Example usage for org.opencv.core Scalar Scalar

Introduction

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

Prototype

public Scalar(double v0, double v1, double v2) 

Source Link

Usage

From source file:depthDataFromStereoCamsOpenCV.ProcessImages.java

/**
 * /*w  w  w . j a  va  2 s.  c  o  m*/
 * @param image
 * @return
 */
public static Mat bringImageToStdSize(Mat image) {
    //create the square container
    int dstWidth = 300;
    int dstHeight = 500;
    Mat dst = new Mat(dstHeight, dstWidth, CvType.CV_8UC3, new Scalar(0, 0, 0));
    //ProcessImages.displayImage(ProcessImages.Mat2BufferedImage(dst),"background");
    //Put the image into the container, roi is the new position
    Rect roi = new Rect((dstWidth - image.cols()) / 2, (dstHeight - image.rows()) / 2, image.cols(),
            image.rows());
    Mat targetROI = new Mat(dst, roi);
    image.copyTo(targetROI);
    //          ProcessImages.displayImage(ProcessImages.Mat2BufferedImage(dst),"Standardized");
    return dst;
}

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From source file:detectiontest.ImageDisplayer.java

public static Scalar colorToScalar(Color c) {
    return new Scalar(c.getBlue(), c.getGreen(), c.getRed());
}

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From source file:dfmDrone.examples.fitEllipseExample.java

private static Mat findAndDrawEllipse(Mat sourceImg) {
    Mat grayScaleImg = new Mat();
    Mat hsvImg = new Mat();
    Imgproc.cvtColor(sourceImg, hsvImg, Imgproc.COLOR_BGR2HSV);
    Mat lower_hue_range = new Mat();
    Mat upper_hue_range = new Mat();
    Core.inRange(hsvImg, new Scalar(0, 100, 45), new Scalar(15, 255, 255), lower_hue_range);
    Core.inRange(hsvImg, new Scalar(160, 100, 45), new Scalar(180, 255, 255), upper_hue_range);
    Mat red_hue_image = new Mat();
    Core.addWeighted(lower_hue_range, 1.0, upper_hue_range, 1.0, 0, red_hue_image);
    Mat dilateElement = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(24, 24));
    Mat erodeElement = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(10, 10));

    Imgproc.blur(red_hue_image, red_hue_image, new Size(11, 11));
    // init//from w w  w  .j a  v a  2s . c om
    List<MatOfPoint> contours = new ArrayList<>();
    Mat hierarchy = new Mat();

    // find contours
    Imgproc.findContours(red_hue_image, contours, hierarchy, Imgproc.RETR_CCOMP, Imgproc.CHAIN_APPROX_SIMPLE);
    System.out.println("After findcontours");
    // if any contour exist...
    if (hierarchy.size().height > 0 && hierarchy.size().width > 0) {
        // for each contour, display it in blue
        for (int idx = 0; idx >= 0; idx = (int) hierarchy.get(0, idx)[0]) {
            System.out.println(idx);
            //   Imgproc.drawContours(frame, contours, idx, new Scalar(250, 0, 0), 3);

        }
    }
    MatOfPoint2f approxCurve = new MatOfPoint2f();

    //For each contour found
    MatOfPoint2f contour2f = null;
    RotatedRect rotatedrect = null;
    for (MatOfPoint contour : contours) {
        //Convert contours(i) from MatOfPoint to MatOfPoint2f
        if (contour2f == null)
            contour2f = new MatOfPoint2f(contour.toArray());
        if (contour.size().area() > contour2f.size().area()) {
            contour2f = new MatOfPoint2f(contour.toArray());
        }
    }
    try {
        Imgproc.fitEllipse(contour2f);
        rotatedrect = Imgproc.fitEllipse(contour2f);

        double approxDistance = Imgproc.arcLength(contour2f, true) * 0.02;
        Imgproc.approxPolyDP(contour2f, approxCurve, approxDistance, true);

        //Convert back to MatOfPoint
        MatOfPoint points = new MatOfPoint(approxCurve.toArray());

        // Get bounding rect of contour
        Rect rect = Imgproc.boundingRect(points);

