Example usage for org.opencv.core Mat get

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

Introduction

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

Prototype

public double[] get(int row, int col) 

Source Link

Usage

From source file:uom.research.thalassemia.logic.BloodCellDataProcessor.java

/**
 * process circular blood cell data including both pallor and red blood
 * cells.// ww  w. jav  a  2 s . com
 *
 * @param currentSelection Mat of selected
 */
public void circularBloodCellsProcesser(final Mat currentSelection) {

    if (currentSelection != null) {
        if (currentSelection == circularBloodCells) {
            circularBloodCellsArray = new ArrayList<>();
        } else if (currentSelection == pallorBloodCells) {
            pallorBloodCellsArray = new ArrayList<>();
        }
        getMinMaxDiameter(currentSelection);
        double sgf = 0;
        if (minDiameter != 0) {
            //calculate shape geometric factor
            sgf = maxDiameter / minDiameter;
        }
        Map<Point, Double> points = getPallorBloodCellsPointList();
        double[] circles;
        double x, y, r, area, perimeter, diameter, deviationValue, areaPreparation;
        for (int a = 0; a < currentSelection.cols(); a++) {
            areaPreparation = 0;
            circles = currentSelection.get(0, a);
            x = circles[0];
            y = circles[1];
            r = Math.round(circles[2]);

            //get area value
            area = calculateArea(r);
            //get perimeter value
            perimeter = calculatePerimeter(r);
            //get diameter value
            diameter = calculateDiameter(area, perimeter);
            // calculate deviational value
            deviationValue = sgf / area;

            Point point = new Point(x, y);
            if (points.containsKey(point)) {
                areaPreparation = calculateArea(points.get(point)) / area;
            }
            Object[] ob = { (a + 1), x, y, r, Validator.formatDouble(perimeter), Validator.formatDouble(area),
                    Validator.formatDouble(diameter), Validator.formatDouble(deviationValue),
                    Validator.formatDouble(areaPreparation) };

            if (currentSelection == circularBloodCells) {
                totalBloodCellArea += area;
                circularBloodCellsArray.add(ob);
            } else if (currentSelection == pallorBloodCells) {
                totalPallarArea += area;
                pallorBloodCellsArray.add(ob);
            } else {
                totalEllipseArea += area;
            }
        }
    }
}

From source file:uom.research.thalassemia.ui.HomeCellCountAnalyzer.java

/**
 * convert Circles Map To CirclesList.// w ww  .j a v  a  2  s  .  co m
 */
private void convertCirclesMapToCirclesList() {
    Mat circles = bcm.getCircles();
    circlesList = new ArrayList<>();
    double[] circle;
    double x, y, r, area, perimeter;
    for (int a = 0; a < circles.cols(); a++) {
        circle = circles.get(0, a);
        x = circle[0];
        y = circle[1];
        r = Math.round(circle[2]);
        area = fi * r * r;
        perimeter = 2 * fi * r;
        circlesList.add(new Circle((int) x, (int) y, (int) r, perimeter, area));
    }
}

From source file:usefull.ColourQuery.java

License:LGPL

public static void main(String[] args) {

    // load the Core OpenCV library by name

    System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

    // load an image from file (read and decode JPEG file)

    Mat inputImage = Highgui.imread("files/lena1.png");

    // create a display window using an Imshow object

    Imshow ims1 = new Imshow("My Image");

    // display some colour values (note the BGR colour channel order)

    double[] bgr = inputImage.get(0, 0);
    System.out.println("colour @ (0,0) = B: " + bgr[0] + " G: " + bgr[1] + " R: " + bgr[2]);

    bgr = inputImage.get(50, 50);/*from ww  w  .j  av a 2  s. c  o m*/
    System.out.println("colour @ (50,50) = B: " + bgr[0] + " G: " + bgr[1] + " R: " + bgr[2]);

    bgr = inputImage.get(100, 25);
    System.out.println("colour @ (100,25) = B: " + bgr[0] + " G: " + bgr[1] + " R: " + bgr[2]);

    bgr = inputImage.get(17, 234);
    System.out.println("colour @ (17,234) = B: " + bgr[0] + " G: " + bgr[1] + " R: " + bgr[2]);

    // set some pixel values to blue (i.e. BGR = (255,0,0)

    double[] colour = new double[3];
    colour[0] = 255;
    colour[1] = 0;
    colour[2] = 0;
    inputImage.put(25, 25, colour);
    inputImage.put(25, 24, colour);
    inputImage.put(25, 23, colour);
    inputImage.put(25, 22, colour);
    // ...

    // display image

    ims1.showImage(inputImage);

}

From source file:usefull.LoopImageFiles.java

License:LGPL

public static void main(String[] args) throws InterruptedException {

    // define the path to my files - clearly and obviously 

    // **** CHANGE THIS TO YOUR OWN DIRECTORY ****/

    String IMAGE_FILES_DIRECTORY_PATH = "files/combinations/";

    // load the Core OpenCV library by name

    System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

    // create a display window using an Imshow object

    Imshow ims = new Imshow("Next Image ...");

    Size frame = new Size(704, 480);

    List<Mat> backgroundImg = new ArrayList<Mat>();
    backgroundImg.add(Highgui.imread("files/1.png"));
    backgroundImg.add(Highgui.imread("files/2.png"));
    backgroundImg.add(Highgui.imread("files/3.png"));
    backgroundImg.add(Highgui.imread("files/4.png"));
    backgroundImg.add(Highgui.imread("files/5.png"));
    backgroundImg.add(Highgui.imread("files/6.png"));
    backgroundImg.add(Highgui.imread("files/7.png"));

    for (Mat bgImg : backgroundImg) {
        Mat grey = new Mat();
        Imgproc.cvtColor(bgImg, grey, Imgproc.COLOR_BGR2GRAY);
        Imgproc.adaptiveThreshold(grey, bgImg, 255, Imgproc.ADAPTIVE_THRESH_MEAN_C, Imgproc.THRESH_BINARY_INV,
                7, 10);//from  w  ww . ja  v  a 2 s.c  om

        Size ksize = new Size(21, 21);
        Mat kernel = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, ksize);

        Imgproc.morphologyEx(bgImg, bgImg, Imgproc.MORPH_CLOSE, kernel);

