Revision history [back]

if you train your SVM on HOG features, you need those for the prediction, too. (not the actual images)

public static void test() {
    System.out.println("Testing..");
    Mat img = Imgcodecs.imread(new File(FILE_TEST).getAbsolutePath(),0);
    HOGDescriptor d = new HOGDescriptor(new Size(32, 16), new Size(8, 8), new Size(4, 4), new Size(4, 4), 9);
    Mat descriptors = new Mat();
    d.compute(img, descriptors);
    System.out.println(clasificador.predict(descriptors.reshape(1,1)));  
}

if you train your SVM on HOG features, you need those for the prediction, too. (not the actual images)

public static void test() {
    System.out.println("Testing..");
    Mat img = Imgcodecs.imread(new File(FILE_TEST).getAbsolutePath(),0);
    HOGDescriptor d = new HOGDescriptor(new Size(32, 16), new Size(8, 8), new Size(4, 4), new Size(4, 4), 9);
    Mat descriptors = new Mat();
    d.compute(img, descriptors);
    System.out.println(clasificador.predict(descriptors.reshape(1,1)));  
}