问题描述
我想知道是否有人设法使用Latent SVM Detector的OpenCV实现( http://docs.opencv.org/modules/objdetect/doc/latent_svm.html )成功.有一个示例代码显示了如何利用该库,但问题是该示例代码使用了使用MatLab生成的现成的检测器模型.有人可以指导我完成如何生成自己的探测器模型的步骤吗?
I was wondering if anyone has managed to use the OpenCV implementation of Latent SVM Detector (http://docs.opencv.org/modules/objdetect/doc/latent_svm.html) successfully. There is a sample code that shows how to utilize the library but the problem is that the sample code uses a ready-made detector model that was generated using MatLab. Can some one guide me through the steps on how to generate my own detector model?
推荐答案
LatSVM 具有一个名为pascal
的训练脚本.有一个自述文件,其中包含压缩包,说明了其用法:
The MATLAB implementation of LatSVM by the authors of the paper has a train script called pascal
. There is a README with the tarball explaining its usage:
Using the learning code
=======================
1. Download and install the 2006-2011 PASCAL VOC devkit and dataset.
(you should set VOCopts.testset='test' in VOCinit.m)
2. Modify 'voc_config.m' according to your configuration.
3. Start matlab.
4. Run the 'compile' function to compile the helper functions.
(you may need to edit compile.m to use a different convolution
routine depending on your system)
5. Use the 'pascal' script to train and evaluate a model.
example:
>> pascal('bicycle', 3); % train and evaluate a 6 component bicycle model
The learning code saves a number of intermediate models in a model cache
directory defined in 'voc_config.m'.
有关更多信息,请访问作者网站.该页面还包含此方法的论文.
For more information, visit the authors website. The page also contain the paper of this method.
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