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GPU accelerated cascade classifier training, is it in the pipeline? Anyone has tried this before?

asked 2013-11-20 02:37:00 -0600

updated 2013-11-21 06:08:18 -0600

I was wondering, if there is an intention of creating a GPU powered pipeline or a decent multicore powered pipeline for object model training using the cascade classification interface. For now my knowledge of the CUDA language is too poor to actually consider implementing it myself, but it could be a future project.

I think that this could push the training of actual object models alot, seeing that recent publications succeed in training decent models in less than a day.

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answered 2014-01-30 09:37:44 -0600

kazeka gravatar image

updated 2014-02-05 08:26:43 -0600

This is done at least since 2.4.7. If you build OpenCV with CUDA flags with driver installed, opencv_traincascade will use CUDA:

$ otool -L bin/opencv_traincascade
    @rpath/libcudart.5.5.dylib (compatibility version 0.0.0, current version 5.5.28)
    @rpath/libcublas.5.5.dylib (compatibility version 0.0.0, current version 5.5.28)
    @rpath/libcufft.5.5.dylib (compatibility version 0.0.0, current version 5.5.28)
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I am wondering if you have any idea about what is actually optimized with CUDA? Because the actual longest part is looking for relevant negative windows, which is a sequential part of the code as far as I get it. The actual training is small compared to the time for looking for samples.

StevenPuttemans gravatar imageStevenPuttemans ( 2014-01-31 01:41:17 -0600 )edit

I think you're right - after looking at it some more, there is not much speed difference between training with CUDA on and off, at least as of today's master branch.

kazeka gravatar imagekazeka ( 2014-02-05 08:25:40 -0600 )edit

Like I expected ... feel free to implement a multithreaded sample retrieval function :D

StevenPuttemans gravatar imageStevenPuttemans ( 2014-02-05 08:57:31 -0600 )edit

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Asked: 2013-11-20 02:37:00 -0600

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Last updated: Feb 05 '14