On 02/22/2016 12:41 PM, Gael Varoquaux wrote: >> 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) > Any chance that this can go in an example? I guess this depends on > whether we can find a dataset that is simple, yet can illustrate visual > BoWs. > You need a supervised learning datasets, and need to extract features for each image. Not sure how to extract features without skimage, unless we use some sparse coding for that. And that would probably take a long time. I guess the most simple datasets for this would be cifar 10 and caltech 101. And it would probably not run fast enough for a plot example.
------------------------------------------------------------------------------ Site24x7 APM Insight: Get Deep Visibility into Application Performance APM + Mobile APM + RUM: Monitor 3 App instances at just $35/Month Monitor end-to-end web transactions and take corrective actions now Troubleshoot faster and improve end-user experience. Signup Now! http://pubads.g.doubleclick.net/gampad/clk?id=272487151&iu=/4140 _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
