Example usage for org.opencv.imgproc Imgproc moments

List of usage examples for org.opencv.imgproc Imgproc moments

Introduction

In this page you can find the example usage for org.opencv.imgproc Imgproc moments.

Prototype

public static Moments moments(Mat array) 

Source Link

Usage

From source file:br.cefetmg.lsi.opencv.multipleObjectTracking.processing.MultipleObjectTracking.java

License:Open Source License

private void trackFilteredObject(Ball theBall, Mat threshold, Mat cameraFeed) {
    List<Ball> balls = new ArrayList<Ball>();

    Mat temp = new Mat();
    threshold.copyTo(temp);/*from w ww.j a  va2  s .c o  m*/

    // The two variables below are the return of "findContours" processing.
    List<MatOfPoint> contours = new ArrayList<MatOfPoint>();
    Mat hierarchy = new Mat();

    // find contours of filtered image using openCV findContours function      
    Imgproc.findContours(temp, contours, hierarchy, Imgproc.RETR_CCOMP, Imgproc.CHAIN_APPROX_SIMPLE);

    // use moments method to find our filtered object
    boolean objectFound = false;

    if (contours.size() > 0) {
        int numObjects = contours.size();

        //if number of objects greater than MAX_NUM_OBJECTS we have a noisy filter
        if (numObjects < MAX_NUM_OBJECTS) {

            for (int i = 0; i < contours.size(); i++) {
                Moments moment = Imgproc.moments(contours.get(i));
                double area = moment.get_m00();

                //if the area is less than 20 px by 20px then it is probably just noise
                //if the area is the same as the 3/2 of the image size, probably just a bad filter
                //we only want the object with the largest area so we safe a reference area each
                //iteration and compare it to the area in the next iteration.
                if (area > MIN_OBJECT_AREA) {
                    Ball ball = new Ball();
                    ball.setXPos((int) (moment.get_m10() / area));
                    ball.setYPos((int) (moment.get_m01() / area));

                    if (theBall != null) {
                        ball.setType(theBall.getType());
                        ball.setColour(theBall.getColour());
                    }

                    balls.add(ball);

                    objectFound = true;
                } else {
                    objectFound = false;
                }

            }

            //let user know you found an object
            if (objectFound) {
                //draw object location on screen
                drawObject(balls, cameraFeed);
            }

        } else {
            Core.putText(cameraFeed, "TOO MUCH NOISE! ADJUST FILTER", new Point(0, 50), 1, 2,
                    new Scalar(0, 0, 255), 2);
        }

    }

}

From source file:classes.FloodFiller.java

private void fillFrom(Point seed, int lo, int up, Scalar backgroundColor, Scalar contourFillingColor) {

    Mat object = ObjectGenerator.extract(image, seed.x, seed.y, 10, 10);
    this.meanColor = Core.mean(object);

    Rect ccomp = new Rect();
    Mat mask = Mat.zeros(image.rows() + 2, image.cols() + 2, CvType.CV_8UC1);

    int connectivity = 4;
    int newMaskVal = 255;
    int ffillMode = 1;

    int flags = connectivity + (newMaskVal << 8) + (ffillMode == 1 ? Imgproc.FLOODFILL_FIXED_RANGE : 0);

    Scalar newVal = new Scalar(0.299, 0.587, 0.114);

    Imgproc.threshold(mask, mask, 1, 128, Imgproc.THRESH_BINARY);

    filledArea = Imgproc.floodFill(image.clone(), mask, seed, newVal, ccomp, new Scalar(lo, lo, lo),
            new Scalar(up, up, up), flags);

    //        Highgui.imwrite("mask.png", mask);
    ImageUtils.saveImage(mask, "mask.png", request);

    morphologicalImage = new Mat(image.size(), CvType.CV_8UC3);

    Mat element = new Mat(3, 3, CvType.CV_8U, new Scalar(1));

    ArrayList<Mat> mask3 = new ArrayList<Mat>();
    mask3.add(mask);//ww  w.  j  a  v a 2 s .  c o  m
    mask3.add(mask);
    mask3.add(mask);
    Core.merge(mask3, mask);