        Size filter = new Size(21, 21);
        Imgproc.GaussianBlur(bgImg, bgImg, filter, 0, 0, Imgproc.BORDER_DEFAULT);
    }

    BackgroundSubtractorMOG MoG = new BackgroundSubtractorMOG();

    List<Mat> fg_masks = new ArrayList<Mat>();

    Imshow imsS = new Imshow("input ... ");
    Imshow imsF = new Imshow("background");

    // get a listing of files in that directory
    Imshow ims_diff = new Imshow("Difference");
    File dir = new File(IMAGE_FILES_DIRECTORY_PATH);
    File[] directoryListing = dir.listFiles();
    if (directoryListing != null) {
        for (File imgFile : directoryListing) {

            // if the file name ends with .jpg (JPEG) or .png (Portable Network Graphic)

            if ((imgFile.getName().endsWith(".png")) || (imgFile.getName().endsWith(".jpg"))) {
                // load an image from each file (read and decode image file)
                Mat inputImage = new Mat();
                Mat iImg = new Mat();
                Size filter = new Size(15, 15);
                iImg = Highgui.imread(IMAGE_FILES_DIRECTORY_PATH + "/" + imgFile.getName());
                Imgproc.resize(iImg, inputImage, frame);
                Imgproc.GaussianBlur(inputImage, inputImage, filter, 0, 0, Imgproc.BORDER_DEFAULT);
                //Imgproc.GaussianBlur(inputImage, inputImage, filter, 0, 0, Imgproc.BORDER_DEFAULT);
                //Imgproc.GaussianBlur(inputImage, inputImage, filter, 0, 0, Imgproc.BORDER_DEFAULT);
                Imgproc.medianBlur(inputImage, inputImage, 9);

                Mat fg_mask = new Mat();

                Mat fg_mask1 = new Mat();
                Mat fg_mask2 = new Mat();
                Mat fg_mask3 = new Mat();
                Mat fg_mask4 = new Mat();
                Mat fg_mask5 = new Mat();
                Mat fg_mask6 = new Mat();
                Mat fg_mask7 = new Mat();

                ArrayList<Integer> countAll = new ArrayList<Integer>();

                for (int i = 0; i < 7; i++) {
                    // add it to the background model with a learning rate of 0.1

                    MoG.apply(inputImage, backgroundImg.get(i), 0.1);

                    // extract the foreground mask (1 = foreground / 0 - background), 
                    // and convert/expand it to a 3-channel version of the same 

                    Imgproc.cvtColor(backgroundImg.get(i), backgroundImg.get(i), Imgproc.COLOR_GRAY2BGR);

                }

                // logically AND it with the original frame to extract colour 
                // pixel only in the foreground regions

                Core.bitwise_and(inputImage, backgroundImg.get(0), fg_mask1);
                Core.bitwise_and(inputImage, backgroundImg.get(1), fg_mask2);
                Core.bitwise_and(inputImage, backgroundImg.get(2), fg_mask3);
                Core.bitwise_and(inputImage, backgroundImg.get(3), fg_mask4);
                Core.bitwise_and(inputImage, backgroundImg.get(4), fg_mask5);
                Core.bitwise_and(inputImage, backgroundImg.get(5), fg_mask6);
                Core.bitwise_and(inputImage, backgroundImg.get(6), fg_mask7);

                for (int i = 0; i < 7; i++) {
                    countAll.add(countP(backgroundImg.get(i)));
                }

                double meanPixels = average(countAll);
                double[] temp = new double[5];
                for (int i = 0; i < 5; i++) {
                    temp[i] = Math.abs(countAll.get(i) - meanPixels);
                }

                double min = temp[0];
                int mark = 0;
                for (int i = 1; i < 5; i++) {
                    if (temp[i] < min) {
                        mark = i;
                        min = temp[i];
                    }
                }

                fg_mask = backgroundImg.get(mark);

                // Create a contour ZONE B top-left
                Point[] contourPoints1 = new Point[5];
                contourPoints1[0] = new Point(55, 22);
                contourPoints1[1] = new Point(200, 22);
                contourPoints1[2] = new Point(330, 175);
                contourPoints1[3] = new Point(200, 430);
                contourPoints1[4] = new Point(55, 110);

                // convert it to a java list of OpenCV MatOfPoint
                // objects as this is what the draw function requires

                MatOfPoint contour1 = new MatOfPoint(contourPoints1);
                List<MatOfPoint> contourList1 = new ArrayList<MatOfPoint>();
                contourList1.add(contour1);

                // Create a contour ZONE C top-right
                Point[] contourPoints2 = new Point[4];

                contourPoints2[0] = new Point(55, 130);
                contourPoints2[1] = new Point(195, 435);
                contourPoints2[2] = new Point(125, 570);
                contourPoints2[3] = new Point(55, 340);

                MatOfPoint contour2 = new MatOfPoint(contourPoints2);
                List<MatOfPoint> contourList2 = new ArrayList<MatOfPoint>();
                contourList2.add(contour2);

                // Create a contour ZONE A
                Point[] contourPoints3 = new Point[5];

                contourPoints3[0] = new Point(420, 22);
                contourPoints3[1] = new Point(465, 22);
                contourPoints3[2] = new Point(463, 295);
                contourPoints3[3] = new Point(190, 695);
                contourPoints3[4] = new Point(65, 695);

                MatOfPoint contour3 = new MatOfPoint(contourPoints3);
                List<MatOfPoint> contourList3 = new ArrayList<MatOfPoint>();
                contourList3.add(contour3);

                // Create a contour ZONE C button
                Point[] contourPoints4 = new Point[4];

                contourPoints4[0] = new Point(310, 545);
                contourPoints4[1] = new Point(463, 320);
                contourPoints4[2] = new Point(463, 695);
                contourPoints4[3] = new Point(400, 695);

                MatOfPoint contour4 = new MatOfPoint(contourPoints4);
                List<MatOfPoint> contourList4 = new ArrayList<MatOfPoint>();
                contourList4.add(contour4);

                // Create a contour ZONE b right
                Point[] contourPoints5 = new Point[3];

                contourPoints5[0] = new Point(300, 555);
                contourPoints5[2] = new Point(385, 695);
                contourPoints5[1] = new Point(200, 695);

                MatOfPoint contour5 = new MatOfPoint(contourPoints5);
                List<MatOfPoint> contourList5 = new ArrayList<MatOfPoint>();
                contourList5.add(contour5);

