Python wrappers for vlfeat quickshift

Finally I got around to wrap vlfeats quickshift features to python.
These can be used to easily build (hierarchical) segmentations or superpixels in images. They can also be used for other clustering tasks but this was the main goal.
You can find my wrappers on github.
If you want, you can me.

I build upon mmmikaels python wrappers and upgraded to vlfeat 0.9.9.
I didn't see if the compiling problems I addressed earlier are still present in this version but I'll check it and try to fix it in my branch.

I am planing to use this together with the sift features for some superpixel and bow based image segmentation.

Before that I used Turbo Pixels by Alex Levinshtein.

Maybe I will write some python wrappers for his Matlab code, too.

Also I just found a brand new paper on TurboPixels, called TurboPixel Segmentation Using Eigen-Images.
Sounds interesting.
I'll dig into it right now :)


  1. If you use turbopixels, you might want to have a look at this GPU implementation in github:

    You can get around 2-3 fps for 640x480 images, which is abound a 40x speed increase over the original code.

  2. Cool, thanks. I'll definitely have a look!


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