Example usage for org.opencv.core Mat Mat

Introduction

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

Prototype

public Mat() 

Source Link

Usage

From source file:intrudersrecorder.MainFXMLDocumentController.java

@Override
public void initialize(URL url, ResourceBundle rb) {
    vidCap = new VideoCapture();

    previousMatrix = new Mat();
    subtractionResult = new Mat();
    col = new ArrayList<>();

    resolutionWidth = 100;/* w w  w . j  a v  a 2  s.c om*/
    resolutionHeight = 100;

    sliderInit();
    resSliderListener();
    pixDiffSliderListener();
    objSizeSliderListener();

    cameraSwitch.setStyle("-fx-background-color: red");
}

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From source file:intrudersrecorder.MainFXMLDocumentController.java

private Image grabFrame() {
    inputImage = null;/*from ww  w . j ava2 s .  c  o m*/
    singleFrame = new Mat();
    if (vidCap.isOpened()) {
        try {
            vidCap.read(singleFrame);
            Imgproc.cvtColor(singleFrame, singleFrame, Imgproc.COLOR_BGR2GRAY);
            if (!hasPrevious) {
                MatOfByte buff = new MatOfByte();
                Imgcodecs.imencode(".jpg", singleFrame, buff);
                inputImage = new Image(new ByteArrayInputStream(buff.toArray()));
            }
        } catch (Exception e) {
            System.out.println("problem in reading frame");
        }
    }
    if (hasPrevious) {
        Core.absdiff(singleFrame, previousMatrix, subtractionResult);
        hi = singleFrame.rows();
        wi = singleFrame.cols();
        col.clear();
        for (int r = 0; r < hi; r++) {
            for (int c = 0; c < wi; c++) {
                //                    double v1[] = singleFrame.get(r, c);
                //                    double v2[] = prevMat.get(r, c);
                //                    double diff = Math.abs(v1[0] - v2[0]);
                previousMatrix.put(r, c, singleFrame.get(r, c)[0]);
                if (subtractionResult.get(r, c)[0] >= minPixelDiff) {
                    subtractionResult.put(r, c, 255);
                    col.add(new Coordinates(r, c));
                } else {
                    subtractionResult.put(r, c, 0);
                }
            }
        }

        boolean ok = true;
        int sz = col.size();
        for (int i = 0; i < sz; i++) {
            double v[] = subtractionResult.get(col.get(i).getR(), col.get(i).getC());
            if (v[0] == 255) {
                topLeftR = 2 * hi;
                topLeftC = 2 * wi;
                bottomRightR = -1;
                bottomRightC = -1;
                cnt = 1;
                floodFill(col.get(i).getR(), col.get(i).getC());
                if (cnt >= minPixelsOfAnObject) {
                    //                      System.out.println("burglur........"+cnt);
                    drawBorder();
                }
            }
        }

        // using non recursive flood fill

        //            for(int i = 0; i < sz; i++){
        //                topLeftR = 2 * hi;
        //                topLeftC = 2 * wi;
        //                bottomRightR = -1;
        //                bottomRightC = -1;
        //                cnt = 1;
        //                Coordinates c = new Coordinates(col.get(i).getR(), col.get(i).getC());
        //                if(subsRes.get(c.getR(), c.getC())[0] == 255){
        //                    nonRecursiveFloodfill(c);
        //                    if(cnt >= minPixelsOfAnObject){
        //                        System.out.println("burglur........"+cnt);
        //                        //floodOne(r, c);
        //                        //drawBorder();
        //                        //ok = false;
        //                    }
        //                }
        //            }

        //            System.out.println("h: "+subsRes.rows() + " w "+subsRes.cols());
        MatOfByte buff = new MatOfByte();
        Imgcodecs.imencode(".jpg", singleFrame, buff);
        inputImage = new Image(new ByteArrayInputStream(buff.toArray()));
    } else {
        //System.out.println("first frame");
        hasPrevious = true;
        previousMatrix = singleFrame.clone();
    }
    return inputImage;
}

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From source file:io.appium.java_client.ScreenshotState.java

