Hi guys,
I got a bit of time meanwhile in a conference:
https://github.com/glemaitre/bow-sklearn-example
The extraction is in the source. I have to include the part to measure the
timing. Let me know of that make sense.
Cheers,
On 23 February 2016 at 20:39, Nadim Farhat <nadim.far...@gmail.com> wrote:
> HI Andreas,
>
> Sorry for Jumping into the conversation and getting a bit off topic, what
> does it mean "flat data" sets in sklearn ?
>
> Bests
>
> Nadim Farhat
> Phd Bioengineering candidate
> Center for Ultrasound and therapeutics
> University of Pittsburgh
>
>
> On Mon, Feb 22, 2016 at 12:12 PM Andreas Mueller <t3k...@gmail.com> wrote:
>
>> Hi Guillaume.
>>
>> I was a big user of BoW myself, but I don't think it should go into
>> scikit-learn.
>> BoW doesn't really operate on a "flat" dataset, as scikit-learn usually
>> does. It works on groups of data points.
>> Each sample is usually a concatenation of feature vectors, which you
>> summarize as a histogram.
>> That doesn't really fit into the scikit-learn API.
>>
>> For any particular application (I did bag of visual words), creating an
>> implementation using the kmeans or sparse coding in scikit-learn
>> is only a couple of lines (you can find my visual bow for per-superpixel
>> descriptors here
>> https://github.com/amueller/segmentation/blob/master/bow.py#L184)
>>
>> Cheers,
>> Andy
>>
>>
>>
>> On 02/14/2016 09:03 PM, Guillaume Lemaître wrote:
>>
>> Dear all,
>>
>> My group and I, are currently working on image classification applied to
>> medical images. We are using the Bag-of-Features (or Bag-of-Visual-Words,
>> Bag-of-Words) which was inspired originally from the text classification.
>> In fact, we have a kind of dirty implementation [here](
>> <https://github.com/glemaitre/protoclass/blob/master/protoclass/extraction/codebook.py>
>> https://github.com/glemaitre/protoclass/blob/master/protoclass/extraction/codebook.py)
>> which I would like to, somehow, even only if it is for a personal branch,
>> integrate to the scikit-learn.
>>
>> However, I have some philosophical questions before to mess around, which
>> in fact are feeding some discussions in our lab. Checking the API, the BoF
>> approach could be part of the `feature_extraction` module. BoF is really
>> similar to the implementation of the BoW for text as previously mentioned.
>>
>> Nevertheless, I am questioning if the BoF shall rather not be integrated
>> to the `decomposition` module. By looking at it, the method consists of:
>> (i) dictionary learning (base K-Means, Mean-Shift, etc.), (ii) encoding (or
>> voting in that case using k-NN), and (iii) pooling (histogram).
>>
>> Thus, in some sort the BoF can be seen as any of the decomposition (even
>> more similar to sparse coding). For instance the sparse learning follow
>> exactly the same scheme: dictionary learning with K-SVD, encoding, and
>> pooling (min/max/etc.). Similar thing for PCA, if you tackle the problem of
>> dictionary as finding the eigenvectors/eigenvalues.
>>
>> My questions are thus the following:
>> - what are you thinking about such thing;
>> - where the BoF implementation of this approach is the most judicious;
>> - would it be judicious to think about the different decomposition
>> methods as the three steps earlier mentioned or it would be not at all
>> intuitive?
>>
>> Hope that the topic is not to weird.
>>
>> Cheers,
>> --
>>
>>
>>
>>
>> *LEMAÎTRE Guillaume PhD Candidate MSc Erasmus Mundus ViBOT
>> (Vision-roBOTic) MSc Business Innovation and Technology Management *
>> <g.lemaitr...@gmail.com>g.lemaitr...@gmail.com
>>
>> *ViCOROB - Computer Vision and Robotic Team*
>> Universitat de Girona, Campus Montilivi, Edifici P-IV 17071 Girona
>> Tel. +34 972 41 98 12 - Fax. +34 972 41 82 59
>> <http://vicorob.udg.es/>http://vicorob.udg.es/
>>
>> *LE2I - Le Creusot *IUT Le Creusot, Laboratoire LE2I, 12 rue de la
>> Fonderie, 71200 Le Creusot
>> Tel. +33 3 85 73 10 90 - Fax. +33 3 85 73 10 97
>> <http://le2i.cnrs.fr>http://le2i.cnrs.fr
>>
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--
*LEMAÎTRE GuillaumePhD CandidateMSc Erasmus Mundus ViBOT
(Vision-roBOTic)MSc Business Innovation and Technology Management*
g.lemaitr...@gmail.com
*ViCOROB - Computer Vision and Robotic Team*
Universitat de Girona, Campus Montilivi, Edifici P-IV 17071 Girona
Tel. +34 972 41 98 12 - Fax. +34 972 41 82 59
http://vicorob.udg.es/
*LE2I - Le Creusot*IUT Le Creusot, Laboratoire LE2I, 12 rue de la Fonderie,
71200 Le Creusot
Tel. +33 3 85 73 10 90 - Fax. +33 3 85 73 10 97
http://le2i.cnrs.fr
https://sites.google.com/site/glemaitre58/
Vice - Chairman of A.S.C. Fours UFOLEP
Chairman of A.S.C. Fours FFC
Webmaster of http://ascfours.free.fr
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