    // Applying morphological filters
    Imgproc.erode(mask, morphologicalImage, element);
    Imgproc.morphologyEx(morphologicalImage, morphologicalImage, Imgproc.MORPH_CLOSE, element,
            new Point(-1, -1), 9);
    Imgproc.morphologyEx(morphologicalImage, morphologicalImage, Imgproc.MORPH_OPEN, element, new Point(-1, -1),
            2);
    Imgproc.resize(morphologicalImage, morphologicalImage, image.size());

    //        Highgui.imwrite("morphologicalImage.png", morphologicalImage);
    ImageUtils.saveImage(morphologicalImage, "morphologicalImage.png", request);

    List<MatOfPoint> contours = new ArrayList<MatOfPoint>();

    Core.split(mask, mask3);
    Mat binarymorphologicalImage = mask3.get(0);

    Imgproc.findContours(binarymorphologicalImage.clone(), contours, new Mat(), Imgproc.RETR_EXTERNAL,
            Imgproc.CHAIN_APPROX_NONE);

    contoursImage = new Mat(image.size(), CvType.CV_8UC3, backgroundColor);

    int thickness = -1; // Thicknes should be lower than zero in order to drawn the filled contours
    Imgproc.drawContours(contoursImage, contours, -1, contourFillingColor, thickness); // Drawing all the contours found
    //        Highgui.imwrite("allContoursImage.png", contoursImage);
    ImageUtils.saveImage(contoursImage, "allContoursImage.png", request);

    if (contours.size() > 1) {

        int minContourWith = 20;
        int minContourHeight = 20;
        int maxContourWith = 6400 / 2;
        int maxContourHeight = 4800 / 2;

        contours = filterContours(contours, minContourWith, minContourHeight, maxContourWith, maxContourHeight);
    }

    if (contours.size() > 0) {

        MatOfPoint biggestContour = contours.get(0); // getting the biggest contour
        contourArea = Imgproc.contourArea(biggestContour);

        if (contours.size() > 1) {
            biggestContour = Collections.max(contours, new ContourComparator()); // getting the biggest contour in case there are more than one
        }

        Point[] points = biggestContour.toArray();
        path = "M " + (int) points[0].x + " " + (int) points[0].y + " ";
        for (int i = 1; i < points.length; ++i) {
            Point v = points[i];
            path += "L " + (int) v.x + " " + (int) v.y + " ";
        }
        path += "Z";

        biggestContourImage = new Mat(image.size(), CvType.CV_8UC3, backgroundColor);

        Imgproc.drawContours(biggestContourImage, contours, 0, contourFillingColor, thickness);

        //            Highgui.imwrite("biggestContourImage.png", biggestContourImage);
        ImageUtils.saveImage(biggestContourImage, "biggestContourImage.png", request);

        Mat maskForColorExtraction = biggestContourImage.clone();

        if (isWhite(backgroundColor)) {
            Imgproc.dilate(maskForColorExtraction, maskForColorExtraction, new Mat(), new Point(-1, -1), 3);
        } else {
            Imgproc.erode(maskForColorExtraction, maskForColorExtraction, new Mat(), new Point(-1, -1), 3);
        }

        //            Highgui.imwrite("maskForColorExtraction.png", maskForColorExtraction);
        ImageUtils.saveImage(maskForColorExtraction, "maskForColorExtraction.png", request);

        Mat extractedColor = new Mat();

        if (isBlack(backgroundColor) && isWhite(contourFillingColor)) {
            Core.bitwise_and(maskForColorExtraction, image, extractedColor);

        } else {
            Core.bitwise_or(maskForColorExtraction, image, extractedColor);
        }

        //            Highgui.imwrite("extractedColor.png", extractedColor);
        ImageUtils.saveImage(extractedColor, "extractedColor.png", request);

        computedSearchWindow = Imgproc.boundingRect(biggestContour);
        topLeftCorner = computedSearchWindow.tl();

        Rect croppingRect = new Rect(computedSearchWindow.x, computedSearchWindow.y,
                computedSearchWindow.width - 1, computedSearchWindow.height - 1);

        Mat imageForTextRecognition = new Mat(extractedColor.clone(), croppingRect);
        //            Highgui.imwrite(outImageName, imageForTextRecognition);
        ImageUtils.saveImage(imageForTextRecognition, outImageName, request);