                // Create a contour ZONE RACT
                Point[] contourPoints6 = new Point[4];

                contourPoints6[0] = new Point(210, 22);
                contourPoints6[1] = new Point(285, 22);
                contourPoints6[2] = new Point(275, 100);
                contourPoints6[3] = new Point(225, 100);

                MatOfPoint contour6 = new MatOfPoint(contourPoints6);
                List<MatOfPoint> contourList6 = new ArrayList<MatOfPoint>();
                contourList1.add(contour6);

                // Create a contour ZONE RACT
                Point[] contourPoints7 = new Point[4];

                contourPoints7[0] = new Point(400, 22);
                contourPoints7[1] = new Point(465, 22);
                contourPoints7[2] = new Point(465, 180);
                contourPoints7[3] = new Point(400, 125);

                MatOfPoint contour7 = new MatOfPoint(contourPoints7);
                List<MatOfPoint> contourList7 = new ArrayList<MatOfPoint>();
                contourList7.add(contour7);

                // Create a contour ZONE RACT
                Point[] contourPoints8 = new Point[3];

                contourPoints8[0] = new Point(0, 340);
                contourPoints8[1] = new Point(0, 695);
                contourPoints8[2] = new Point(150, 695);

                MatOfPoint contour8 = new MatOfPoint(contourPoints8);
                List<MatOfPoint> contourList8 = new ArrayList<MatOfPoint>();
                contourList8.add(contour8);

                //put point to the list
                List<Point> list1 = new ArrayList<Point>();
                List<Point> list2 = new ArrayList<Point>();
                List<Point> list3 = new ArrayList<Point>();
                List<Point> list4 = new ArrayList<Point>();
                List<Point> list5 = new ArrayList<Point>();
                List<Point> list6 = new ArrayList<Point>();
                List<Point> list7 = new ArrayList<Point>();
                List<Point> list8 = new ArrayList<Point>();

                Point[] contourPoints10 = new Point[5];

                contourPoints10[0] = new Point(22, 55);
                contourPoints10[1] = new Point(22, 200);
                contourPoints10[2] = new Point(175, 330);
                contourPoints10[3] = new Point(430, 200);
                contourPoints10[4] = new Point(110, 55);

                // convert it to a java list of OpenCV MatOfPoint
                // objects as this is what the draw function requires

                MatOfPoint contour10 = new MatOfPoint(contourPoints10);
                List<MatOfPoint> contourList10 = new ArrayList<MatOfPoint>();
                contourList10.add(contour10);

                // Create a contour ZONE C top-right
                Point[] contourPoints20 = new Point[4];

                contourPoints20[0] = new Point(130, 55);
                contourPoints20[1] = new Point(435, 195);
                contourPoints20[2] = new Point(570, 125);
                contourPoints20[3] = new Point(340, 55);

                MatOfPoint contour20 = new MatOfPoint(contourPoints20);
                List<MatOfPoint> contourList20 = new ArrayList<MatOfPoint>();
                contourList20.add(contour20);

                // Create a contour ZONE A
                Point[] contourPoints30 = new Point[5];

                contourPoints30[0] = new Point(22, 420);
                contourPoints30[1] = new Point(22, 465);
                contourPoints30[2] = new Point(295, 463);
                contourPoints30[3] = new Point(695, 190);
                contourPoints30[4] = new Point(695, 65);

                MatOfPoint contour30 = new MatOfPoint(contourPoints30);
                List<MatOfPoint> contourList30 = new ArrayList<MatOfPoint>();
                contourList30.add(contour30);

                // Create a contour ZONE C button
                Point[] contourPoints40 = new Point[4];

                contourPoints40[0] = new Point(545, 310);
                contourPoints40[1] = new Point(320, 463);
                contourPoints40[2] = new Point(695, 463);
                contourPoints40[3] = new Point(695, 400);

                MatOfPoint contour40 = new MatOfPoint(contourPoints40);
                List<MatOfPoint> contourList40 = new ArrayList<MatOfPoint>();
                contourList40.add(contour40);

                // Create a contour ZONE b right
                Point[] contourPoints50 = new Point[3];

                contourPoints50[0] = new Point(555, 300);
                contourPoints50[2] = new Point(695, 385);
                contourPoints50[1] = new Point(695, 200);

                MatOfPoint contour50 = new MatOfPoint(contourPoints50);
                List<MatOfPoint> contourList50 = new ArrayList<MatOfPoint>();
                contourList50.add(contour50);

                // Create a contour ZONE RACT
                Point[] contourPoints60 = new Point[4];

                contourPoints60[0] = new Point(22, 210);
                contourPoints60[1] = new Point(22, 285);
                contourPoints60[2] = new Point(100, 275);
                contourPoints60[3] = new Point(100, 225);

                MatOfPoint contour60 = new MatOfPoint(contourPoints60);
                List<MatOfPoint> contourList60 = new ArrayList<MatOfPoint>();
                contourList60.add(contour60);

                // Create a contour ZONE RACT
                Point[] contourPoints70 = new Point[4];

                contourPoints70[0] = new Point(22, 400);
                contourPoints70[1] = new Point(22, 465);
                contourPoints70[2] = new Point(180, 465);
                contourPoints70[3] = new Point(125, 400);

                MatOfPoint contour70 = new MatOfPoint(contourPoints70);
                List<MatOfPoint> contourList70 = new ArrayList<MatOfPoint>();
                contourList70.add(contour70);

                // Create a contour ZONE RACT
                Point[] contourPoints80 = new Point[3];

                contourPoints80[0] = new Point(340, 0);
                contourPoints80[1] = new Point(695, 0);
                contourPoints80[2] = new Point(695, 150);

                MatOfPoint contour80 = new MatOfPoint(contourPoints80);
                List<MatOfPoint> contourList80 = new ArrayList<MatOfPoint>();
                contourList80.add(contour80);

