Example usage for org.opencv.core MatOfRect toArray

Introduction

In this page you can find the example usage for org.opencv.core MatOfRect toArray.

Prototype

public Rect[] toArray() 

Source Link

Usage

From source file:Fiji_OpenCV.java

License:Creative Commons License

public void process(int[] pixels) {
    int channels = 3;
    byte[] buf = new byte[pixels.length * channels];
    for (int i = 0; i < pixels.length; i++) {
        buf[i * channels] = (byte) (0x000000ff & (pixels[i]));
        buf[i * channels + 1] = (byte) (0x000000ff & (pixels[i] >>> 8));
        buf[i * channels + 2] = (byte) (0x000000ff & (pixels[i] >>> 16));
    }//w w  w .j  av a  2  s  . c o  m

    Mat image = new Mat(width, height, CvType.CV_8UC3);
    image.put(0, 0, buf);

    // Create a face detector from the cascade file in the resources
    // directory.
    CascadeClassifier faceDetector = new CascadeClassifier(
            getClass().getResource("/opencv/data/haarcascades/haarcascade_frontalface_alt2.xml").getPath());

    // Detect faces in the image.
    // MatOfRect is a special container class for Rect.
    MatOfRect faceDetections = new MatOfRect();
    faceDetector.detectMultiScale(image, faceDetections);

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

    // Draw a bounding box around each face.
    for (Rect rect : faceDetections.toArray()) {
        Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),
                new Scalar(0, 255, 0));
    }

    image.get(0, 0, buf);
    for (int i = 0; i < pixels.length; i++) {
        pixels[i] = 0x80000000 + ((int) (buf[i * channels + 2]) << 16) + ((int) (buf[i * channels + 1]) << 8)
                + ((int) (buf[i * channels + 0]));
    }
    this.ip = new ColorProcessor(width, height, pixels);
}

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From source file:M.java

/**
 * Resize the certain image to required size (WIDTH*HEIGHT).
 *
 * @param imgPath the path of the image.
 * @return the path of the resized image.
 * @throws Exception//from   w w  w .j a  va2  s .  c o  m
 */
public static String resize(String imgPath) throws Exception {
    System.out.println("\nRunning DetectFaceDemo");
    String xmlfilePath = FaceDetector.class.getResource("haarcascade_frontalface_alt.xml").getPath()
            .substring(1);
    System.out.println(xmlfilePath);//test
    CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath);
    //        String imgPath=FaceDetector.class.getResource("cam_img/test.jpg").getPath().substring(1);
    Mat image = Highgui.imread(imgPath);
    System.out.println(imgPath);
    MatOfRect faceDetections = new MatOfRect();
    faceDetector.detectMultiScale(image, faceDetections);
    System.out.println(String.format("Detected %s faces", faceDetections.toArray().length));
    int count = 1;
    String dir = "";
    for (Rect rect : faceDetections.toArray()) {
        ImageFilter cropFilter = new CropImageFilter(rect.x, rect.y, rect.width, rect.height);
        BufferedImage tag = new BufferedImage(rect.width, rect.height, BufferedImage.TYPE_INT_RGB);
        //            File file = new File("build\\classes\\cam_img\\test.jpg");
        File file = new File(imgPath);
        BufferedImage src = ImageIO.read(file);
        Image img = Toolkit.getDefaultToolkit()
                .createImage(new FilteredImageSource(src.getSource(), cropFilter));
        BufferedImage output = new BufferedImage(WIDTH, HEIGHT, BufferedImage.TYPE_INT_RGB);
        Graphics g = output.getGraphics();
        g.drawImage(img, 0, 0, WIDTH, HEIGHT, null);
        g.dispose();
        dir = "img_resized\\cut_image.jpg";
        //            String dir = "trainset\\57-tx\\57-"+(count++)+".jpg";
        File dest = new File(dir);
        ImageIO.write(output, "JPEG", dest);
    }
    return dir;
}