License:Apache License

private static Mat resizeFirstMatrixToSecondMatrixResolution(Mat first, Mat second) {
    if (first.width() != second.width() || first.height() != second.height()) {
        final Mat result = new Mat();
        final Size sz = new Size(second.width(), second.height());
        Imgproc.resize(first, result, sz);
        return result;
    }/* ww  w . j a v  a2  s.  c  o  m*/
    return first;
}

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From source file:io.github.jakejmattson.facialrecognition.FacialRecognition.java

License:Open Source License

private static void capture() {
    File classifier = new File("lbpcascade_frontalface_improved.xml");

    if (!classifier.exists()) {
        displayFatalError("Unable to find classifier!");
        return;/*from   w  w  w  . j  a va 2s . c o m*/
    }

    CascadeClassifier faceDetector = new CascadeClassifier(classifier.toString());
    VideoCapture camera = new VideoCapture(0);

    if (!camera.isOpened()) {
        displayFatalError("No camera detected!");
        return;
    }

    if (!DATABASE.exists())
        DATABASE.mkdir();

    ImageFrame frame = new ImageFrame();

    while (frame.isOpen() && camera.isOpened()) {
        Mat rawImage = new Mat();
        camera.read(rawImage);
        Mat newImage = detectFaces(rawImage, faceDetector, frame);
        frame.showImage(newImage);
    }

    camera.release();
}

---

From source file:io.github.jakejmattson.facialrecognition.FacialRecognition.java

License:Open Source License

private static int compareFaces(Mat currentImage, String fileName) {
    Mat compareImage = Imgcodecs.imread(fileName);
    ORB orb = ORB.create();
    int similarity = 0;

    MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
    MatOfKeyPoint keypoints2 = new MatOfKeyPoint();
    orb.detect(currentImage, keypoints1);
    orb.detect(compareImage, keypoints2);

    Mat descriptors1 = new Mat();
    Mat descriptors2 = new Mat();
    orb.compute(currentImage, keypoints1, descriptors1);
    orb.compute(compareImage, keypoints2, descriptors2);

    if (descriptors1.cols() == descriptors2.cols()) {
        MatOfDMatch matchMatrix = new MatOfDMatch();
        DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING);
        matcher.match(descriptors1, descriptors2, matchMatrix);
        DMatch[] matches = matchMatrix.toArray();

        for (DMatch match : matches)
            if (match.distance <= 50)
                similarity++;//w w w .ja v a2 s  .  c o m
    }

    return similarity;
}

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From source file:jarvis.module.colourtracking.ColourTrackingModule.java

public ColourTrackingModule() {
    System.out.println("Initialising colour tracking module...");

    // Load native library
    System.loadLibrary("opencv_java2410");

    // Initialise webcam
    cap = new VideoCapture(0);

    // Initialise window
    frame = new JFrame("untitled");
    frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
    frame.setSize(640, 480 + 50);/*ww  w .  j  a  v a 2 s .c o m*/
    panel = new Panel();
    frame.setContentPane(panel);
    lowH = new JSlider(JSlider.HORIZONTAL, 0, 179, 0);
    panel.add(lowH);
    lowS = new JSlider(JSlider.HORIZONTAL, 0, 255, 0);
    panel.add(lowS);
    lowV = new JSlider(JSlider.HORIZONTAL, 0, 255, 0);
    panel.add(lowV);
    highH = new JSlider(JSlider.HORIZONTAL, 0, 179, 0);
    panel.add(highH);
    highS = new JSlider(JSlider.HORIZONTAL, 0, 255, 0);
    panel.add(highS);
    highV = new JSlider(JSlider.HORIZONTAL, 0, 255, 0);
    panel.add(highV);
    frame.setVisible(true);
    running = true;

    imageOriginal = new Mat();
    imageHSV = new Mat();
    imageThresholded = new Mat();
    mat2image = new Mat2Image();

    System.out.println("done");
}

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From source file:javaapplication1.Ocv.java

public void blendWithGray50(String input, String output) {
    // load the image and read it into a matrix
    File f2 = new File(input);
    Mat image = Highgui.imread(this.input);