                Imgproc.drawContours(fg_mask, contourList10, -1, new Scalar(255, 255, 255), 2);
                Imgproc.drawContours(fg_mask, contourList20, -1, new Scalar(255, 255, 255), 2);
                Imgproc.drawContours(fg_mask, contourList30, -1, new Scalar(255, 255, 255), 2);
                Imgproc.drawContours(fg_mask, contourList40, -1, new Scalar(255, 255, 255), 2);
                Imgproc.drawContours(fg_mask, contourList50, -1, new Scalar(255, 255, 255), 2);
                Imgproc.drawContours(fg_mask, contourList60, -1, new Scalar(255, 255, 255), 2);
                Imgproc.drawContours(fg_mask, contourList70, -1, new Scalar(255, 255, 255), 2);
                Imgproc.drawContours(fg_mask, contourList80, -1, new Scalar(255, 255, 255), 2);

                Point point = new Point();
                for (int row = 0; row < fg_mask.rows(); row++) {
                    for (int col = 0; col < fg_mask.cols(); col++) {

                        point = new Point(row, col);
                        // perform point in polygon test
                        MatOfPoint2f contourPoint1f = new MatOfPoint2f(contourPoints1);
                        MatOfPoint2f contourPoint2f = new MatOfPoint2f(contourPoints2);
                        MatOfPoint2f contourPoint3f = new MatOfPoint2f(contourPoints3);
                        MatOfPoint2f contourPoint4f = new MatOfPoint2f(contourPoints4);
                        MatOfPoint2f contourPoint5f = new MatOfPoint2f(contourPoints5);
                        MatOfPoint2f contourPoint6f = new MatOfPoint2f(contourPoints6);
                        MatOfPoint2f contourPoint7f = new MatOfPoint2f(contourPoints7);
                        MatOfPoint2f contourPoint8f = new MatOfPoint2f(contourPoints8);

                        if (Imgproc.pointPolygonTest(contourPoint1f, point, false) >= 0) {
                            list1.add(point);
                        }
                        if (Imgproc.pointPolygonTest(contourPoint2f, point, false) >= 0) {
                            list2.add(point);
                        }
                        if (Imgproc.pointPolygonTest(contourPoint3f, point, false) >= 0) {
                            list3.add(point);
                        }
                        if (Imgproc.pointPolygonTest(contourPoint4f, point, false) >= 0) {
                            list4.add(point);
                        }
                        if (Imgproc.pointPolygonTest(contourPoint5f, point, false) >= 0) {
                            list5.add(point);
                        }
                        if (Imgproc.pointPolygonTest(contourPoint6f, point, false) >= 0) {
                            list6.add(point);
                        }
                        if (Imgproc.pointPolygonTest(contourPoint7f, point, false) >= 0) {
                            list7.add(point);
                        }
                        if (Imgproc.pointPolygonTest(contourPoint8f, point, false) >= 0) {
                            list8.add(point);
                        }

                    }

                }

                boolean flag[] = { false, false, false, false, false, false, false };

                int events = 0;
                String events_name = "";

                int count1 = 0;
                for (Point p : list1) {
                    int x1 = (int) p.x;
                    int y1 = (int) p.y;
                    double[] n = fg_mask.get(x1, y1);
                    double value1 = n[0];
                    if (value1 == 255.0) {
                        count1++;
                    }
                }
                System.out.println(" 1 " + count1);

                if (count1 > 2000) {
                    flag[0] = true;
                }

                int count2 = 0;
                for (Point p : list2) {
                    int x2 = (int) p.x;
                    int y2 = (int) p.y;
                    double[] n = fg_mask.get(x2, y2);
                    double value2 = n[0];
                    if (value2 == 255.0) {
                        count2++;
                    }
                }
                System.out.println(" 2 " + count2);

                if (count2 > 1500) {
                    flag[1] = true;
                }

                int count3 = 0;
                for (Point p : list3) {
                    int x3 = (int) p.x;
                    int y3 = (int) p.y;
                    double[] n = fg_mask.get(x3, y3);
                    double value3 = n[0];
                    if (value3 == 255.0) {
                        count3++;
                    }
                }
                System.out.println(" 3 " + count3);

                if (count3 > 20000) {
                    flag[4] = true;
                }
                if (count3 > 4000) {
                    flag[2] = true;
                }

                int count4 = 0;
                for (Point p : list4) {
                    int x4 = (int) p.x;
                    int y4 = (int) p.y;
                    double[] n = fg_mask.get(x4, y4);
                    double value4 = n[0];
                    if (value4 == 255.0) {
                        count4++;
                    }
                }
                System.out.println(" 4 " + count4);

                if (count4 > 1700) {
                    flag[1] = true;
                }

                int count5 = 0;
                for (Point p : list5) {
                    int x5 = (int) p.x;
                    int y5 = (int) p.y;
                    double[] n = fg_mask.get(x5, y5);
                    double value5 = n[0];
                    if (value5 == 255.0) {
                        count5++;
                    }
                }
                System.out.println(" 5 " + count5);

                if (count5 > 1000) {
                    flag[0] = true;
                }

                int count6 = 0;
                for (Point p : list6) {
                    int x6 = (int) p.x;
                    int y6 = (int) p.y;
                    double[] n = fg_mask.get(x6, y6);
                    double value6 = n[0];
                    if (value6 == 255.0) {
                        count6++;
                    }
                }
                System.out.println(" 6 " + count6);

                if (count6 > 750) {
                    flag[3] = true;
                }

                int count7 = 0;
                for (Point p : list7) {
                    int x7 = (int) p.x;
                    int y7 = (int) p.y;
                    double[] n = fg_mask.get(x7, y7);
                    double value7 = n[0];
                    if (value7 == 255.0) {
                        count7++;
                    }
                }
                System.out.println(" 7 " + count7);

                if (count7 > 1100) {
                    flag[5] = true;
                }

                int count8 = 0;
                for (Point p : list8) {
                    int x8 = (int) p.x;
                    int y8 = (int) p.y;
                    double[] n = fg_mask.get(x8, y8);
                    double value8 = n[0];
                    if (value8 == 255.0) {
                        count8++;
                    }
                }
                System.out.println(" 8 " + count8);

                if (count8 > 2000) {
                    flag[6] = true;
                }

                imsS.showImage(inputImage);
                imsF.showImage(fg_mask);
                imsF.showImage(backgroundImg.get(0));
                System.out.print(imgFile.getName() + " ");