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From source file:M.java

public static String resize(String imgPath, String andrewId, int trainImageCount) throws Exception {
    System.out.println("\nRunning DetectFaceDemo");
    String xmlfilePath = FaceDetector.class.getResource("haarcascade_frontalface_alt.xml").getPath()
            .substring(1);//  w w  w  .  j  a  v a  2 s.c om
    System.out.println(xmlfilePath);//test
    CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath);
    //        String imgPath=FaceDetector.class.getResource("cam_img/test.jpg").getPath().substring(1);
    Mat image = Highgui.imread(imgPath);
    System.out.println(imgPath);
    MatOfRect faceDetections = new MatOfRect();
    faceDetector.detectMultiScale(image, faceDetections);
    System.out.println(String.format("Detected %s faces", faceDetections.toArray().length));
    int count = 1;
    String dir = "";
    for (Rect rect : faceDetections.toArray()) {
        ImageFilter cropFilter = new CropImageFilter(rect.x, rect.y, rect.width, rect.height);
        BufferedImage tag = new BufferedImage(rect.width, rect.height, BufferedImage.TYPE_INT_RGB);
        //            File file = new File("build\\classes\\cam_img\\test.jpg");
        File file = new File(imgPath);
        BufferedImage src = ImageIO.read(file);
        Image img = Toolkit.getDefaultToolkit()
                .createImage(new FilteredImageSource(src.getSource(), cropFilter));
        BufferedImage output = new BufferedImage(WIDTH, HEIGHT, BufferedImage.TYPE_INT_RGB);
        Graphics g = output.getGraphics();
        g.drawImage(img, 0, 0, WIDTH, HEIGHT, null);
        g.dispose();
        int st_no = findLabel("photodb_resized\\", andrewId);
        dir = "photodb_resized\\" + st_no + "-" + andrewId + trainImageCount + ".jpg";
        //            String dir = "trainset\\57-tx\\57-"+(count++)+".jpg";
        File dest = new File(dir);
        ImageIO.write(output, "JPEG", dest);
    }
    return dir;
}

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From source file:attendance_system_adder.cv.image.java

public Mat getFaceDetec(Mat image) {
    Mat face = null;//from  w w w. jav a2  s  . c  o m

    System.out.println("\nRunning DetectFaceDemo");

    CascadeClassifier faceDetector = new CascadeClassifier(".\\resource\\haarcascade_frontalface_default.xml");

    // Detect faces in the image.
    // MatOfRect is a special container class for Rect.
    MatOfRect faceDetections = new MatOfRect();
    faceDetector.detectMultiScale(image, faceDetections);

    //    System.out.println(String.format("Detected %s faces", faceDetections.toArray().length));
    //    // Draw a bounding box around each face.
    for (Rect rect : faceDetections.toArray()) {
        Imgproc.rectangle(image, new Point(rect.x, rect.y),
                new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(255, 0, 0));
        face = new Mat(image, rect);
    }
    //    // Save the visualized detection.
    //    String filename = "faceDetection.png";
    //    System.out.println(String.format("Writing %s", filename));
    //    imwrite(filename, image);
    //FaceRecognizer fr;//= new LBPHFaceRecognizer();
    return face;
}

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From source file:attendance_system_adder.cv.image.java

public Mat FaceDetec(Mat image) {
    Mat face = null;/*from   ww  w  . j  a  v a2  s  .co  m*/

    System.out.println("\nRunning DetectFaceDemo");

    CascadeClassifier faceDetector = new CascadeClassifier(".\\resource\\haarcascade_frontalface_default.xml");

    // Detect faces in the image.
    // MatOfRect is a special container class for Rect.
    MatOfRect faceDetections = new MatOfRect();
    faceDetector.detectMultiScale(image, faceDetections);

    //    System.out.println(String.format("Detected %s faces", faceDetections.toArray().length));
    //    // Draw a bounding box around each face.
    for (Rect rect : faceDetections.toArray()) {
        Imgproc.rectangle(image, new Point(rect.x, rect.y),
                new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(255, 0, 0));