        //            
        //
        //            Mat data = new Mat(imageForTextRecognition.size(), CvType.CV_8UC3, backgroundColor);
        //            imageForTextRecognition.copyTo(data);
        //            data.convertTo(data, CvType.CV_8UC3);
        //
        //            // The meanColor variable represents the color in the GBR space, the following line transforms this to the RGB color space, which
        //            // is assumed in the prepareImage method of the TextRecognitionPreparer class
        //            Scalar userColor = new Scalar(meanColor.val[2], meanColor.val[1], meanColor.val[0]);
        //
        //            ArrayList<String> recognizableImageNames = TextRecognitionPreparer.generateRecognizableImagesNames(data, backgroundColor, userColor);
        //            for (String imageName : recognizableImageNames) {
        //
        //                try {
        //                    // First recognition step
        //                    String recognizedText = TextRecognizer.recognize(imageName, true).trim();
        //                    if (recognizedText != null && !recognizedText.isEmpty()) {
        //                        recognizedStrings.add(recognizedText);
        //                    }
        //                    // Second recognition step
        //                    recognizedText = TextRecognizer.recognize(imageName, false).trim();
        //                    if (recognizedText != null && !recognizedText.isEmpty()) {
        //                        recognizedStrings.add(recognizedText);
        //                    }
        //                    
        //                } catch (Exception e) {
        //                }
        //            }
        //            
        ////            ArrayList<BufferedImage> recognizableBufferedImages = TextRecognitionPreparer.generateRecognizableBufferedImages(data, backgroundColor, userColor);
        ////            for (BufferedImage bufferedImage : recognizableBufferedImages) {
        ////                try {
        ////                    // First recognition step
        ////                    String recognizedText = TextRecognizer.recognize(bufferedImage, true).trim();
        ////                    if (recognizedText != null && !recognizedText.isEmpty()) {
        ////                        recognizedStrings.add(recognizedText);
        ////                    }
        ////                    // Second recognition step
        ////                    recognizedText = TextRecognizer.recognize(bufferedImage, false).trim();
        ////                    if (recognizedText != null && !recognizedText.isEmpty()) {
        ////                        recognizedStrings.add(recognizedText);
        ////                    }
        ////                    
        ////                } catch (Exception e) {
        ////                }
        ////            }
        //
        //            
        //            

        // compute all moments
        Moments mom = Imgproc.moments(biggestContour);
        massCenter = new Point(mom.get_m10() / mom.get_m00(), mom.get_m01() / mom.get_m00());

        // draw black dot
        Core.circle(contoursImage, massCenter, 4, contourFillingColor, 8);
    }

}

From source file:classes.ObjectFinder.java

private void computeSearchWindow() {

    List<MatOfPoint> contours = new ArrayList<MatOfPoint>();

    // a vector of contours
    // retrieve the external contours
    // all pixels of each contours    
    Imgproc.findContours(this.morphologicalImage.clone(), contours, new Mat(), Imgproc.RETR_EXTERNAL,
            Imgproc.CHAIN_APPROX_NONE);/*from w  w w .j av a  2s  .com*/

    // Draw black contours on a white image
    this.contoursImage = new Mat(morphologicalImage.size(), CvType.CV_8U, new Scalar(255));

    if (contours.size() > 1) {

        int minContourWith = 20;
        int minContourHeight = 20;
        int maxContourWith = 6400 / 2;
        int maxContourHeight = 4800 / 2;

        contours = filterContours(contours, minContourWith, minContourHeight, maxContourWith, maxContourHeight);
    }

    if (contours.size() > 1) {
        Collections.sort(contours, new ContourComparator()); // Sorttig the contours to take ONLY the bigger one
    }

    computedSearchWindow = new Rect();
    massCenter = new Point(-1, -1);

    if (contours.size() > 0) {

        this.firstContour = contours.get(0);

        Mat contournedImage = this.firstContour;

        // draw all contours in black with a thickness of 2
        Scalar color = new Scalar(0);
        int thickness = 2;
        Imgproc.drawContours(contoursImage, contours, 0, color, thickness); //

        // testing the bounding box
        computedSearchWindow = Imgproc.boundingRect(this.firstContour);

        topLeftCorner = computedSearchWindow.tl();

        // compute all moments
        Moments mom = Imgproc.moments(contournedImage);

        massCenter = new Point(mom.get_m10() / mom.get_m00(), mom.get_m01() / mom.get_m00());