                //Identifying events
                if ((!flag[0]) && (!flag[1]) && (!flag[2]) && (!flag[3]) && (!flag[4])) {
                    System.out.print("Empty ");
                } else if (flag[4] || (!flag[4] && flag[5]) || (!flag[4] && flag[6])) {
                    System.out.print("Train ");
                }

                if (flag[0] && !(flag[4] || (!flag[4] && flag[5]) || (!flag[4] && flag[6]))) {
                    System.out.print("Enter ");
                }

                if (flag[1] && !(flag[4] || (!flag[4] && flag[5]) || (!flag[4] && flag[6]))) {
                    System.out.print("Leave ");
                }

                if ((flag[2] && (!flag[5]) && (!flag[6]))
                        && !(flag[3] && (!(flag[4] || (!flag[4] && flag[5]) || (!flag[4] && flag[6]))))) {
                    System.out.print("On track ");
                }

                if (flag[3] && (!(flag[4] || (!flag[4] && flag[5]) || (!flag[4] && flag[6])))) {
                    System.out.print("Barrier");
                }

                System.out.println();

                Thread.sleep(40);
            }
        }
    } else {

        System.out.println("Could not get listing for directory: " + IMAGE_FILES_DIRECTORY_PATH);
    }
}

From source file:usefull.LoopImageFiles.java

License:LGPL

public static int countP(Mat f) {
    int countAll = 0;
    for (int m = 0; m < f.cols(); m++) {
        for (int n = 0; n < f.rows(); n++) {
            double[] t = f.get(n, m);
            double value2 = t[0];
            if (value2 == 255.0) {
                countAll++;/*ww w .  ja  va 2  s.  co  m*/
            }
        }
    }
    return countAll;
}

From source file:video.PictureAnalyser.java

public void Calibrate(BufferedImage img) {
    Mat frameMat = new Mat();
    frameMat = PictureView.bufferedImageToMat(img);
    pic = blur(frameMat, 3);//  w  w  w.jav  a  2s . c  o m
    Mat imgHSV = new Mat();
    Imgproc.cvtColor(pic, imgHSV, Imgproc.COLOR_RGB2HSV);
    int height = 10;
    int width = 10;
    int hue = 0;
    int saturation = 0;
    int value = 0;
    for (int i = 0; i < height; i++) {
        for (int j = 0; j < width; j++) {
            double[] testColor = imgHSV.get((imgHSV.height() / 2) - (width / 2) + i,
                    (imgHSV.width() / 2) - (height / 2) + j);
            if (testColor[0] > 140)
                testColor[0] = testColor[0] - 180;
            hue = hue + (int) testColor[0];
            saturation = saturation + (int) testColor[1];
            value = value + (int) testColor[2];

        }
    }
    /*
     * Green values hue=55; saturation =240; value= 70;
     */
    hue = hue / (height * width);
    saturation = saturation / (height * width);
    value = value / (height * width);
    this.color.get(0).val[0] = hue - 5;
    this.color.get(0).val[1] = saturation - 40;
    this.color.get(0).val[2] = value - 40;
    this.color.get(1).val[0] = hue + 5;
    this.color.get(1).val[1] = saturation + 40;
    this.color.get(1).val[2] = value + 40;

}

From source file:View.Signature.java

public static int sift(String routeVal, String route, String n_img1, String n_img2, String extension) {

    String bookObject = routeVal + n_img2 + extension;
    String bookScene = route + n_img1 + extension;

    //System.out.println("Iniciando SIFT");
    //java.lang.System.out.print("Abriendo imagenes | ");
    Mat objectImage = Highgui.imread(bookObject, Highgui.CV_LOAD_IMAGE_COLOR);
    Mat sceneImage = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR);

    MatOfKeyPoint objectKeyPoints = new MatOfKeyPoint();
    FeatureDetector featureDetector = FeatureDetector.create(FeatureDetector.SIFT);
    //java.lang.System.out.print("Encontrar keypoints con SIFT | ");  
    featureDetector.detect(objectImage, objectKeyPoints);
    KeyPoint[] keypoints = objectKeyPoints.toArray();

    MatOfKeyPoint objectDescriptors = new MatOfKeyPoint();
    DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.SIFT);
    //java.lang.System.out.print("Computando descriptores | ");  
    descriptorExtractor.compute(objectImage, objectKeyPoints, objectDescriptors);

    // Create the matrix for output image.   
    Mat outputImage = new Mat(objectImage.rows(), objectImage.cols(), Highgui.CV_LOAD_IMAGE_COLOR);
    Scalar newKeypointColor = new Scalar(255, 0, 0);

    //java.lang.System.out.print("Dibujando keypoints en imagen base | ");  
    Features2d.drawKeypoints(objectImage, objectKeyPoints, outputImage, newKeypointColor, 0);

    // Match object image with the scene image  
    MatOfKeyPoint sceneKeyPoints = new MatOfKeyPoint();
    MatOfKeyPoint sceneDescriptors = new MatOfKeyPoint();
    //java.lang.System.out.print("Detectando keypoints en imagen base | ");
    featureDetector.detect(sceneImage, sceneKeyPoints);
    //java.lang.System.out.print("Computando descriptores en imagen base | ");
    descriptorExtractor.compute(sceneImage, sceneKeyPoints, sceneDescriptors);

    Mat matchoutput = new Mat(sceneImage.rows() * 2, sceneImage.cols() * 2, Highgui.CV_LOAD_IMAGE_COLOR);
    Scalar matchestColor = new Scalar(0, 255, 0);

    List<MatOfDMatch> matches = new LinkedList<MatOfDMatch>();
    DescriptorMatcher descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED);
    //java.lang.System.out.print("Encontrando matches entre imagenes | ");  
    descriptorMatcher.knnMatch(objectDescriptors, sceneDescriptors, matches, 2);

    //java.lang.System.out.println("Calculando buenos matches");
    LinkedList<DMatch> goodMatchesList = new LinkedList<DMatch>();

    float nndrRatio = 0.7f;
    java.lang.System.out.println(matches.size());
    for (int i = 0; i < matches.size(); i++) {
        MatOfDMatch matofDMatch = matches.get(i);
        DMatch[] dmatcharray = matofDMatch.toArray();
        DMatch m1 = dmatcharray[0];/* ww w  .ja  v a  2 s .  c o m*/
        DMatch m2 = dmatcharray[1];

        if (m1.distance <= m2.distance * nndrRatio) {
            goodMatchesList.addLast(m1);

