Hi, having opencv as a dependency has two important drawbacks for me. First, it makes the installation of the scikit more difficult. Second, the documentation of openCV does not match the standards of numpy/scipy docstrings (no examples, few references to articles). Performance is great, but I think we'll gain more users by putting effort on user-friendliness than if we put it on performance. For examples, a large fraction of my colleagues are using image processing, but on Windows, and they get discouraged by a package with unsufficient documentation. I'm at the Python for Physics day now and I don't have the time to write more, but I'll be glad to continue the discussion later. Cheers, Emmanuelle On Mon, Aug 29, 2011 at 11:25:06AM +0200, St�fan van der Walt wrote:
Hi all,
After merging the GSoC contributions, I think we're in good shape for a next release. Before we get there, however, I'd like to ask your opinions.
Should we declare OpenCV a dependency? There are two sides to this: 1) I want to stop focusing on optimising low-level routines, and instead implement interesting algorithms but 2) OpenCV is quite a big dependency (although it does run on Windows, Linux, Mac etc, comes with built binaries in all of them, and has a permissive BSD license).
Fact is, our manpower is limited, so we should focus on where we can make a difference. My aim is to provide an excellent image processing toolbox for Python that at least covers the MATLAB functionality and more, and to reach that goal with our limited manpower, we need to carefully pick our strategy.
I'd be glad to hear what you have to say.
Regards St�fan