        // draw enclosing rectangle (all same color, but you could use variable i to make them unique)
        Imgproc.rectangle(sourceImg, rect.tl(), rect.br(), new Scalar(255, 0, 0), 1, 8, 0);
        Imgproc.ellipse(sourceImg, rotatedrect, new Scalar(255, 192, 203), 4, 8);
    } catch (CvException e) {
        e.printStackTrace();
        System.out.println("Ingen ellipse fundet");
    }
    return sourceImg;
}

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From source file:digimesh.xbee.gui.SensorMap.java

private void drawSensor(SmartSensor sensor) {
    Point sensorLocation = new Point(sensor.getPositionXY().positionX - 50,
            sensor.getPositionXY().positionY + 30);

    int measNr = sensor.getMeasurmentToDraw();
    String id = sensor.getId();//from   w w  w  .jav  a  2 s.c  o m
    String sTextName = "Sensor ID : " + id.substring(id.length() - 4, id.length());
    int fontFace = Core.FONT_HERSHEY_PLAIN;
    double fontScale = 0.7;
    Imgproc.putText(map, sTextName, sensorLocation, fontFace, fontScale, Scalar.all(255));
    Scalar circleColor = new Scalar(255, 255, 255);
    if (sensor.hasMeasurements) {
        double value = sensor.m_measurments.get(measNr).value;
        String measName = sensor.m_measurments.get(measNr).name;
        String unit = sensor.m_measurments.get(measNr).unit;

        String sTextMeas = measName + " = " + value + "[" + unit + "]";
        Imgproc.putText(map, sTextMeas,
                new Point(sensor.getPositionXY().positionX - 50, (sensor.getPositionXY().positionY + 50)),
                fontFace, fontScale, Scalar.all(255));
        double upperLimit = sensor.m_measurments.get(measNr).upperLimit;
        double lowerLimit = sensor.m_measurments.get(measNr).lowerLimit;
        //check value

        if (value > upperLimit) {
            circleColor = new Scalar(0, 0, 255);
        } else if (value < lowerLimit) {
            circleColor = new Scalar(255, 0, 0);
        } else {
            circleColor = new Scalar(0, 255, 0);
        }
    } else {
        Imgproc.putText(map, HUB_LABEL,
                new Point(sensor.getPositionXY().positionX - 50, (sensor.getPositionXY().positionY + 12)),
                fontFace, fontScale, Scalar.all(255));
    }

    Imgproc.circle(map, sensorLocation, 10, circleColor, 2, fontFace, 0);

}

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From source file:digitalassistant.Panel.java

public void face_detect(Mat image) {
    //System.out.println("\nRunning DetectFaceDemo");

    // Create a face detector from the cascade file in the resources
    // directory.
    String test1 = getClass().getResource("lbpcascade_frontalface.xml").getPath();
    test1 = test1.replace("/C:", "C:");
    CascadeClassifier faceDetector = new CascadeClassifier(test1);
    /* String test=getClass().getResource("lena.png").getPath();
     test = test.replace("/C:", "C:");//from  ww  w.jav  a  2  s .c  o m
     System.out.println(test);
     Mat image = Highgui.imread(test);*/

    // 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.
    //  String filename = "faceDetection.png";
    //  System.out.println(String.format("Writing %s", filename));
    // Highgui.imwrite(filename, image);
}

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From source file:Domain.ImgProcess.java

public Mat DetectarFace(Canvas c, Mat image) throws IOException {
    System.out.println("Rodando DetectFace");

    CascadeClassifier faceDetector = new CascadeClassifier(
            "C:\\Users\\Gertrude\\Documents\\NetBeansProjects\\OWL_Sight\\src\\Resources\\lbpcascade_frontalface.xml"); // seleciona o classificador para identificao da face

    MatOfRect faceDetections = new MatOfRect(); //matriz de rectangulos representando os rosto encontrados
    faceDetector.detectMultiScale(image, faceDetections);//detecta multiplas faces na imagem fornecida

    System.out.printf("Detected %s faces", faceDetections.toArray().length);

    Mat corte = null;//from w ww  .j  a  va  2s  .co  m

    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, 0, 0));// desenha os rectangulos

