[JAVA] Bureau: OpenCV Subdiv2d Make Delaunay For Face By WebCam

Goal
Test OpenCV Subdiv2d Make Delaunay For Face By WebCam.

OpenCV_Subdiv2dMakeDelaunayForFaceByWebCam.java


import javax.swing.JFrame;
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfFloat6;
import org.opencv.core.MatOfInt;
import org.opencv.core.MatOfPoint2f;
import org.opencv.core.MatOfRect;
import org.opencv.core.Point;
import org.opencv.core.Rect;
import org.opencv.core.Scalar;
import org.opencv.imgproc.Imgproc;
import org.opencv.imgproc.Subdiv2D;
import org.opencv.objdetect.CascadeClassifier;
import org.opencv.videoio.VideoCapture;

public class OpenCV_Subdiv2dMakeDelaunayForFaceByWebCam {
    static {
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
    }
    public static void main(String arg[]) {
        VideoCapture capture = new VideoCapture();
        capture.open(0);
        JFrame frame1 = new JFrame("show image");
        frame1.setTitle("Mesure de la division fine du corps humain");
        frame1.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        frame1.setSize(640, 480);
        frame1.setBounds(0, 0, frame1.getWidth(), frame1.getHeight());
        Panel panel1 = new Panel();
        frame1.setContentPane(panel1);
        frame1.setVisible(true);

        int CenterX=304;
        int CenterY=276;

        //Épée humaine(œil,nez,sourcil,Le bec)68 關 clé 點 coordonnées
        float[][] faceData={
                {207, 242},
                {210, 269},
                {214, 297},
                {220, 322},
                {229, 349},
                {243, 373},
                {261, 394},
                {282, 412},
                {308, 416},
                {334, 408},
                {356, 388},
                {374, 367},
                {388, 344},
                {397, 319},
                {403, 291},
                {405, 263},
                {408, 235},
                {221, 241},
                {232, 225},
                {250, 219},
                {270, 219},
                {289, 223},
                {320, 222},
                {339, 216},
                {358, 215},
                {375, 220},
                {387, 233},
                {304, 240},
                {304, 259},
                {304, 277},
                {304, 296},//center
                {281, 311},
                {292, 312},
                {303, 314},
                {315, 310},
                {326, 307},
                {243, 247},
                {254, 240},
                {266, 239},
                {276, 245},
                {266, 247},
                {254, 249},
                {332, 243},
                {343, 236},
                {356, 236},
                {367, 242},
                {356, 245},
                {344, 245},
                {263, 346},
                {278, 341},
                {293, 336},
                {303, 340},
                {315, 335},
                {331, 338},
                {348, 342},
                {332, 353},
                {318, 360},
                {305, 362},
                {294, 361},
                {279, 356},
                {270, 347},
                {293, 347},
                {304, 348},
                {316, 345},
                {342, 343},
                {316, 345},
                {304, 348},
                {294, 347}
        };



        if (!capture.isOpened()) {
            System.out.println("Error");
        } else {
            Mat webcam_image = new Mat();
            capture.read(webcam_image);
            frame1.setSize(webcam_image.width() + 10,webcam_image.height() + 20);

            CascadeClassifier faceDetector = new CascadeClassifier("D:\\projects\\Java\\opencv\\build\\etc\\haarcascades\\haarcascade_frontalface_alt.xml");
            MatOfRect faceDetections = new MatOfRect();


            while (true) {
                capture.read(webcam_image);
                if( !webcam_image.empty() ){
                    faceDetector.detectMultiScale(webcam_image, faceDetections);
                    for (Rect rect : faceDetections.toArray()) {
                        //Imgproc.rectangle(webcam_image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),new Scalar(0, 255, 0),3);
                        //System.out.println("center="+(rect.x + (int)rect.width/2)+","+(rect.y + (int)rect.height/2));

                        try {

                            //Utilisez Haar+ROI d'adaBoost Defender,Renouvellement 68 點 Conversion de coordonnées
                            int diffX=(rect.x + (int)rect.width/2)-CenterX;
                            int diffY=(rect.y + (int)rect.height/2)-CenterY;

                            float[][] newFace=HandleFaceKeyPoints(faceData,diffX,diffY);



                            //Subdiv2D Triangle de Delaunay-Kaisei

                            MatOfPoint2f obj=new MatOfPoint2f();
                            List<Point> allPoints=new ArrayList<Point>();

                            //System.out.println(faceData[0][0]+","+faceData[0][1]);

                            for(int j=0;j<68;j++){
                                allPoints.add(new Point(newFace[j][0],newFace[j][1]));
                            }
                            Rect rectSubdiv2D=new Rect(0,0,webcam_image.width(),webcam_image.height());
                            Subdiv2D subdiv=new Subdiv2D(rectSubdiv2D);
                            obj.fromList(allPoints);
                            subdiv.insert(obj);

                            MatOfInt idx=new MatOfInt();
                            List<MatOfPoint2f> facetList=new ArrayList<MatOfPoint2f>();
                            MatOfPoint2f facetCenters=new MatOfPoint2f();

                            subdiv.getVoronoiFacetList(idx, facetList, facetCenters);
                            for(int j=0;j<68;j++){
                                Point tmpPoint=allPoints.get(j);

                                Imgproc.circle(webcam_image, tmpPoint,4, new Scalar(0,0,255), -1);
                            }
                            MatOfFloat6 triangleList = new MatOfFloat6();
                            subdiv.getTriangleList(triangleList);
                            //System.out.println(triangleList.dump());

                            for(int j=0;j<triangleList.rows();j++){

                                double dataU=triangleList.get(j, 0)[0];
                                double dataV=triangleList.get(j, 0)[1];
                                double dataW=triangleList.get(j, 0)[2];
                                double dataX=triangleList.get(j, 0)[3];
                                double dataY=triangleList.get(j, 0)[4];
                                double dataZ=triangleList.get(j, 0)[5];
                                Point p1=new Point(dataU,dataV);
                                Point p2=new Point(dataW,dataX);
                                Point p3=new Point(dataY,dataZ);


                                Imgproc.line(webcam_image, p1, p2, new Scalar(64,255,128));
                                Imgproc.line(webcam_image, p2, p3, new Scalar(64,255,128));
                                Imgproc.line(webcam_image, p3, p1, new Scalar(64,255,128));


                                //System.out.println(dataU+","+dataV+","+dataW+","+dataX+","+dataY+","+dataZ);
                            }
                            ///Subdiv2D-e

                        } catch (Exception e) {
                            System.out.println(e);
                        }



                    }

                    System.out.println(String.format("Detected %s faces", faceDetections.toArray().length));




                    panel1.setimagewithMat(webcam_image);
                    frame1.repaint();



                }else{
                    capture.release();
                    break;
                }
            }
        }
    }
    //Méthode de conversion des coordonnées
    public static float[][] HandleFaceKeyPoints(float[][] standard,int shiftX,int shiftY){
        float[][] newFacePoints=new float[68][2];
        for(int i=0;i<68;i++){

            newFacePoints[i][0]=standard[i][0]+shiftX;
            newFacePoints[i][1]=standard[i][1]+shiftY;

        }

        return newFacePoints;

    }

}

Result
![opencv_subdiv2d_make_delaunay_for_face_by_webcam.JPG](https://qiita-image-store.s3.ap-northeast-1.amazonaws.com/0/276243/bcd4ae9a-0bcb-6b61-48e1-0397c5fb7f61.jpeg)

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