        }
    }

    if (goodMatchesList.size() >= 7) {
        //java.lang.System.out.println("Match enontrado!!! Matches: "+goodMatchesList.size());
        //if(goodMatchesList.size()>max){

        //cambio = 1;
        //}    

        List<KeyPoint> objKeypointlist = objectKeyPoints.toList();
        List<KeyPoint> scnKeypointlist = sceneKeyPoints.toList();

        LinkedList<Point> objectPoints = new LinkedList<>();
        LinkedList<Point> scenePoints = new LinkedList<>();

        for (int i = 0; i < goodMatchesList.size(); i++) {
            objectPoints.addLast(objKeypointlist.get(goodMatchesList.get(i).queryIdx).pt);
            scenePoints.addLast(scnKeypointlist.get(goodMatchesList.get(i).trainIdx).pt);
        }

        MatOfPoint2f objMatOfPoint2f = new MatOfPoint2f();
        objMatOfPoint2f.fromList(objectPoints);
        MatOfPoint2f scnMatOfPoint2f = new MatOfPoint2f();
        scnMatOfPoint2f.fromList(scenePoints);

        Mat homography = Calib3d.findHomography(objMatOfPoint2f, scnMatOfPoint2f, Calib3d.RANSAC, 3);

        Mat obj_corners = new Mat(4, 1, CvType.CV_32FC2);
        Mat scene_corners = new Mat(4, 1, CvType.CV_32FC2);

        obj_corners.put(0, 0, new double[] { 0, 0 });
        obj_corners.put(1, 0, new double[] { objectImage.cols(), 0 });
        obj_corners.put(2, 0, new double[] { objectImage.cols(), objectImage.rows() });
        obj_corners.put(3, 0, new double[] { 0, objectImage.rows() });

        //System.out.println("Transforming object corners to scene corners...");  
        Core.perspectiveTransform(obj_corners, scene_corners, homography);

        Mat img = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR);

        Core.line(img, new Point(scene_corners.get(0, 0)), new Point(scene_corners.get(1, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(1, 0)), new Point(scene_corners.get(2, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(2, 0)), new Point(scene_corners.get(3, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(3, 0)), new Point(scene_corners.get(0, 0)),
                new Scalar(0, 255, 0), 4);

        //java.lang.System.out.println("Dibujando imagen de coincidencias");
        MatOfDMatch goodMatches = new MatOfDMatch();
        goodMatches.fromList(goodMatchesList);

        Features2d.drawMatches(objectImage, objectKeyPoints, sceneImage, sceneKeyPoints, goodMatches,
                matchoutput, matchestColor, newKeypointColor, new MatOfByte(), 2);
        String n_outputImage = route + "results\\" + n_img2 + "_outputImage_sift" + extension;
        String n_matchoutput = route + "results\\" + n_img2 + "_matchoutput_sift" + extension;
        String n_img = route + "results\\" + n_img2 + "_sift" + extension;
        Highgui.imwrite(n_outputImage, outputImage);
        Highgui.imwrite(n_matchoutput, matchoutput);
        //Highgui.imwrite(n_img, img);  
        java.lang.System.out.println(goodMatches.size().height);
        double result = goodMatches.size().height * 100 / matches.size();

        java.lang.System.out.println((int) result);
        //double result =goodMatches.size().height;
        if (result > 100) {
            return 100;
        } else if (result <= 100 && result > 85) {
            return 85;
        } else if (result <= 85 && result > 50) {
            return 50;
        } else if (result <= 50 && result > 25) {
            return 25;
        } else {
            return 0;
        }
    } else {
        //java.lang.System.out.println("Firma no encontrada");  
    }
    return 0;
    //System.out.println("Terminando SIFT");  
}

From source file:View.SignatureLib.java

public static int sift(String routeRNV, String routeAdherent) {

    String bookObject = routeAdherent;
    String bookScene = routeRNV;//  www  . j  a  v a 2  s .  co  m

    //System.out.println("Iniciando SIFT");
    //java.lang.System.out.print("Abriendo imagenes | ");
    Mat objectImage = Highgui.imread(bookObject, Highgui.CV_LOAD_IMAGE_COLOR);
    Mat sceneImage = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR);

    MatOfKeyPoint objectKeyPoints = new MatOfKeyPoint();
    FeatureDetector featureDetector = FeatureDetector.create(FeatureDetector.SIFT);
    //java.lang.System.out.print("Encontrar keypoints con SIFT | ");  
    featureDetector.detect(objectImage, objectKeyPoints);
    KeyPoint[] keypoints = objectKeyPoints.toArray();

    MatOfKeyPoint objectDescriptors = new MatOfKeyPoint();
    DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.SIFT);
    //java.lang.System.out.print("Computando descriptores | ");  
    descriptorExtractor.compute(objectImage, objectKeyPoints, objectDescriptors);

    // Create the matrix for output image.   
    Mat outputImage = new Mat(objectImage.rows(), objectImage.cols(), Highgui.CV_LOAD_IMAGE_COLOR);
    Scalar newKeypointColor = new Scalar(255, 0, 0);

    //java.lang.System.out.print("Dibujando keypoints en imagen base | ");  
    Features2d.drawKeypoints(objectImage, objectKeyPoints, outputImage, newKeypointColor, 0);

    // Match object image with the scene image  
    MatOfKeyPoint sceneKeyPoints = new MatOfKeyPoint();
    MatOfKeyPoint sceneDescriptors = new MatOfKeyPoint();
    //java.lang.System.out.print("Detectando keypoints en imagen base | ");
    featureDetector.detect(sceneImage, sceneKeyPoints);
    //java.lang.System.out.print("Computando descriptores en imagen base | ");
    descriptorExtractor.compute(sceneImage, sceneKeyPoints, sceneDescriptors);

    Mat matchoutput = new Mat(sceneImage.rows() * 2, sceneImage.cols() * 2, Highgui.CV_LOAD_IMAGE_COLOR);
    Scalar matchestColor = new Scalar(0, 255, 0);

    List<MatOfDMatch> matches = new LinkedList<MatOfDMatch>();
    DescriptorMatcher descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED);
    //java.lang.System.out.println(sceneDescriptors);  

    if (sceneDescriptors.empty()) {
        java.lang.System.out.println("Objeto no encontrado");
        return 0;
    }

    descriptorMatcher.knnMatch(objectDescriptors, sceneDescriptors, matches, 2);