        // Highgui.imwrite("C:/TCC-FacialRecognize/src/resources/TESTECORTE.jpg", utl.corte(image, rect));
        corte = new Mat(image, rect);
    }

    Size sz = new Size(120, 120);

    MatOfByte bytemat = new MatOfByte(); //transformando a matriz image em uma matriz de bytes para carga no canvas do form principal
    Highgui.imencode(".jpg", corte, bytemat);
    byte[] bytes = bytemat.toArray();
    InputStream in = new ByteArrayInputStream(bytes);

    BufferedImage render = ImageIO.read(in);
    Graphics g = c.getGraphics();

    g.drawImage(render, 1, 1, c.getHeight(), c.getWidth(), c);

    return corte;
}

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From source file:dr.Interface.java

private void detect_BtnMouseClicked(java.awt.event.MouseEvent evt) {//GEN-FIRST:event_detect_BtnMouseClicked

    if (file != null) {
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

        CascadeClassifier faceDetector = new CascadeClassifier(HAAR_FILE_PATH);
        CascadeClassifier eyeDetector = new CascadeClassifier("src//dr//haarcascade_eye.xml");

        Mat image = Highgui.imread(file.getAbsolutePath());
        MatOfRect faceDetections = new MatOfRect();
        MatOfRect eyeDetections = new MatOfRect();

        faceDetector.detectMultiScale(image, faceDetections, scale, minN, 0, min, max);

        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));
        }// w w  w  . ja  v  a 2  s .  c o m
        if (eye_detection.isSelected()) {

            eyeDetector.detectMultiScale(image, eyeDetections, e_scale, e_minN, 0, e_min, e_max);
            for (Rect rect : eyeDetections.toArray()) {
                Core.circle(image, new Point(rect.x + rect.width / 2, rect.y + rect.width / 2), rect.width / 2,
                        new Scalar(255, 0, 255));
                Core.circle(image, new Point(rect.x + rect.width / 2, rect.y + rect.width / 2),
                        rect.width / 2 + 1, new Scalar(255, 0, 255));
                Core.circle(image, new Point(rect.x + rect.width / 2, rect.y + rect.width / 2),
                        rect.width / 2 + 1, new Scalar(255, 0, 255));
            }
        }
        String filename = file.getAbsolutePath().substring(0, file.getAbsolutePath().lastIndexOf("\\"))
                + "\\out.png";
        Highgui.imwrite(filename, image);
        BufferedImage i;
        try {
            if ((i = ImageIO.read(new File(filename))) != null) {
                current_image = i;
                loadImage_Lbl.setIcon(new ImageIcon(resize_image(i)));
            } else {
                JOptionPane.showMessageDialog(this, "Nu s-a detectat nimic!", "Info",
                        JOptionPane.INFORMATION_MESSAGE);
            }
        } catch (IOException ex) {
            Logger.getLogger(Interface.class.getName()).log(Level.SEVERE, null, ex);
        }
    }
}

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From source file:drawing.application.FaceDetection.java

License:Open Source License

@Override
public void run() {
    CascadeClassifier faceDetector = new CascadeClassifier("lbpcascade_frontalface.xml");
    Mat image = Imgcodecs.imread(filePath);

    MatOfRect faceDetections = new MatOfRect();
    faceDetector.detectMultiScale(image, faceDetections);

    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(0, 255, 0));
    }/*from  w  w  w.ja  v  a 2 s . co m*/

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

    int numFaces = faceDetections.toArray().length;
    JOptionPane.showMessageDialog(null,
            "Detected " + faceDetections.toArray().length + (numFaces == 1 ? " face" : " faces"));
}

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From source file:edu.fiu.cate.breader.BaseSegmentation.java

/**
 * Finds the bounding box for the book on the stand using 
 * the high resolution image.//ww  w  .  j av  a 2 s. c o  m
 * @param src- High Resolution image of the book
 * @return Rectangle delineating the book
 */
public Rect highRes(Mat src) {
    Mat dst = src.clone();
    Imgproc.blur(src, dst, new Size(100.0, 100.0), new Point(-1, -1), Core.BORDER_REPLICATE);
    Imgproc.threshold(dst, dst, 0, 255, Imgproc.THRESH_BINARY_INV + Imgproc.THRESH_OTSU);
    Imgproc.Canny(dst, dst, 50, 200, 3, false);