        // draw black dot
        Core.circle(contoursImage, massCenter, 4, color, 8);
    }
}

From source file:com.shootoff.camera.autocalibration.AutoCalibrationManager.java

License:Open Source License

private Point massCenterMatOfPoint2f(final MatOfPoint2f map) {
    final Moments moments = Imgproc.moments(map);
    final Point centroid = new Point();
    centroid.x = moments.get_m10() / moments.get_m00();
    centroid.y = moments.get_m01() / moments.get_m00();
    return centroid;
}

From source file:com.ttolley.pongbot.opencv.CvWorker.java

private Target findTarget(List<MatOfPoint> contours, Mat webcam_image, Filter filter) {
    Target largestTarget = null;//  ww w . j  a  va  2 s .c o  m
    for (MatOfPoint matOfPoint : contours) {
        Moments moment = Imgproc.moments(matOfPoint);
        double area = moment.get_m00();

        if ((largestTarget == null && area > filter.objectSize * filter.objectSize)
                || (largestTarget != null && area > largestTarget.area)) {
            // Found object, do something about it
            largestTarget = new Target(moment.get_m10() / area, moment.get_m01() / area, area);
        }
    }
    if (largestTarget != null) {
        xPos.addValue(largestTarget.x);
        yPos.addValue(largestTarget.y);
        Core.circle(webcam_image, new Point(xPos.getMean(), yPos.getMean()), 10, new Scalar(0, 0, 255));
        Core.putText(webcam_image, "[" + xPos.getMean() + " " + yPos.getMean() + "]",
                new Point(xPos.getMean() - 40, yPos.getMean() + 25), 1, 1, new Scalar(0, 0, 255));
    }
    return largestTarget;
}

From source file:eu.fpetersen.robobrain.behavior.followobject.ColorBlobDetector.java

License:Open Source License

public void process(Mat rgbaImage) {
    Imgproc.pyrDown(rgbaImage, mPyrDownMat);
    Imgproc.pyrDown(mPyrDownMat, mPyrDownMat);

    Imgproc.cvtColor(mPyrDownMat, mHsvMat, Imgproc.COLOR_RGB2HSV_FULL);

    Core.inRange(mHsvMat, mLowerBound, mUpperBound, mMask);
    Imgproc.dilate(mMask, mDilatedMask, new Mat());

    List<MatOfPoint> contours = new ArrayList<MatOfPoint>();

    Imgproc.findContours(mDilatedMask, contours, mHierarchy, Imgproc.RETR_EXTERNAL,
            Imgproc.CHAIN_APPROX_SIMPLE);

    // Find max contour area
    maxArea = 0;/*from ww  w.  j  av  a2s.  c o  m*/
    Iterator<MatOfPoint> each = contours.iterator();
    Mat biggestContour = null;
    while (each.hasNext()) {
        MatOfPoint wrapper = each.next();
        double area = Imgproc.contourArea(wrapper);
        if (area > maxArea) {
            maxArea = area;
            biggestContour = wrapper.clone();
        }
    }
    if (biggestContour != null) {
        Core.multiply(biggestContour, new Scalar(4, 4), biggestContour);
        Moments mo = Imgproc.moments(biggestContour);
        centroidOfMaxArea = new Point(mo.get_m10() / mo.get_m00(), mo.get_m01() / mo.get_m00());
    } else {
        centroidOfMaxArea = null;
    }

    // Filter contours by area and resize to fit the original image size
    mContours.clear();
    each = contours.iterator();
    while (each.hasNext()) {
        MatOfPoint contour = each.next();
        if (Imgproc.contourArea(contour) > mMinContourArea * maxArea) {
            Core.multiply(contour, new Scalar(4, 4), contour);
            mContours.add(contour);
        }
    }

