svm train (fail saving)

/*public static void main(String args[]){
        SVM svm = SVM.create();
        HOGDescriptor hog = new HOGDescriptor(new Size(64, 128), new Size(16, 16), new Size(8, 8), new Size(8, 8), 9);
        Mat vector = new Mat();
        Mat label = new Mat();
        int dim = 0;
        for (int i=0; i<100; i++){
            Mat img = Imgcodecs.imread("/Users/Clive/Desktop/trainHOG-master/pos/"+i+".png");
            MatOfFloat factor = new MatOfFloat();
            MatOfPoint locations =new MatOfPoint();
            hog.compute(img, factor, new Size(64, 128), new Size(8, 8), locations);
            if (i == 0){
                dim = factor.toArray().length;
                vector = Mat.zeros(200, dim, CvType.CV_32FC1);
                label = Mat.zeros(200, 1, CvType.CV_32SC1);
            }
            for (int j=0; j<dim; j++){
                vector.put(i, j, factor.toArray()[j]);
            }
            label.put(i, 0, 1);
        }
        for (int i=0; i<100; i++){
            Mat img = Imgcodecs.imread("/Users/Clive/Desktop/trainHOG-master/neg/"+i+".png");
            MatOfFloat factor = new MatOfFloat();
            MatOfPoint locations =new MatOfPoint();
            hog.compute(img, factor, new Size(64, 128), new Size(8, 8), locations);
            for (int j=0; j<dim; j++){
                vector.put(i+100, j, factor.toArray()[j]);
            }
            label.put(i+100, 0, -1);
        }
        svm.train(vector, Ml.ROW_SAMPLE, label);
        svm.save("data.xml");
        System.out.println("Done!");
        
    }*/