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package org.opencv.test.ml;
import org.opencv.ml.Ml;
import org.opencv.ml.SVM;
import org.opencv.core.Mat;
import org.opencv.core.MatOfFloat;
import org.opencv.core.MatOfInt;
import org.opencv.core.CvType;
import org.opencv.test.OpenCVTestCase;
import org.opencv.test.OpenCVTestRunner;
public class MLTest extends OpenCVTestCase {
public void testSaveLoad() {
Mat samples = new MatOfFloat(new float[] {
5.1f, 3.5f, 1.4f, 0.2f,
4.9f, 3.0f, 1.4f, 0.2f,
4.7f, 3.2f, 1.3f, 0.2f,
4.6f, 3.1f, 1.5f, 0.2f,
5.0f, 3.6f, 1.4f, 0.2f,
7.0f, 3.2f, 4.7f, 1.4f,
6.4f, 3.2f, 4.5f, 1.5f,
6.9f, 3.1f, 4.9f, 1.5f,
5.5f, 2.3f, 4.0f, 1.3f,
6.5f, 2.8f, 4.6f, 1.5f
}).reshape(1, 10);
Mat responses = new MatOfInt(new int[] {
0, 0, 0, 0, 0, 1, 1, 1, 1, 1
}).reshape(1, 10);
SVM saved = SVM.create();
assertFalse(saved.isTrained());
saved.train(samples, Ml.ROW_SAMPLE, responses);
assertTrue(saved.isTrained());
String filename = OpenCVTestRunner.getTempFileName("yml");
saved.save(filename);
SVM loaded = SVM.load(filename);
assertTrue(saved.isTrained());
}
}
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