Example usage for org.opencv.core Mat put

List of usage examples for org.opencv.core Mat put

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Introduction

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

Prototype

public int put(int row, int col, byte[] data)

Source Link

Usage

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

License:Open Source License

public static Rect[] rotateFaces(Mat img, Rect[] faces, int angle) {
    Point center = new Point(img.cols() / 2, img.rows() / 2);
    Mat rotMat = Imgproc.getRotationMatrix2D(center, angle, 1);
    rotMat.convertTo(rotMat, CvType.CV_32FC1);
    float scale = img.cols() / img.rows();
    for (Rect face : faces) {
        Mat m = new Mat(3, 1, CvType.CV_32FC1);
        m.put(0, 0, face.x);
        m.put(1, 0, face.y);/* www.  j  av a  2s .c om*/
        m.put(2, 0, 1);
        Mat res = Mat.zeros(2, 1, CvType.CV_32FC1);
        Core.gemm(rotMat, m, 1, new Mat(), 0, res, 0);
        face.x = (int) res.get(0, 0)[0];
        face.y = (int) res.get(1, 0)[0];
        if (angle == 270 || angle == -90) {
            face.x = (int) (face.x * scale - face.width);
            face.x = face.x + face.width / 4;
            face.y = face.y + face.height / 4;
        } else if (angle == 180 || angle == -180) {
            face.x = face.x - face.width;
            face.y = face.y - face.height;
        } else if (angle == 90 || angle == -270) {
            face.y = (int) (face.y * scale - face.height);
            face.x = face.x - face.width / 4;
            face.y = face.y - face.height / 4;
        }
    }
    return faces;
}

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

License:Open Source License

public Mat readMat(String tag) {
    if (isWrite) {
        System.err.println("Try read from file with write flags");
        return null;
    }//from   w  w w .jav  a  2  s.co  m

    NodeList nodelist = doc.getElementsByTagName(tag);
    Mat readMat = null;

    for (int i = 0; i < nodelist.getLength(); i++) {
        Node node = nodelist.item(i);

        if (node.getNodeType() == Node.ELEMENT_NODE) {
            Element element = (Element) node;

            String type_id = element.getAttribute("type_id");
            if ("opencv-matrix".equals(type_id) == false) {
                System.out.println("Fault type_id ");
            }

            String rowsStr = element.getElementsByTagName("rows").item(0).getTextContent();
            String colsStr = element.getElementsByTagName("cols").item(0).getTextContent();
            String dtStr = element.getElementsByTagName("dt").item(0).getTextContent();
            String dataStr = element.getElementsByTagName("data").item(0).getTextContent();

            int rows = Integer.parseInt(rowsStr);
            int cols = Integer.parseInt(colsStr);
            int type = CvType.CV_8U;

            Scanner s = new Scanner(dataStr);

            if ("f".equals(dtStr)) {
                type = CvType.CV_32F;
                readMat = new Mat(rows, cols, type);
                float fs[] = new float[1];
                for (int r = 0; r < rows; r++) {
                    for (int c = 0; c < cols; c++) {
                        if (s.hasNextFloat()) {
                            fs[0] = s.nextFloat();
                        } else {
                            fs[0] = 0;
                            System.err.println("Unmatched number of float value at rows=" + r + " cols=" + c);
                        }
                        readMat.put(r, c, fs);
                    }
                }
            } else if ("i".equals(dtStr)) {
                type = CvType.CV_32S;
                readMat = new Mat(rows, cols, type);
                int is[] = new int[1];
                for (int r = 0; r < rows; r++) {
                    for (int c = 0; c < cols; c++) {
                        if (s.hasNextInt()) {
                            is[0] = s.nextInt();
                        } else {
                            is[0] = 0;
                            System.err.println("Unmatched number of int value at rows=" + r + " cols=" + c);
                        }
                        readMat.put(r, c, is);
                    }
                }
            } else if ("s".equals(dtStr)) {
                type = CvType.CV_16S;
                readMat = new Mat(rows, cols, type);
                short ss[] = new short[1];
                for (int r = 0; r < rows; r++) {
                    for (int c = 0; c < cols; c++) {
                        if (s.hasNextShort()) {
                            ss[0] = s.nextShort();
                        } else {
                            ss[0] = 0;
                            System.err.println("Unmatched number of int value at rows=" + r + " cols=" + c);
                        }
                        readMat.put(r, c, ss);
                    }
                }
            } else if ("b".equals(dtStr)) {
                readMat = new Mat(rows, cols, type);
                byte bs[] = new byte[1];
                for (int r = 0; r < rows; r++) {
                    for (int c = 0; c < cols; c++) {
                        if (s.hasNextByte()) {
                            bs[0] = s.nextByte();
                        } else {
                            bs[0] = 0;
                            System.err.println("Unmatched number of byte value at rows=" + r + " cols=" + c);
                        }
                        readMat.put(r, c, bs);
                    }
                }
            }
        }
    }
    return readMat;
}