    //java.lang.System.out.println("Calculando buenos matches");
    LinkedList<DMatch> goodMatchesList = new LinkedList<DMatch>();

    float nndrRatio = 0.7f;

    for (int i = 0; i < matches.size(); i++) {
        MatOfDMatch matofDMatch = matches.get(i);
        DMatch[] dmatcharray = matofDMatch.toArray();
        DMatch m1 = dmatcharray[0];
        DMatch m2 = dmatcharray[1];

        if (m1.distance <= m2.distance * nndrRatio) {
            goodMatchesList.addLast(m1);

        }
    }

    if (goodMatchesList.size() >= 7) {
        max = goodMatchesList.size();

        List<KeyPoint> objKeypointlist = objectKeyPoints.toList();
        List<KeyPoint> scnKeypointlist = sceneKeyPoints.toList();

        LinkedList<Point> objectPoints = new LinkedList<>();
        LinkedList<Point> scenePoints = new LinkedList<>();

        for (int i = 0; i < goodMatchesList.size(); i++) {
            objectPoints.addLast(objKeypointlist.get(goodMatchesList.get(i).queryIdx).pt);
            scenePoints.addLast(scnKeypointlist.get(goodMatchesList.get(i).trainIdx).pt);
        }

        MatOfPoint2f objMatOfPoint2f = new MatOfPoint2f();
        objMatOfPoint2f.fromList(objectPoints);
        MatOfPoint2f scnMatOfPoint2f = new MatOfPoint2f();
        scnMatOfPoint2f.fromList(scenePoints);

        Mat homography = Calib3d.findHomography(objMatOfPoint2f, scnMatOfPoint2f, Calib3d.RANSAC, 3);

        Mat obj_corners = new Mat(4, 1, CvType.CV_32FC2);
        Mat scene_corners = new Mat(4, 1, CvType.CV_32FC2);

        obj_corners.put(0, 0, new double[] { 0, 0 });
        obj_corners.put(1, 0, new double[] { objectImage.cols(), 0 });
        obj_corners.put(2, 0, new double[] { objectImage.cols(), objectImage.rows() });
        obj_corners.put(3, 0, new double[] { 0, objectImage.rows() });

        //System.out.println("Transforming object corners to scene corners...");  
        Core.perspectiveTransform(obj_corners, scene_corners, homography);

        Mat img = Highgui.imread(bookScene, Highgui.CV_LOAD_IMAGE_COLOR);

        Core.line(img, new Point(scene_corners.get(0, 0)), new Point(scene_corners.get(1, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(1, 0)), new Point(scene_corners.get(2, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(2, 0)), new Point(scene_corners.get(3, 0)),
                new Scalar(0, 255, 0), 4);
        Core.line(img, new Point(scene_corners.get(3, 0)), new Point(scene_corners.get(0, 0)),
                new Scalar(0, 255, 0), 4);

        //java.lang.System.out.println("Dibujando imagen de coincidencias");
        MatOfDMatch goodMatches = new MatOfDMatch();
        goodMatches.fromList(goodMatchesList);

        Features2d.drawMatches(objectImage, objectKeyPoints, sceneImage, sceneKeyPoints, goodMatches,
                matchoutput, matchestColor, newKeypointColor, new MatOfByte(), 2);

        String n_outputImage = "../pre/outputImage_sift.jpg";
        String n_matchoutput = "../pre/matchoutput_sift.jpg";
        String n_img = "../pre/sift.jpg";
        Highgui.imwrite(n_outputImage, outputImage);
        Highgui.imwrite(n_matchoutput, matchoutput);
        Highgui.imwrite(n_img, img);
        java.lang.System.out.println(goodMatches.size().height);
        double result = goodMatches.size().height;//*100/matches.size();
        int score = 0;
        if (result > 26) {
            score = 100;
        } else if (result <= 26 && result > 22) {
            score = 85;
        } else if (result <= 22 && result > 17) {
            score = 50;
        } else if (result <= 17 && result > 11) {
            score = 25;
        } else {
            score = 0;
        }
        java.lang.System.out.println("Score: " + score);
        return score;
    } else {
        java.lang.System.out.println("Objeto no encontrado");
        return 0;
    }
    //System.out.println("Terminando SIFT");  
}

From source file:view.TelaComCaptura.java

public String salvarPgm2(String path, Mat mat) {
    FileOutputStream fout;/*  w w w . ja  v  a  2  s .  com*/

    int pixels[][] = new int[mat.rows()][mat.cols()];

    try {
        fout = new FileOutputStream(path);

        //write image header
        //write PGM magic value 'P5'
        String tstr;
        tstr = "P5" + "\n";
        fout.write(tstr.getBytes());

        //write comment
        // comment = comment + "\n";
        //fout.write(comment.getBytes());
        //write cols
        tstr = Integer.toString(mat.cols());
        fout.write(tstr.getBytes());
        fout.write(32); //write blank space

        //write rows
        tstr = Integer.toString(mat.rows());
        fout.write(tstr.getBytes());
        fout.write(32); //write blank space

        //write maxgray
        tstr = Integer.toString(255);
        tstr = tstr + "\n";
        fout.write(tstr.getBytes());

        for (int r = 0; r < mat.rows(); r++) {
            for (int c = 0; c < mat.cols(); c++) {

                double[] pixelsRgb = mat.get(r, c);

                int red = (int) (pixelsRgb[0] * 0.299);
                int green = (int) (pixelsRgb[1] * 0.587);
                int blue = (int) (pixelsRgb[1] * 0.114);

                Color newColor = new Color(red + green + blue, red + green + blue, red + green + blue);

                //int pixel = (int) (pixelsRgb[0] + pixelsRgb[1] + pixelsRgb[1]);
                //pixel = pixel / 3;
                fout.write(newColor.getRGB());