    Imgproc.drawContours(rgbaImage, mContours, -1, CONTOUR_COLOR);
}

From source file:opencv_ext.TGG_OpenCV_Util.java

public static Point[] getCentroidPoints(BufferedImage bufferedImage) {
    Point[][] contourPoints = getExternalConvexHullPoints(bufferedImage);
    Point[] centroidPoints = new Point[contourPoints.length];
    for (int c = 0; c < contourPoints.length; c++) {
        BufferedImage grayImage = new BufferedImage(bufferedImage.getWidth(), bufferedImage.getHeight(),
                BufferedImage.TYPE_BYTE_GRAY);
        Graphics g = grayImage.getGraphics();
        g.setColor(Color.GREEN);//from ww w . jav  a 2  s  .com
        Polygon convexHull = new Polygon();
        for (int p = 0; p < contourPoints[c].length; p++) {
            Point p0 = contourPoints[c][p];
            convexHull.addPoint((int) p0.x, (int) p0.y);
        }
        g.fillPolygon(convexHull);
        Mat cHull = bufferedImage2Mat(grayImage);
        Moments m = Imgproc.moments(cHull);
        centroidPoints[c] = new Point(m.m10 / m.m00, m.m01 / m.m00);
    }
    return centroidPoints;
}

From source file:org.pattern.detection.contour.ContourDetectionAlgorithm.java

/** Calculates center of particle. */
private Point calcCog(MatOfPoint contour) {
    Moments moments = Imgproc.moments(contour);
    Point cog = new Point();
    cog.x = moments.get_m10() / moments.get_m00();
    cog.y = moments.get_m01() / moments.get_m00();
    return cog;/* ww  w .  j  a v a  2s  . c om*/
}

From source file:org.sahyagiri.rpi.opencv.DetectCar.java

License:Mozilla Public License

public final Point findCentreOfMass(final Mat inputRGB, final Scalar carColorThresholdHSVLow,
        final Scalar carColorThresholdHSVHigh) {
    Mat hsvImage = new Mat();
    Imgproc.cvtColor(inputRGB, hsvImage, Imgproc.COLOR_RGB2HSV);
    Mat outputHSV = new Mat();
    Core.inRange(hsvImage, carColorThresholdHSVLow, carColorThresholdHSVHigh, outputHSV);
    Imgproc.morphologyEx(outputHSV, outputHSV, Imgproc.MORPH_ERODE, new Mat());
    Imgproc.GaussianBlur(outputHSV, outputHSV, new Size(3, 3), 3);
    Imgproc.threshold(outputHSV, outputHSV, 50, 255, Imgproc.THRESH_BINARY);

    ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>();
    Imgproc.findContours(outputHSV, contours, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
    MatOfPoint contourPoints = combineContourPoints(contours);
    Moments moments = Imgproc.moments(contourPoints);
    int x = (int) (moments.get_m10() / moments.get_m00());
    int y = (int) (moments.get_m01() / moments.get_m00());
    final Point centreOfMass = new Point(x, y);
    return centreOfMass;
}

From source file:org.usfirst.frc.team2084.CMonster2016.vision.Target.java

License:Open Source License

/**
 * Creates a new possible target based on the specified blob and calculates
 * its score.//from  ww w  . jav  a  2  s .c om
 *
 * @param p the shape of the possible target
 */
public Target(MatOfPoint contour, Mat grayImage) {
    // Simplify contour to make the corner finding algorithm work better
    MatOfPoint2f fContour = new MatOfPoint2f();
    contour.convertTo(fContour, CvType.CV_32F);
    Imgproc.approxPolyDP(fContour, fContour, VisionParameters.getGoalApproxPolyEpsilon(), true);
    fContour.convertTo(contour, CvType.CV_32S);

    this.contour = contour;

    // Check area, and don't do any calculations if it is not valid
    if (validArea = validateArea()) {

        // Find a bounding rectangle
        RotatedRect rect = Imgproc.minAreaRect(fContour);

        Point[] rectPoints = new Point[4];
        rect.points(rectPoints);

        for (int j = 0; j < rectPoints.length; j++) {
            Point rectPoint = rectPoints[j];

            double minDistance = Double.MAX_VALUE;
            Point point = null;

            for (int i = 0; i < contour.rows(); i++) {
                Point contourPoint = new Point(contour.get(i, 0));
                double dist = distance(rectPoint, contourPoint);
                if (dist < minDistance) {
                    minDistance = dist;
                    point = contourPoint;
                }
            }

            rectPoints[j] = point;
        }
        MatOfPoint2f rectMat = new MatOfPoint2f(rectPoints);
        // Refine the corners to improve accuracy
        Imgproc.cornerSubPix(grayImage, rectMat, new Size(4, 10), new Size(-1, -1),
                new TermCriteria(TermCriteria.EPS + TermCriteria.COUNT, 30, 0.1));
        rectPoints = rectMat.toArray();