From source file:ch.zhaw.facerecognitionlibrary.PreProcessor.Contours.LocalBinaryPattern.java

License:Open Source License

@Override
public PreProcessor preprocessImage(PreProcessor preProcessor) {
    List<Mat> images = preProcessor.getImages();
    List<Mat> processed = new ArrayList<Mat>();
    for (Mat img : images) {
        // Resize for Performance enhancement
        Size size = new Size(preProcessor.getN(), preProcessor.getN());
        Imgproc.resize(img, img, size);//from   w ww.  j  a  v a2s .com
        Mat lbp = new Mat(img.rows() - 2, img.cols() - 2, img.type());
        for (int i = 1; i < img.rows() - 1; i++) {
            for (int j = 1; j < img.cols() - 1; j++) {
                BitSet out = new BitSet(8);
                double cen = img.get(i, j)[0];
                if (img.get(i - 1, j - 1)[0] > cen)
                    out.set(0);
                if (img.get(i - 1, j)[0] > cen)
                    out.set(1);
                if (img.get(i - 1, j + 1)[0] > cen)
                    out.set(2);
                if (img.get(i, j + 1)[0] > cen)
                    out.set(3);
                if (img.get(i + 1, j + 1)[0] > cen)
                    out.set(4);
                if (img.get(i + 1, j)[0] > cen)
                    out.set(5);
                if (img.get(i + 1, j - 1)[0] > cen)
                    out.set(6);
                if (img.get(i, j - 1)[0] > cen)
                    out.set(7);
                int value = 0;
                for (int k = 0; k < out.length(); k++) {
                    int index = out.nextSetBit(k);
                    value += Math.pow(2, out.length() - 1 - index);
                    k = index;
                }
                lbp.put(i - 1, j - 1, value);
            }
        }
        processed.add(lbp);
    }
    preProcessor.setImages(processed);
    return preProcessor;
}

From source file:ch.zhaw.facerecognitionlibrary.PreProcessor.StandardPreprocessing.EyeAlignment.java

License:Open Source License

public PreProcessor preprocessImage(PreProcessor preProcessor) {
    List<Mat> images = preProcessor.getImages();
    List<Mat> processed = new ArrayList<Mat>();
    preProcessor.setEyes();//from  w  ww. j a va2 s  .c o  m
    Eyes[] eyes = preProcessor.getEyes();
    if (eyes == null || eyes[0] == null) {
        return null;
    }
    for (int i = 0; i < images.size(); i++) {
        Mat img = images.get(i);
        Eyes eye = eyes[i];
        double desiredLen = (DESIRED_LEFT_EYE_X - DESIRED_RIGHT_EYE_X) * img.cols();
        double scale = 0.9 * desiredLen / eye.getDist();
        MatOfFloat leftCenter = eye.getLeftCenter();
        MatOfFloat rightCenter = eye.getRightCenter();
        double centerX = ((leftCenter.get(0, 0)[0] + rightCenter.get(0, 0)[0]) / 2);
        double centerY = ((leftCenter.get(1, 0)[0] + rightCenter.get(1, 0)[0]) / 2);
        Mat rotMat = Imgproc.getRotationMatrix2D(new Point(centerX, centerY), eye.getAngle(), scale);
        rotMat.put(2, 0, img.cols() * 0.5 - centerX);
        rotMat.put(2, 1, img.rows() * DESIRED_RIGHT_EYE_Y - centerY);
        Imgproc.warpAffine(img, img, rotMat, new Size(img.cols(), img.rows()));
        processed.add(img);
    }
    preProcessor.setImages(processed);
    return preProcessor;
}

From source file:ch.zhaw.facerecognitionlibrary.Recognition.Eigenfaces.java

License:Open Source License

public String recognize(Mat img, String expectedLabel) {
    // Ignore/*from   w ww.j a va2s  .c  om*/
    img = img.reshape(1, 1);
    // Subtract mean
    img.convertTo(img, CvType.CV_32F);
    Core.subtract(img, Psi, img);
    // Project to subspace
    Mat projected = getFeatureVector(img);
    // Save all points of image for tSNE
    img.convertTo(img, CvType.CV_8U);
    addImage(projected, expectedLabel, true);
    //addImage(projected, expectedLabel);
    Mat distance = new Mat(Omega.rows(), 1, CvType.CV_64FC1);
    for (int i = 0; i < Omega.rows(); i++) {
        double dist = Core.norm(projected.row(0), Omega.row(i), Core.NORM_L2);
        distance.put(i, 0, dist);
    }
    Mat sortedDist = new Mat(Omega.rows(), 1, CvType.CV_8UC1);
    Core.sortIdx(distance, sortedDist, Core.SORT_EVERY_COLUMN + Core.SORT_ASCENDING);
    // Give back the name of the found person
    int index = (int) (sortedDist.get(0, 0)[0]);
    return labelMap.getKey(labelList.get(index));
}