    // clone the image, and convert it to grayscale
    Mat gray = image.clone();/*from w w w . ja v a  2 s. c  o  m*/
    Imgproc.cvtColor(gray, gray, Imgproc.COLOR_BGR2GRAY, 1);
    Imgproc.cvtColor(gray, gray, Imgproc.COLOR_GRAY2BGR, 3);

    // blend the two images (equal weight) into a new matrix and save it
    Mat dst = new Mat();
    Core.addWeighted(image, .5f, gray, .5f, 0.0, dst);
    Highgui.imwrite(this.output, dst);
}

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From source file:javaapplication1.Ocv.java

void doSobel(String input, String output) {
    // load the image and read it into a matrix
    File f2 = new File(input);
    Mat image = Highgui.imread(this.input);

    // blur the image
    Imgproc.GaussianBlur(image, image, new Size(3, 3), 0, 0, Imgproc.BORDER_DEFAULT);

    // convert the image to gray
    Mat gray = new Mat();
    Imgproc.cvtColor(image, gray, Imgproc.COLOR_BGR2GRAY);

    // parameters for our conversion
    int scale = 1;
    int delta = 0;
    int ddepth = CvType.CV_16S;

    // figure out the X gradient, get its absolute value
    Mat gx = new Mat();
    Imgproc.Sobel(gray, gx, ddepth, 1, 0, 3, scale, delta, Imgproc.BORDER_DEFAULT);
    Mat abs_gx = new Mat();
    Core.convertScaleAbs(gx, abs_gx);//w ww. j  ava  2 s.  c o m

    // do the same for Y
    Mat gy = new Mat();
    Imgproc.Sobel(gray, gy, ddepth, 0, 1, 3, scale, delta, Imgproc.BORDER_DEFAULT);
    Mat abs_gy = new Mat();
    Core.convertScaleAbs(gy, abs_gy);

    // do a simple combine, and save it
    Mat grad = new Mat();
    Core.addWeighted(abs_gx, 0.5, abs_gy, 0.5, 0, grad);
    Highgui.imwrite(this.output, grad);
}

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From source file:javacv.JavaCV.java

/**
 * @param args the command line arguments
 *///from w ww.j  av  a 2 s  .  com
public static void main(String[] args) {
    // TODO code application logic here

    System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
    Mat mat = Mat.eye(3, 3, CvType.CV_8UC1);
    System.out.println("mat = " + mat.dump());

    CascadeClassifier faceDetector = new CascadeClassifier("./data/lbpcascade_frontalface.xml");
    //CascadeClassifier faceDetector = new CascadeClassifier();

    JFrame frame = new JFrame("BasicPanel");
    frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
    frame.setSize(400, 400);
    JavaCV panel = new JavaCV();
    frame.setContentPane(panel);
    frame.setVisible(true);
    Mat webcam_image = new Mat();
    BufferedImage temp;
    VideoCapture capture;
    capture = new VideoCapture(0);

    if (capture.isOpened()) {
        while (true) {
            capture.read(webcam_image);
            if (!webcam_image.empty()) {
                frame.setSize(webcam_image.width() + 40, webcam_image.height() + 60);

                MatOfRect faceDetections = new MatOfRect();
                faceDetector.detectMultiScale(webcam_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(webcam_image, new Point(rect.x, rect.y),
                            new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0));
                }

                temp = matToBufferedImage(webcam_image);
                panel.setimage(temp);
                panel.repaint();
            } else {
                System.out.println(" --(!) No captured frame -- Break!");
                break;
            }
        }
    }
    return;

}

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From source file:javafx1.JavaFX1.java

private Mat doCanny(Mat frame) {
        // init//w  w  w.ja  va2  s.  c o  m
        Mat grayImage = new Mat();
        Mat detectedEdges = new Mat();

        // convert to grayscale
        Imgproc.cvtColor(frame, grayImage, Imgproc.COLOR_BGR2GRAY);

        // reduce noise with a 3x3 kernel
        Imgproc.blur(grayImage, detectedEdges, new Size(2, 2));

        // canny detector, with ratio of lower:upper threshold of 3:1
        // Imgproc.Canny(detectedEdges, detectedEdges, 2, 2 * 3);
        // using Canny's output as a mask, display the result
        Mat dest = new Mat();
        frame.copyTo(dest, detectedEdges);

        return dest;
    }

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