opencv_win_ann4.java

package opencvapp;
import org.opencv.core.Core;
import static org.opencv.core.CvType.CV_32F;
import static org.opencv.core.CvType.CV_8U;
import org.opencv.core.Mat;
import org.opencv.core.TermCriteria;
import org.opencv.ml.ANN_MLP;
import org.opencv.ml.Ml;

public class OpenCVApp {
    public static void main(String[] args) {
        System.load("D:\\Opencv-4.1.0-vc14_vc15\\opencv\\build\\java\\x64\\" + Core.NATIVE_LIBRARY_NAME + ".dll");
        double[][] XORTrainArray = {
            {0.0, 0.0},
            {0.0, 1.0},
            {1.0, 0.0},
            {1.0, 1.0}
        };
        Mat XORTrain = new Mat(4, 2, CV_32F);
        XORTrain.put(0, 0, XORTrainArray[0]);
        XORTrain.put(1, 0, XORTrainArray[1]);
        XORTrain.put(2, 0, XORTrainArray[2]);
        XORTrain.put(3, 0, XORTrainArray[3]);
        System.out.println("Train Inputs : \n" + XORTrain.dump());

        double[][] XORTrainOutArray = {
            {0.0},
            {1.0},
            {1.0},
            {0.0}
        };
        Mat XORTrainOut = new Mat(4, 1, CV_32F);
        XORTrainOut.put(0, 0, XORTrainOutArray[0]);
        XORTrainOut.put(1, 0, XORTrainOutArray[1]);
        XORTrainOut.put(2, 0, XORTrainOutArray[2]);
        XORTrainOut.put(3, 0, XORTrainOutArray[3]);
        System.out.println("Train Labels : \n" + XORTrainOut.dump());

        ANN_MLP ANN = ANN_MLP.create();

        Mat layerSizes = new Mat(3, 1, CV_8U);
        layerSizes.put(0, 0, 2);
        layerSizes.put(1, 0, 2);
        layerSizes.put(2, 0, 1);
        ANN.setLayerSizes(layerSizes);
        System.out.println("Layers Sizes : \n" + layerSizes.dump());

        ANN.setActivationFunction(ANN_MLP.SIGMOID_SYM);
        ANN.setTrainMethod(ANN_MLP.BACKPROP);

        TermCriteria criteria = new TermCriteria(TermCriteria.EPS + TermCriteria.COUNT, 10000, 0.00000001);
        ANN.setTermCriteria(criteria);
        
        ANN.train(XORTrain, Ml.ROW_SAMPLE, XORTrainOut);
        System.out.println("Model is trained? " + ANN.isTrained());

        Mat input_weights = ANN.getWeights(0);
        Mat hidden_weights = ANN.getWeights(1);
        Mat output_weights = ANN.getWeights(2);
        System.out.println("Input Layer Weights : \n" + input_weights.dump());
        System.out.println("Hidden Layer Weights : \n" + hidden_weights.dump());
        System.out.println("Output Layer Weights : \n" + output_weights.dump());

        try{
            ANN.save("OpenCV_ANN_XOR.yml");
            System.out.println("Model Saved Successfully.");
        } catch(Exception ex) {
            System.err.println("Error Saving Model.");
        }
    }
}