIBCVD's design is very simple: there are only three main classes and its interface is designed to be very functional so it translates from Python very nicely. Most of its dependencies are optional so it compiles very easily. You don't have to use pointers very much in LIBCVD, which eliminates many kinds of bugs--iteration is done with highly optimized and succinct iterators and index operators (e.g. image[y][x]). Best of all, it's very fast. Damian PS: I'm cc'ing Edward Rosten who's the author of LIBCVD. 2009/9/25 Stéfan van der Walt <stefan@sun.ac.za>:
Hi Mike
2009/9/25 Mike Sarahan <msarahan@gmail.com>:
Sorry if I missed this in discussions at the sprint, but is there any reason we're not taking advantage of OpenCV? It may be a little more than what this scikit is aiming to offer, but it has some really nice, well-optimized routines. It's BSD licensed. I have been using the ctypes-opencv python wrapper, which is also BSD licensed.
I know there are two sets of wrappers, but I haven't used either. Do you know their pros and cons?
OpenCV is a fairly heavy dependency, but if it adds good value I see little reason to avoid it.
Regards Stéfan
-- ----------------------------------------------------- Damian Eads Ph.D. Candidate University of California Computer Science 1156 High Street Machine Learning Lab, E2-489 Santa Cruz, CA 95064 http://www.soe.ucsc.edu/~eads