algorithms-for-computing-line-estimators/LinearRegressionTool/src/main/java/de/wwwu/awolf/presenter/evaluation/PictureProcessor.java

package de.wwwu.awolf.presenter.evaluation;

import de.wwwu.awolf.model.Line;
import de.wwwu.awolf.model.communication.Data;
import de.wwwu.awolf.model.communication.SubscriberType;
import de.wwwu.awolf.model.communication.TypeData;
import de.wwwu.awolf.presenter.Presenter;
import de.wwwu.awolf.presenter.util.Logging;
import org.opencv.core.*;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;

import javax.swing.*;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.io.File;
import java.util.ArrayList;
import java.util.concurrent.Flow;

/**
 * Implementierung verschiedener Algorithmen zur Berechnung von Ausgleichsgeraden.
 *
 * @Author: Armin Wolf
 * @Email: a_wolf28@uni-muenster.de
 * @Date: 17.09.2017.
 */
public class PictureProcessor implements Flow.Publisher<Data> {

    private Mat image;
    private Mat contour;
    private Presenter presenter;
    private File file;
    private ArrayList<MatOfPoint> contours;
    private double contourLength;
    private Flow.Subscriber<? super Data> subscriber;

    /**
     * Konstruktor
     *
     * @param presenter Presenter
     * @param file      Bilddatei
     */
    public PictureProcessor(Presenter presenter, File file) {
        this.file = file;
        this.presenter = presenter;
        subscribe(presenter);
    }

    /**
     * startet den Import des Bild und die Vorverarbeitung
     */
    public void run() {
        image = Imgcodecs.imread(file.getAbsolutePath());
        contour = process(image);
        contourLength = image.width() * 0.3;
        createInputData();
    }

    /**
     * Vorverarbeitung des Eingabebilds. Dabei wird auf verschiedene OpenCV Methoden zurückgegriffen.
     *
     * @param image Eingabebild
     * @return Matrix representation des Bilds
     */
    private Mat process(Mat image) {
        Mat threshold = new Mat(image.width(), image.height(), CvType.CV_8UC1);
        Mat source = new Mat(image.width(), image.height(), CvType.CV_8UC1);
        Imgcodecs.imwrite(file.getAbsolutePath().substring(0, file.getAbsolutePath().lastIndexOf(".")) + "-orig.png", image);
        Imgproc.cvtColor(image, source, Imgproc.COLOR_BGR2GRAY);
        Imgcodecs.imwrite(file.getAbsolutePath().substring(0, file.getAbsolutePath().lastIndexOf(".")) + "-Greyscale.png", source);
        Imgproc.GaussianBlur(source, threshold, new Size(3, 3), 0, 0);
        Imgproc.Canny(threshold, source, 300, 600, 5, true);
        Imgcodecs.imwrite(file.getAbsolutePath().substring(0, file.getAbsolutePath().lastIndexOf(".")) + "-Canny.png", source);
        //Konturen berechnen und filtern
        contours = new ArrayList<>();
        Imgproc.findContours(source, contours, new Mat(), Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE, new Point(0, 0));
        Mat viscont = new Mat(source.size(), source.type());
        double minArea = 50;
        double maxArea = 0.2 * image.cols() * image.rows();
        for (int i = 0; i < contours.size(); i++) {
            double acutualArea = Imgproc.contourArea(contours.get(i));
            if (minArea < acutualArea && maxArea > acutualArea) {
                Imgproc.drawContours(viscont, contours, i, new Scalar(255, 0, 0), 1);
            }
        }
        Imgcodecs.imwrite(file.getAbsolutePath().substring(0, file.getAbsolutePath().lastIndexOf(".")) + "-Contour.png", viscont);
        Mat resized = new Mat();
        Imgproc.resize(viscont, resized, new Size(560, 560));
        SwingUtilities.invokeLater(() -> {
            JDialog dialog = new JDialog();
            dialog.setSize(560, 560);
            JLabel label = new JLabel();
            label.setSize(560, 560);
            label.setIcon(new ImageIcon(toBufferedImage(resized)));
            dialog.add(label);
            dialog.setVisible(true);
        });
        return viscont;
    }

    /**
     * Das Bild wird passend umgewandelt, um im nächsten Schritt visualisiert werden zu können.
     *
     * @param m Matrix representation des Bilds
     * @return visualisierbares Bild
     */
    private BufferedImage toBufferedImage(Mat m) {
        int type = BufferedImage.TYPE_BYTE_GRAY;
        if (m.channels() > 1) {
            type = BufferedImage.TYPE_3BYTE_BGR;
        }
        int bufferSize = m.channels() * m.cols() * m.rows();
        byte[] b = new byte[bufferSize];
        m.get(0, 0, b); // get all the pixels
        BufferedImage image = new BufferedImage(m.cols(), m.rows(), type);
        final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
        System.arraycopy(b, 0, targetPixels, 0, b.length);
        return image;

    }

    /**
     * Das gefilerte Bild ist bereit ins Modell aufgenommen zu werden um darauf dann die Algorithmen laufen zu lassen.
     */
    private void createInputData() {
        Thread t = new Thread(() -> {
            double minArea = 50;
            double maxArea = 0.2 * image.cols() * image.rows();
            int id = 0;
            for (int j = 0; j < contours.size(); j++) {
                Point[] p = contours.get(j).toArray();
                double acutualArea = Imgproc.contourArea(contours.get(j));
                if (minArea < acutualArea && maxArea > acutualArea) {
                    for (int i = 0; i < p.length; i++) {
                        Line line = new Line(-1 * (500 - p[i].x), p[i].y);
                        line.setId("" + id++);
                        presenter.getModel().getLines().add(line);
                    }
                }
            }

            TypeData data = new TypeData();
            data.setType(SubscriberType.PICTURE);
            this.subscriber.onNext(data);
        });
        t.start();
        try {
            t.join();
        } catch (InterruptedException e) {
            Logging.logError(e.getMessage(), e);
            Thread.currentThread().interrupt();
        }
    }

    @Override
    public void subscribe(Flow.Subscriber<? super Data> subscriber) {
        this.subscriber = subscriber;
    }
}