Desktop: OpenCV Scharr Filter

Goal
Test OpenCV Scharr Filter.

OpenCV_ScharrFilter.java


import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;

import javax.swing.*;
import java.awt.*;
import java.awt.event.ActionEvent;
import java.awt.event.ActionListener;
import java.awt.image.BufferedImage;

public class OpenCV_ScharrFilter {

    static {System.loadLibrary(Core.NATIVE_LIBRARY_NAME);}

    private JFrame frmjavaSwing;

    /**
        *   Launch the application.
        */
    public static void main(String[] args){
        EventQueue.invokeLater(new Runnable() {
            @Override
            public void run() {
                try{
                    OpenCV_ScharrFilter window = new OpenCV_ScharrFilter();
                    window.frmjavaSwing.setVisible(true);
                }catch (Exception e){
                    e.printStackTrace();
                }
            }
        });
    }

    /**
        * Create the application.
        */
    public OpenCV_ScharrFilter(){
        init();
    }

    /**
        *   Init the contents of the frame.
        */
    private void init(){
        final Mat src = Imgcodecs.imread(
                "D:\\projects\\Java\\OpenCV_Samples\\resource\\imgs\\lena.jpg ");

        BufferedImage image = matToBufferedImage(src);
        frmjavaSwing = new JFrame();
        frmjavaSwing.setTitle("opencv Sharr filter practice");
        frmjavaSwing.setBounds(100, 100, 560, 620);
        frmjavaSwing.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        frmjavaSwing.getContentPane().setLayout(null);

        final JLabel lblNewLabel = new JLabel("");
        lblNewLabel.setBounds(5, 60, image.getHeight()+10, image.getWidth()+10);
        lblNewLabel.setIcon(new ImageIcon(image));
        frmjavaSwing.getContentPane().add(lblNewLabel);

        JButton btnX = new JButton("Horizontal theory");
        btnX.addActionListener(new ActionListener() {
            public void actionPerformed(ActionEvent arg0) {
                BufferedImage newImage=matToBufferedImage(Convolution(src,1));
                lblNewLabel.setIcon(new ImageIcon(newImage));
            }
        });
        btnX.setBounds(42, 10, 114, 23);
        frmjavaSwing.getContentPane().add(btnX);

        JButton btnY = new JButton("Vertical theory");
        btnY.addActionListener(new ActionListener() {
            public void actionPerformed(ActionEvent arg0) {
                BufferedImage newImage=matToBufferedImage(Convolution(src,2));
                lblNewLabel.setIcon(new ImageIcon(newImage));
            }
        });
        btnY.setBounds(211, 10, 102, 23);
        frmjavaSwing.getContentPane().add(btnY);
    }

    public Mat Convolution(Mat source,int type){
        Mat kernel =new Mat(3,3, CvType.CV_32F);
        if (type==1){


            kernel.put(0, 0, new float[]{-3,-10,-3});
            kernel.put(1, 0, new float[]{0,0,0});
            kernel.put(2, 0, new float[]{3,10,3});
        }else if (type==2){

            kernel.put(0, 0, new float[]{-3,0,3});
            kernel.put(1, 0, new float[]{-10,0,10});
            kernel.put(2, 0, new float[]{-3,0,3});

        }
        Mat destination=new Mat(source.rows(),source.cols(),source.type());
        Imgproc.filter2D(source, destination, -1, kernel);
        return destination;

    }

    public BufferedImage matToBufferedImage(Mat matrix) {
        int cols = matrix.cols();
        int rows = matrix.rows();
        int elemSize = (int)matrix.elemSize();
        byte[] data = new byte[cols * rows * elemSize];
        int type;
        matrix.get(0, 0, data);
        switch (matrix.channels()) {
            case 1:
                type = BufferedImage.TYPE_BYTE_GRAY;
                break;
            case 3:
                type = BufferedImage.TYPE_3BYTE_BGR;
                // bgr to rgb
                byte b;
                for(int i=0; i<data.length; i=i+3) {
                    b = data[i];
                    data[i] = data[i+2];
                    data[i+2] = b;
                }
                break;
            default:
                return null;
        }
        BufferedImage image2 = new BufferedImage(cols, rows, type);
        image2.getRaster().setDataElements(0, 0, cols, rows, data);
        return image2;
    }
}
Result
![opencv_scharr_filter.JPG](https://qiita-image-store.s3.ap-northeast-1.amazonaws.com/0/276243/1516c3c0-f50a-108e-d5e2-457f86852321.jpeg)

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