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Opencv + Hog + SVM... i want to know the recipe please

asked 2015-02-12 06:39:02 -0500

VonTalavang gravatar image

updated 2015-02-17 09:22:47 -0500

I train my SVM and create a vector file:

clasificador = new CvSVM(); clasificador.train_auto(trainingData, classes, new Mat(), new Mat(), params); clasificador.save("asdf.xml");

now am lost... ok, i load the xml file with CVSVM

how i implement the CVSVM with the HogDescriptor ?

This is my LOAD and image analisis. Where "imag" its the captured frame, "clasificador" its a CVSVM, "hog" its a HogDescriptor

private static void buscar_hog_svm() {

    if (clasificador == null) {
        clasificador = new CvSVM();
        clasificador.load(path_vectores);
    }

    Mat img_gray = new Mat();

    Imgproc.cvtColor(imag, img_gray, Imgproc.COLOR_BGR2GRAY);

    hog = new HOGDescriptor(
            _winSize //new Size(32, 16)
            , _blockSize, _blockStride, _cellSize, _nbins);
    MatOfFloat descriptorsValues = new MatOfFloat();
    MatOfPoint locations = new MatOfPoint();
    hog.compute(img_gray,
            descriptorsValues,
            _winSize,
            _padding, locations);
    Mat fm = descriptorsValues;
    float result = clasificador.predict(fm);
}
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please try to explain, where you're stuck now .

berak gravatar imageberak ( 2015-02-12 07:09:38 -0500 )edit

Thanks berak, i use this awesome post HERE to create this trainning.

but i cant use it yet because i get this error:

error: (-209) The sample size is different from what has been used for training in function cvPreparePredictData

I understand the error, but my question is how can i use the trained data with the hog descriptor now.

VonTalavang gravatar imageVonTalavang ( 2015-02-17 09:26:17 -0500 )edit

Mat fm = descriptorsValues.reshape(1,1);

in other words, you have to flatten your prediction Mat to 1d in the same way, as you (hopefully) did during the training.

berak gravatar imageberak ( 2015-02-17 09:54:11 -0500 )edit

i think thats not the problem.

i trained all the project with pos and neg images in 96 X 160 pxl images.

adding some outputs:

System.out.println("tamano descriptorsValues: " + descriptorsValues.size());
    Mat fm = descriptorsValues;

    System.out.println("tamano fm: " + fm.size());

    float result = clasificador.predict(fm);

i get this:

tamano descriptorsValues: 1x581256

tamano fm: 1x581256

I dont get it... i should create a LARGE descriptor mat ( captured frame )... to be compared with a smaller one mat of 1x (96*160) ??

so there i get this error. Am missing some concepts may be ?

i almost forgot... all images trained in 1D matrix of 1 x (nm) with reshape 1,1

VonTalavang gravatar imageVonTalavang ( 2015-02-17 11:25:11 -0500 )edit

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answered 2015-02-24 09:46:49 -0500

VonTalavang gravatar image

Ok, i found the solution here

You just have to create 2 folders for pos images and neg images. Just keep adding positive and negatives images until the trainning is complete.

Right now... looking for the GPU CUDA version of this.

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Asked: 2015-02-12 06:39:02 -0500

Seen: 746 times

Last updated: Feb 24 '15