        // Identify each corner
        SortedMap<Double, List<Point>> x = new TreeMap<>();
        Arrays.stream(rectPoints).forEach((p) -> {
            List<Point> points;
            if ((points = x.get(p.x)) == null) {
                x.put(p.x, points = new LinkedList<>());
            }
            points.add(p);
        });

        int i = 0;
        for (Iterator<List<Point>> it = x.values().iterator(); it.hasNext();) {
            List<Point> s = it.next();

            for (Point p : s) {
                switch (i) {
                case 0:
                    topLeft = p;
                    break;
                case 1:
                    bottomLeft = p;
                    break;
                case 2:
                    topRight = p;
                    break;
                case 3:
                    bottomRight = p;
                }
                i++;
            }
        }

        // Organize corners
        if (topLeft.y > bottomLeft.y) {
            Point p = bottomLeft;
            bottomLeft = topLeft;
            topLeft = p;
        }

        if (topRight.y > bottomRight.y) {
            Point p = bottomRight;
            bottomRight = topRight;
            topRight = p;
        }

        // Create corners for centroid calculation
        corners = new MatOfPoint2f(rectPoints);

        // Calculate center
        Moments moments = Imgproc.moments(corners);
        center = new Point(moments.m10 / moments.m00, moments.m01 / moments.m00);

        // Put the points in the correct order for solvePNP
        rectPoints[0] = topLeft;
        rectPoints[1] = topRight;
        rectPoints[2] = bottomLeft;
        rectPoints[3] = bottomRight;
        // Recreate corners in the new order
        corners = new MatOfPoint2f(rectPoints);

        widthTop = distance(topLeft, topRight);
        widthBottom = distance(bottomLeft, bottomRight);
        width = (widthTop + widthBottom) / 2.0;
        heightLeft = distance(topLeft, bottomLeft);
        heightRight = distance(topRight, bottomRight);
        height = (heightLeft + heightRight) / 2.0;

        Mat tvec = new Mat();

        // Calculate target's location
        Calib3d.solvePnP(OBJECT_POINTS, corners, CAMERA_MAT, DISTORTION_MAT, rotation, tvec, false,
                Calib3d.CV_P3P);

        // =======================================
        // Position and Orientation Transformation
        // =======================================

        double armAngle = VisionResults.getArmAngle();

        // Flip y axis to point upward
        Core.multiply(tvec, SIGN_NORMALIZATION_MATRIX, tvec);

        // Shift origin to arm pivot point, on the robot's centerline
        CoordinateMath.translate(tvec, CAMERA_X_OFFSET, CAMERA_Y_OFFSET, ARM_LENGTH);

        // Align axes with ground
        CoordinateMath.rotateX(tvec, -armAngle);
        Core.add(rotation, new MatOfDouble(armAngle, 0, 0), rotation);

        // Shift origin to robot center of rotation
        CoordinateMath.translate(tvec, 0, ARM_PIVOT_Y_OFFSET, -ARM_PIVOT_Z_OFFSET);

        double xPosFeet = tvec.get(0, 0)[0];
        double yPosFeet = tvec.get(1, 0)[0];
        double zPosFeet = tvec.get(2, 0)[0];

        // Old less effective aiming heading and distance calculation
        // double pixelsToFeet = TARGET_WIDTH / width;

        // distance = (TARGET_WIDTH * HighGoalProcessor.IMAGE_SIZE.width
        // / (2 * width ** Math.tan(VisionParameters.getFOVAngle() / 2)));
        // double xPosFeet = (center.x - (HighGoalProcessor.IMAGE_SIZE.width
        // / 2)) * pixelsToFeet;
        // double yPosFeet = -(center.y -
        // (HighGoalProcessor.IMAGE_SIZE.height / 2)) * pixelsToFeet;

        distance = Math.sqrt(xPosFeet * xPosFeet + zPosFeet * zPosFeet);

        position = new Point3(xPosFeet, yPosFeet, zPosFeet);

        xGoalAngle = Math.atan(xPosFeet / zPosFeet);
        yGoalAngle = Math.atan(yPosFeet / zPosFeet);

        validate();
        score = calculateScore();
    } else {
        valid = false;
    }
}