    }
    return image;
}

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From source file:br.com.prj.TelaPrincipal.java

private void btnProcurarActionPerformed(java.awt.event.ActionEvent evt) {//GEN-FIRST:event_btnProcurarActionPerformed

    // remove todos os labels do componente
    jPanel1.removeAll();/*from  w  ww  . jav  a  2  s . com*/

    // reposicionao o primeiro label
    boundX = 12;
    boundY = 22;

    CascadeClassifier faceDetector = new CascadeClassifier(URL_LIB_FACE);

    imagemCarregada = Imgcodecs.imread(selectedFile.getAbsolutePath(), Imgcodecs.CV_LOAD_IMAGE_COLOR);
    // imagem com retangulo dos rostos encontrados
    imagemDest = new Mat(imagemCarregada.rows(), imagemCarregada.cols(), imagemCarregada.type());
    MatOfRect faceDetections = new MatOfRect();
    faceDetector.detectMultiScale(imagemCarregada, faceDetections);

    // tentar verificar se o rect encontrado possui olhos
    Rect[] faceEncontrada = new Rect[faceDetections.toArray().length];
    int i = 0;
    for (Rect rect : faceDetections.toArray()) {

        faceEncontrada[i] = new Rect(new Point(rect.x - PAD_LATERAL + 5, rect.y - PAD_SUPERIOR + 5),
                new Point(rect.x + rect.width + PAD_LATERAL, (rect.y + rect.height + PAD_SUPERIOR) - 5));

        adicionarLabel(convertMatToImage(new Mat(imagemCarregada, faceEncontrada[i])), faceEncontrada[i]);

        //            ADICIONA RETANGULO DO ROSTO NA IMAGEM  
        //            Imgproc.rectangle(imagemDest,
        //                    new Point(rect.x - PAD_LATERAL, rect.y - PAD_SUPERIOR),
        //                    new Point(rect.x + rect.width + PAD_LATERAL, (rect.y + rect.height + PAD_SUPERIOR) - 5),
        //                    new Scalar(0, 255, 0));
        i++;
    }

    if (faceDetections.toArray().length == 0) {
        totalRostos.setText("No foi possvel identificar nenhum rosto na imagem selecionada.");
    } else {
        totalRostos
                .setText("Identificamos " + faceDetections.toArray().length + " rosto(s) na imagem carregada.");
    }

}

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From source file:by.zuyeu.deyestracker.core.detection.detector.BaseDetector.java

protected Rect[] detectWithClassifier(final Mat inputframe, final CascadeClassifier classifier) {
    LOG.debug("detectWithClassifier - start;");

    final Mat mRgba = new Mat();
    final Mat mGrey = new Mat();
    final MatOfRect detectedObjects = new MatOfRect();
    inputframe.copyTo(mRgba);//w  ww  . jav  a2  s .  com
    inputframe.copyTo(mGrey);
    Imgproc.cvtColor(mRgba, mGrey, Imgproc.COLOR_BGR2GRAY);
    Imgproc.equalizeHist(mGrey, mGrey);
    classifier.detectMultiScale(mGrey, detectedObjects);

    LOG.debug("detectWithClassifier - end;");
    return detectedObjects.toArray();
}

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From source file:car_counter.counting.opencv.OpencvCarCounter.java

License:Apache License

@Override
public Collection<DetectedVehicle> processVideo(Path video, DateTime startDateTime) {
    CascadeClassifier carDetector = new CascadeClassifier("/Users/luke/working/car-counter/data/cars3.xml");

    VideoCapture videoCapture = new VideoCapture();
    videoCapture.open("/Users/luke/working/car-counter/data/video1.m4v");

    int index = 0;

    while (true) {
        if (!videoCapture.read(image)) {
            break;
        }//from   w w  w  .j  a v  a 2s.  c  o m

        System.out.print(".");

        //processFrame();

        MatOfRect carDetections = new MatOfRect();
        carDetector.detectMultiScale(image, carDetections);

