Awesome effort! ;) Is it maybe worth, during the refactor, to evaluate how NDimage could be supportive for auto-parallelization? I’m thinking that it somehow would be able to split off into embarrassingly parallel n tasks, if thrown to a n-core machine?
I’m sorry if I talk non-sense, I’m just fighting to get GLCM faster, when running it via “generic_filter” over large-ish images, so far not successful, even trying to use numba, but as many things are already running in Cython, so I guess I can’t expect much auto-improvements. ;) So, I’m anticipating to have to go to a cluster for my hundreds of images I want to run multiple/many GLCM analyses on. Thanks again for the developer docs, they are great! Regards, Michael > On Jun 27, 2017, at 09:06, Stefan van der Walt <stef...@berkeley.edu> wrote: > > On Tue, Jun 27, 2017, at 07:49, Egor Panfilov wrote: >> - Not sure that I'll find enough time to contribute to the code by myself, >> but it won't harm if you could provide to the public some directions on >> where to start with `scipy.ndimage` C-code. > > Making ndimage developer notes along the way would be extremely helpful! > > Stéfan > > _______________________________________________ > scikit-image mailing list > scikit-image@python.org > https://mail.python.org/mailman/listinfo/scikit-image _______________________________________________ scikit-image mailing list scikit-image@python.org https://mail.python.org/mailman/listinfo/scikit-image
