On Thu, Dec 27, 2012 at 2:06 PM, François firstname.lastname@example.org wrote:
I understand that numpy intregrates some basic features and we need some advanced features but I have the feeling that skimages is redoundant with opencv in some ways. What's the position of skimage about that?
Thanks for your question--it's a good one. There are several reasons for a separate project, some of them already highlighted by Emmanuelle. A few years ago, we had to decide whether we wanted to build on top of OpenCV, and the general consensus was that it is too heavy a dependency. We have three aims with `skimage`:
1. Provide a highly Pythonic interface to building blocks for reproducible image processing reseach 2. Have simple, well-written and clear implementations of common algorithms for use in education 3. Provide tools for solving industry problems efficiently
I think OpenCV does number 3 particularly well, while some projects such as SimpleCV take on number 1. But when it comes to education and reproducible research, I believe `skimage` still holds a significant advantage, in terms of the transparency and clarity of the code, as well as the examples provided.
`skimage` plays particularly well with the scipy stack of tools, and I find that the pipelining tools (dtype conversion, color space handling, exposure adjustment, etc.) significantly improve my research productivity.
Your comments and criticisms are most welcome; we are always keen to hear good feedback!