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

        // Draw a bounding box around each hit
        for (Rect rect : carDetections.toArray()) {
            Core.rectangle(image, new Point(rect.x, rect.y),
                    new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0));
        }

        String file = String.format("/Users/luke/working/car-counter/data/out/out-%03d.jpg", index++);
        org.opencv.highgui.Highgui.imwrite(file, image);
    }

    return null;
}

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From source file:ch.zhaw.facerecognitionlibrary.Helpers.FaceDetection.java

License:Open Source License

public Eyes getEyes(Mat img) {
    double halfWidth = img.cols() / 2;
    double height = img.rows();
    double[] values = new double[4];
    values[0] = 0;//from ww w. j a  v a2 s .co  m
    values[1] = 0;
    values[2] = halfWidth;
    values[3] = height;
    Rect rightHalf = new Rect(values);
    values[0] = halfWidth;
    Rect leftHalf = new Rect(values);
    MatOfRect rightEyes = new MatOfRect();
    MatOfRect leftEyes = new MatOfRect();

    Mat rightHalfImg = img.submat(rightHalf);
    rightEyeDetector.detectMultiScale(rightHalfImg, rightEyes);
    Mat leftHalfImg = img.submat(leftHalf);
    leftEyeDetector.detectMultiScale(leftHalfImg, leftEyes);

    if (rightEyes.empty() || leftEyes.empty() || rightEyes.toArray().length > 1
            || leftEyes.toArray().length > 1) {
        return null;
    }

    Rect rightEye = rightEyes.toArray()[0];
    Rect leftEye = leftEyes.toArray()[0];

    MatOfFloat rightPoint = new MatOfFloat(rightEye.x + rightEye.width / 2, rightEye.y + rightEye.height / 2);
    MatOfFloat leftPoint = new MatOfFloat(img.cols() / 2 + leftEye.x + leftEye.width / 2,
            leftEye.y + leftEye.height / 2);

    MatOfFloat diff = new MatOfFloat();
    Core.subtract(leftPoint, rightPoint, diff);
    double angle = Core.fastAtan2(diff.toArray()[1], diff.toArray()[0]);
    double dist = Core.norm(leftPoint, rightPoint, Core.NORM_L2);
    Eyes eyes = new Eyes(dist, rightPoint, leftPoint, angle);
    return eyes;
}

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From source file:classes.FaceDetector.java

public static String detectFace(String filePath) {

    //        String dirName = "C:/Users/ggm/Documents/NetBeansProjects/MyWebApplication";
    String dirName = "C:/Users/Gonzalo/Documents/NetBeansProjects/MyWebApplication";
    //        String dirName = "/Users/ggmendez/Development/MyWebApplication";

    System.out.println(dirName);/*from w  w  w . ja v  a2s . co m*/

    String frontalfaceFile = dirName + "/data/lbpcascades/lbpcascade_frontalface.xml";

    System.out.println(frontalfaceFile);

    CascadeClassifier faceDetector = new CascadeClassifier(frontalfaceFile);

    Mat image = Highgui.imread(filePath);

    System.out.println(image);

    // Detect faces in the image 
    // MatOfRect is a special container class for Rect.
    MatOfRect faceDetections = new MatOfRect();
    faceDetector.detectMultiScale(image, faceDetections);

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

    // Draw a bounding box around each face.
    for (Rect rect : faceDetections.toArray()) {
        Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),
                new Scalar(0, 255, 0));
    }

    // Save the visualized detection.            
    Date date = new Date();
    Format formatter = new SimpleDateFormat("YYYY-MM-dd_hh-mm-ss");
    String filename = dirName + "/imgs/out_" + formatter.format(date) + ".png";

    System.out.println(String.format("Writing %s", filename));
    Highgui.imwrite(filename, image);

    Gson gson = new Gson();
    String jsonResponse = gson.toJson(faceDetections.toArray());
    jsonResponse = jsonResponse.replaceAll("x", "left").replaceAll("y", "top");

    return jsonResponse;

}

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