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Training new LatentSVMDetector Models.

asked 2013-07-09 03:19:57 -0500


I haven't found any method to train new latent svm detector models using openCV. I'm currently using the existing models given in the xml files, but I would like to train my own.

Is there any method for doing so?

Thank you,


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answered 2013-07-09 11:12:42 -0500

The latent svm training software isnt included in opencv but it is publicly available on the latentsvm website of pedro felzenswalb. Just google for his page and download the code. Compile and build and it will get you started.

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Thank you !

GilLevi gravatar imageGilLevi ( 2013-07-10 03:29:32 -0500 )edit

Thanks, but the code on the latentsvm website of pedro felzenswalb is a matlab code that works only on linux.

Is there any windows c++ alternative?

Thank you, Gil.

GilLevi gravatar imageGilLevi ( 2013-07-10 04:17:29 -0500 )edit

No I have same problem. You will need to port it yourself :)

StevenPuttemans gravatar imageStevenPuttemans ( 2013-07-10 04:23:35 -0500 )edit

Thank you for your help.

have you already ported the code?

I'm having some difficulty with fv_cache and I really don't know how to continue.

will you be king enough to send me the ported version, assuming you already managed to port it?

I'm really stuck trying to port it, as fv_cashe uses a linux function that has no alternative in windows.

Thank you, Gil.

GilLevi gravatar imageGilLevi ( 2013-07-10 04:30:14 -0500 )edit

I started on it some months ago but gave up after looking for windows alternatives for about 5 days for several code parts and snippets. Guess the best is just to install a linux version in dualboot, build your models there and then port the xml files. The files are operating system independant. A collegue took about 2 days to get it completely running in linux.

StevenPuttemans gravatar imageStevenPuttemans ( 2013-07-10 04:51:37 -0500 )edit

Thank you!

GilLevi gravatar imageGilLevi ( 2013-07-14 12:07:46 -0500 )edit
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Asked: 2013-07-09 03:19:57 -0500

Seen: 1,203 times

Last updated: Jul 09 '13