Relation with computer vision and machine learning

[LI Wei]

Hi Andy:

Thanks for your comments. Seems I am not quite clear about the scope of
skimage and scikits-learn currently. I will get myself more familiar with
both packages to find anything currently in skimage requires the overlap
with scikits-learn's methods.

For MRF, I think your comments are correct. It is just related to some
specific forms(if not one) of MRFs and to solve it is the main problem.
Maybe a complete functioning MRF package is not quite necessary and not
suitable/efficient enough to do the image tasks.

Could I ask why rbm will not be in both packages? I see you release a RBM
on your blog, and why not make it into scikits-learn. Seems it is a
big-package itself and some python libarary like theano has been relaesed,
maybe this is the concern?

Best,
Wei

On Fri, Jul 27, 2012 at 6:02 AM, Andreas Mueller
<amueller at ais.uni-bonn.de>wrote:

>  Hi Wei.
>
> Thanks for your reply! I see your great work in scikits-learn and your
> comments are quite useful.
>
>  Thanks :)
>
>  Many will overlap, I think we can maintain a list. As a quick example in
> the following:
>
> There is no discussion that machine learning methods are helpful for
> vision problems and that vision problems
> are an important application domain for machine learning tools.
>
> The question is if there is something you would like in skimage that would
> require the use of something from sklearn.
> I.e. what algorithm you want in skimage is only useful together with
> something from sklearn?
> I don't think any of your examples are in this category. Which is well
> enough, since this means
> it should be easy to keep the two things separate ;)
>
> Btw, MRFs in vision are often not learned, so this is no ML, just
> optimization. And I would rather place
> that in skimage, as it is quite image specific. When I talked about
> graph-cuts, that's what I meant.
> Normalized cuts are of limited use in low level vision since they are very
> slow for superpixels.
> I was rather thinking of Boykov-Kolmogorov push-relabel - which is my next
> project when I get
> my superpixels done. (Stefan actually mentioned he'd like to have it :)
>
> Abour RBMs: I am<http://www.ais.uni-bonn.de/deep_learning/papers/ESANN10_schulz.pdf>
> no <http://www.ais.uni-bonn.de/deep_learning/papers/IJCNN10_mueller.pdf>
> stranger<http://www.ais.uni-bonn.de/%7Eschulz/publications/papers/nips10ws_schulz_mueller_behnke.pdf>to
> them<http://www.ais.uni-bonn.de/%7Eschulz/publications/papers/neurocomp11_schulz_mueller_behnke.pdf>but I would rather not include them in sklearn and definitely not in
> skimage.
>
> Cheers,
> Andy
>
>
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