Hi Mael, thanks for all these contributions! I had a look at the new filters. I added some documentation to the existing docstrings (http://github.com/emmanuelle/scikits.image/commits/denoise), could you please check that I didn't write anything wrong? I'm planning to add tests for these denoising functions in the next few days. After the code is fully tested, I think it will be time to start to start a new branch, cherry-pick the commits corresponding to the denoising algorithms only, rebase... and ask for a merge. It's important to make sure that your work can be re-used into the main branch. As you seem to have plenty of new stuff (the viewer for example) to keep you busy, I can take care of this refactoring if you like. Concerning the tutorial, I couldn't make the demos run. I understood that Mathjax had to be installed, but the installation instructions of Mathjax did not appear very clear to me, so I did not really know where I should put it. So I guess I will also wait for some documentation from your side. The idea of an interactive tutorial that explains the algorithms and let the user execute some demo is really cool, however! Do you plan to have the tutorial on a single web server, or that users run it on their own computer? In the first case, you may use any kind of top-notch not-so-standard software such as Mathjax, but if every user has to install it, it will be more of a problem... In any case, I'm eager to know more about this tutorial project! Finally, for the viewer, I had to make a small addition to the setup.py to install the package (see my comment on github, I needed to specify the location of numpy headers). I was glad to see that you were able to code some of the features that Lionel and you really need, such as being able to flip between two images, or representing the level lines of an image. However, I know almost nothing about visualization, so I'm afraid I don't have very constructive comments about the viewer. Maybe just one remark: as a lot of scientists work interactively within the Python shell, e.g. Ipython, it is important that calls to the viewer are not blocking, i.e., that the user gets the prompt back. Cheers, Emmanuelle On Wed, Oct 27, 2010 at 01:43:42PM -0700, mael wrote:
Hello,
I had lots of things to do lately, haven't had much time to work on the library, but I'll do it quickly,
here are the new things: http://github.com/maelp/scikits.image (some new filters, and some nice zooms)
here are other projects that I work on in parallel, and I'd be happy to have some contribution: - image viewer: this should become the image viewer of scikits.image in our opinion (although it is not yet complete). Basically, it is a modulable efficient viewer, that handles zoom properly, displays level lines, etc and should be easily extensible. This is only a stub yet, and I'd be happy to merge it with your viewer, in particular have the threaded computations to have faster computations, and add the histrograms, normalization, etc. It can show grey and color int / float images, and should be pretty fast even for large images since it only computes the strictly required part that is needed to be viewed, and has a cache to speed-up the next recomputations (if you move the view a little, most of the rendered image does not change, and it only recomputes what needs be )
- tutorial: http://github.com/maelp/tutorial This should become a standard way to describe scikits.image algorithms in a dynamic way (this is basically the Qt Webkit that has been extended to include scikits.image algorithm) This could be a good advantage of the library: it is often difficult to find interactive use-case for algorithms, etc, and many times, old algorithms aren't properly documented, or we don't know in which case they do and don't apply. If we have a standard "documentation" in interactive format (where people can try our algorithms, have a mathematical presentation, upload their images etc) this will help keep up with a large image library. I made it such that it is visually attractive because I'm pretty sure this is extremely important (have beautiful documentation )
I will add new filters to the library soon, please give some inputs on the new projects and feel free to extend and/or modify anything
I haven't had time to properly document everything yet, I'll do that soon