From source file:Clases.Analizador.java

public BufferedImage analizarCatarata(Mat img) {
    double[] pupila = segmentador.segmentarPupila(img);
    double[] clase = { 99.8125, 150.7500, 150.8125 };
    double areaPupila = Math.PI * Math.pow(pupila[2], 2);
    int acumulador = 0;
    //Core.circle(img, new Point(pupila[0], pupila[1]), (int) pupila[2], new Scalar(255, 0, 0), 3);
    //Ventana v1 = new Ventana(convertir(max), 1, 0);
    //Ventana v2 = new Ventana(convertir(img), 3, 0);
    Size sizeA = img.size();/*from   www . jav a  2  s . co  m*/
    Mat max = img.clone();

    double[] data;
    for (int i = 0; i < sizeA.height; i++) {
        for (int j = 0; j < sizeA.width; j++) {
            if ((Math.pow(pupila[0] - j, 2) + Math.pow(pupila[1] - i, 2) <= Math.pow(pupila[2], 2))) {
                data = img.get(i, j);
                double res = Math.sqrt(Math.pow(clase[0] - data[2], 2) + Math.pow(clase[1] - data[1], 2)
                        + Math.pow(clase[2] - data[0], 2));
                if (res < 60) {
                    data[0] = 0;
                    data[1] = 255;
                    data[2] = 0;
                    acumulador++;
                }
                max.put(i, j, data);
            }
        }
    }
    resultadoCatarata = (acumulador * 100) / areaPupila;
    resultadoCatarata = (double) ((int) (resultadoCatarata * 100.00) / 100);
    //Core.circle(imagen, new Point(pupila[0], pupila[1]), (int) pupila[2], new Scalar(255, 0, 0), 3);
    //Ventana v1 = new Ventana(segmentador.convertir(max), 0, 0);
    //Ventana v2 = new Ventana(convertir(imagen), 2, 0);
    return segmentador.Mat2BufferedImage(max);
}

From source file:Clases.Segmentador.java

public Mat detectaPterigion(Mat img_ana, int val1, int val2, int val3) {
    int r = 200, g = 125, b = 115;
    for (int y = 0; y < img_ana.rows(); y++) {
        for (int x = 0; x < img_ana.cols(); x++) {
            double[] color = img_ana.get(y, x);
            if (color[2] >= r - val1 && color[2] <= r + val1 && color[1] >= g - val2 && color[1] <= g + val2
                    && color[0] >= b - val3 && color[0] <= b + val3) {
                color[0] = 0;/*  ww w. j  a  v  a  2 s . co m*/
                color[1] = 255;
                color[2] = 255;
            }
            img_ana.put(y, x, color);
        }
    }
    return img_ana;
}

From source file:Clases.Segmentador.java

public int detectaEsclerotica(Mat img_ana, int val1, int val2, int val3) {
    int r = 190, g = 187, b = 181, area = 0;
    for (int y = 0; y < img_ana.rows(); y++) {
        for (int x = 0; x < img_ana.cols(); x++) {
            double[] color = img_ana.get(y, x);
            if (color[2] >= r - val1 && color[2] <= r + val1 && color[1] >= g - val2 && color[1] <= g + val2
                    && color[0] >= b - val3 && color[0] <= b + val3) {
                area++;//from  w w w.  ja v a2 s  .  com
            }
            img_ana.put(y, x, color);
        }
    }
    return area;
}

From source file:Clases.Segmentador.java

public Mat dameLaDona(Mat img1) {
    double[] iris = segmentarIris(img1);
    double[] pupila = segmentarPupila(img1);

    Size sizeA = img1.size();/*from   www .j a  v a2 s  .  c  o m*/
    Mat max = img1.clone();

    double[] data;
    for (int i = 0; i < sizeA.height; i++) {
        for (int j = 0; j < sizeA.width; j++) {
            if ((Math.pow(iris[0] - j, 2) + Math.pow(iris[1] - i, 2) >= Math.pow(iris[2], 2))
                    || (Math.pow(pupila[0] - j, 2) + Math.pow(pupila[1] - i, 2) <= Math.pow(pupila[2], 2))) {
                data = img1.get(i, j);
                data[0] = 255;
                data[1] = 255;
                data[2] = 255;
                max.put(i, j, data);
            }

        }
    }
    return max;
}

From source file:Clases.Segmentador.java

public Mat limitaIris(Mat img1) {

    double[] iris = segmentarIris(img1);
    iris[2] = iris[2] * 0.8;/*from w w w.j av  a  2 s  . co  m*/
    Size sizeA = img1.size();
    Mat max = img1.clone();

    double[] data;
    for (int i = 0; i < sizeA.height; i++) {
        for (int j = 0; j < sizeA.width; j++) {
            if ((Math.pow(iris[0] - j, 2) + Math.pow(iris[1] - i, 2) >= Math.pow(iris[2], 2))) {
                data = img1.get(i, j);
                data[0] = 255;
                data[1] = 255;
                data[2] = 255;
                max.put(i, j, data);
            }

        }
    }
    return max;
}