    List<MatOfPoint> contours = new LinkedList<>();
    Mat hierarchy = new Mat();
    Imgproc.findContours(dst, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE,
            new Point(0, 0));

    Mat color = new Mat();
    Imgproc.cvtColor(src, color, Imgproc.COLOR_GRAY2BGR);
    for (int k = 0; k < contours.size(); k++) {
        byte[] vals = ITools.getHeatMapColor((float) k / (float) contours.size());
        Imgproc.drawContours(color, contours, k, new Scalar(vals[0], vals[1], vals[2]), 8);
    }
    new IViewer("HighRes Contours ", BReaderTools.bufferedImageFromMat(color));

    Point center = new Point(src.cols() / 2, src.rows() / 2);
    //Check hierarchy tree
    int[] res = polySearch(center, hierarchy, contours, 0);
    while (res[0] != 1 && res[2] != -1) {
        res = polySearch(center, hierarchy, contours, res[2]);
        if (res[0] == 1)
            break;
    }

    MatOfInt tHull = new MatOfInt();
    int index = 0;
    if (res[1] != -1) {
        index = res[1];
    }
    Imgproc.convexHull(contours.get(index), tHull);

    //get bounding box
    MatOfPoint cont = contours.get(index);
    Point[] points = new Point[tHull.rows()];
    for (int i = 0; i < tHull.rows(); i++) {
        int pIndex = (int) tHull.get(i, 0)[0];
        points[i] = new Point(cont.get(pIndex, 0));
    }
    Rect out = Imgproc.boundingRect(new MatOfPoint(points));
    return out;
}

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From source file:edu.fiu.cate.breader.BaseSegmentation.java

/**
 * Finds the bounding box for the book on the stand using 
 * the depth average image.//from w w  w .j av a  2 s .c  o  m
 * @param src- The Depth average image
 * @return Rectangle delineating the book
 */
public Rect lowResDist(Mat src) {
    Mat dst = src.clone();

    Imgproc.blur(src, dst, new Size(5, 5), new Point(-1, -1), Core.BORDER_REPLICATE);
    //      Imgproc.threshold(dst, dst, 0,255,Imgproc.THRESH_BINARY_INV+Imgproc.THRESH_OTSU);
    Imgproc.Canny(dst, dst, 50, 200, 3, false);
    //      Canny(src, dst, 20, 60, 3);

    List<MatOfPoint> contours = new LinkedList<>();
    Mat hierarchy = new Mat();
    /// Find contours
    Imgproc.findContours(dst, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE,
            new Point(0, 0));

    Mat color = new Mat();
    Imgproc.cvtColor(src, color, Imgproc.COLOR_GRAY2BGR);
    for (int k = 0; k < contours.size(); k++) {
        byte[] vals = ITools.getHeatMapColor((float) k / (float) contours.size());
        Imgproc.drawContours(color, contours, k, new Scalar(vals[0], vals[1], vals[2]), 1);
    }
    new IViewer("LowRes Contours ", BReaderTools.bufferedImageFromMat(color));

    for (int k = 0; k < contours.size(); k++) {
        MatOfPoint2f tMat = new MatOfPoint2f();
        Imgproc.approxPolyDP(new MatOfPoint2f(contours.get(k).toArray()), tMat, 5, true);
        contours.set(k, new MatOfPoint(tMat.toArray()));
    }

    List<Point> points = new LinkedList<Point>();
    for (int i = 0; i < contours.size(); i++) {
        points.addAll(contours.get(i).toList());
    }

    MatOfInt tHull = new MatOfInt();
    Imgproc.convexHull(new MatOfPoint(points.toArray(new Point[points.size()])), tHull);

    //get bounding box
    Point[] tHullPoints = new Point[tHull.rows()];
    for (int i = 0; i < tHull.rows(); i++) {
        int pIndex = (int) tHull.get(i, 0)[0];
        tHullPoints[i] = points.get(pIndex);
    }
    Rect out = Imgproc.boundingRect(new MatOfPoint(tHullPoints));
    return out;
}

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