                // fout.write((int) mat.get(r, c)[0]);
            }
        }

        fout.close();
        return path;
    } catch (Exception e) {
        System.out.println("Erro ao salvar PGM: " + e);
    }

    return "";
}

From source file:vinylsleevedetection.Analyze.java

public void Check() {
    count = 1;/* w  ww .j a va 2  s  . c o  m*/
    //load openCV library
    System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
    //for loop to compare source images to user image
    for (int j = 1; j < 4; j++) {
        //source image location (record sleeve)
        String Object = "E:\\Users\\Jamie\\Documents\\NetBeansProjects\\VinylSleeveDetection\\Source\\" + j
                + ".jpg";
        //user image location
        String Scene = "E:\\Users\\Jamie\\Documents\\NetBeansProjects\\VinylSleeveDetection\\Output\\camera.jpg";
        //load images
        Mat objectImage = Imgcodecs.imread(Object, Imgcodecs.CV_LOAD_IMAGE_COLOR);
        Mat sceneImage = Imgcodecs.imread(Scene, Imgcodecs.CV_LOAD_IMAGE_COLOR);
        //use BRISK feature detection
        MatOfKeyPoint objectKeyPoints = new MatOfKeyPoint();
        FeatureDetector featureDetector = FeatureDetector.create(FeatureDetector.BRISK);
        //perform feature detection on source image
        featureDetector.detect(objectImage, objectKeyPoints);
        KeyPoint[] keypoints = objectKeyPoints.toArray();
        //use descriptor extractor
        MatOfKeyPoint objectDescriptors = new MatOfKeyPoint();
        DescriptorExtractor descriptorExtractor = DescriptorExtractor.create(DescriptorExtractor.BRISK);
        descriptorExtractor.compute(objectImage, objectKeyPoints, objectDescriptors);

        Mat outputImage = new Mat(objectImage.rows(), objectImage.cols(), Imgcodecs.CV_LOAD_IMAGE_COLOR);
        Scalar newKeypointColor = new Scalar(255, 0, 0);

        Features2d.drawKeypoints(objectImage, objectKeyPoints, outputImage, newKeypointColor, 0);

        MatOfKeyPoint sceneKeyPoints = new MatOfKeyPoint();
        MatOfKeyPoint sceneDescriptors = new MatOfKeyPoint();
        featureDetector.detect(sceneImage, sceneKeyPoints);
        descriptorExtractor.compute(sceneImage, sceneKeyPoints, sceneDescriptors);

        Mat matchoutput = new Mat(sceneImage.rows() * 2, sceneImage.cols() * 2, Imgcodecs.CV_LOAD_IMAGE_COLOR);
        Scalar matchestColor = new Scalar(0, 255, 0);

        List<MatOfDMatch> matches = new LinkedList<>();
        DescriptorMatcher descriptorMatcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE);
        descriptorMatcher.knnMatch(objectDescriptors, sceneDescriptors, matches, 2);

        LinkedList<DMatch> goodMatchesList = new LinkedList<DMatch>();

        float nndrRatio = 0.7f;

        for (int i = 0; i < matches.size(); i++) {
            MatOfDMatch matofDMatch = matches.get(i);
            DMatch[] dmatcharray = matofDMatch.toArray();
            DMatch m1 = dmatcharray[0];
            DMatch m2 = dmatcharray[1];

            if (m1.distance <= m2.distance * nndrRatio) {
                goodMatchesList.addLast(m1);

            }
        }
        //if the number of good mathces is more than 150 a match is found
        if (goodMatchesList.size() > 150) {
            System.out.println("Object Found");

            List<KeyPoint> objKeypointlist = objectKeyPoints.toList();
            List<KeyPoint> scnKeypointlist = sceneKeyPoints.toList();

            LinkedList<Point> objectPoints = new LinkedList<>();
            LinkedList<Point> scenePoints = new LinkedList<>();

            for (int i = 0; i < goodMatchesList.size(); i++) {
                objectPoints.addLast(objKeypointlist.get(goodMatchesList.get(i).queryIdx).pt);
                scenePoints.addLast(scnKeypointlist.get(goodMatchesList.get(i).trainIdx).pt);
            }

            MatOfPoint2f objMatOfPoint2f = new MatOfPoint2f();
            objMatOfPoint2f.fromList(objectPoints);
            MatOfPoint2f scnMatOfPoint2f = new MatOfPoint2f();
            scnMatOfPoint2f.fromList(scenePoints);

            Mat homography = Calib3d.findHomography(objMatOfPoint2f, scnMatOfPoint2f, Calib3d.RANSAC, 3);

            Mat obj_corners = new Mat(4, 1, CvType.CV_32FC2);
            Mat scene_corners = new Mat(4, 1, CvType.CV_32FC2);

            obj_corners.put(0, 0, new double[] { 0, 0 });
            obj_corners.put(1, 0, new double[] { objectImage.cols(), 0 });
            obj_corners.put(2, 0, new double[] { objectImage.cols(), objectImage.rows() });
            obj_corners.put(3, 0, new double[] { 0, objectImage.rows() });

            Core.perspectiveTransform(obj_corners, scene_corners, homography);

            Mat img = Imgcodecs.imread(Scene, Imgcodecs.CV_LOAD_IMAGE_COLOR);
            //draw a green square around the matched object
            Imgproc.line(img, new Point(scene_corners.get(0, 0)), new Point(scene_corners.get(1, 0)),
                    new Scalar(0, 255, 0), 10);
            Imgproc.line(img, new Point(scene_corners.get(1, 0)), new Point(scene_corners.get(2, 0)),
                    new Scalar(0, 255, 0), 10);
            Imgproc.line(img, new Point(scene_corners.get(2, 0)), new Point(scene_corners.get(3, 0)),
                    new Scalar(0, 255, 0), 10);
            Imgproc.line(img, new Point(scene_corners.get(3, 0)), new Point(scene_corners.get(0, 0)),
                    new Scalar(0, 255, 0), 10);

            MatOfDMatch goodMatches = new MatOfDMatch();
            goodMatches.fromList(goodMatchesList);

            Features2d.drawMatches(objectImage, objectKeyPoints, sceneImage, sceneKeyPoints, goodMatches,
                    matchoutput, matchestColor, newKeypointColor, new MatOfByte(), 2);
            //output image with match, image of the match locations and keypoints image
            String folder = "E:\\Users\\Jamie\\Documents\\NetBeansProjects\\VinylSleeveDetection\\Output\\";
            Imgcodecs.imwrite(folder + "outputImage.jpg", outputImage);
            Imgcodecs.imwrite(folder + "matchoutput.jpg", matchoutput);
            Imgcodecs.imwrite(folder + "found.jpg", img);
            count = j;
            break;
        } else {
            System.out.println("Object Not Found");
            count = 0;
        }

    }

}