On Tue, Dec 27, 2011 at 8:29 AM, Nadav Horesh <nadavh.horesh@gmail.com>wrote:
How can I get it?
Nadav
The code Stefan mentioned is in an old pull request (PR #16<https://github.com/scikits-image/scikits-image/pull/16>). That PR is from before the switch from scikits.image to skimage. I've made a new branch<https://github.com/tonysyu/scikits-image/commits/skimage-convolution>in my git repo with the convolution code in the new namespace. If you're already running skimage from git, then you can use git to clone this branch: git remote -f add tonysyu git@github.com:tonysyu/scikits-image.git git checkout -b convolution tonysyu/skimage-convolution In case this isn't familiar: The first line adds my git repo to your list of remotes, and the "-f" flag fetches the tags from my repo (this ensures that you have the info about my branches). My repo is now added to your repo as a remote with the name "tonysyu" (you can change this). The second line creates a new branch "convolution", clones my "skimage-convolution" branch into it, and checks it out. Hope that helps, -Tony
2011/12/23 Stéfan van der Walt <stefan@sun.ac.za>
The application is not too sophisticated, and I do use numpy, scipy and skimage for all I need. The only problem is speed, I need the
On Thu, Dec 22, 2011 at 10:44 PM, Nadav Horesh <nadavh.horesh@gmail.com> wrote: processing to
be at l5-10 time faster. Convolutions take most of the processing time. I prefer a flexible solution that would speed up also common nonlinear filters (i.e. a median filter).
We have a PR in the pipeline for doing really, really fast convolutions... but it needs a bit of work. Would you like to have a look at it?
Stéfan