List of usage examples for org.opencv.imgproc Imgproc findContours
public static void findContours(Mat image, List<MatOfPoint> contours, Mat hierarchy, int mode, int method)
From source file:com.davidmiguel.gobees.monitoring.algorithm.processors.ContoursFinder.java
License:Open Source License
@Override public Mat process(@NonNull Mat frame) { if (frame.empty()) { Log.e("Invalid input frame."); return null; }// w w w .j ava2 s. c o m Mat tmp = frame.clone(); // Finding outer contours contourList.clear(); Imgproc.findContours(tmp, contourList, hierarchy, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); // Filter bees Mat contours = new Mat(tmp.rows(), tmp.cols(), CvType.CV_8UC3); tmp.release(); double area; Scalar color; numBees = 0; for (int i = 0; i < contourList.size(); i++) { area = Imgproc.contourArea(contourList.get(i)); if (area > minArea && area < maxArea) { color = GREEN; numBees++; } else { color = RED; } // Draw contour Imgproc.drawContours(contours, contourList, i, color, -1); } return contours; }
From source file:com.example.afs.makingmusic.process.MotionDetector.java
License:Open Source License
@Override public void process(Frame frame) { Mat image = frame.getImageMatrix();/*from w ww .j a v a 2s . c o m*/ Core.flip(image, image, 1); backgroundSubtractor.apply(image, foregroundMask); List<MatOfPoint> contours = new ArrayList<MatOfPoint>(); Imgproc.findContours(foregroundMask.clone(), contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE); Collections.shuffle(contours); int contourCount = contours.size(); for (int contourIndex = 0; contourIndex < contourCount; contourIndex++) { MatOfPoint contour = contours.get(contourIndex); double contourArea = Imgproc.contourArea(contour); if (contourArea > MotionDetector.MINIMUM_AREA) { Rect item = Imgproc.boundingRect(contour); frame.addItem(item); itemCount++; } } Injector.getMetrics().setItems(itemCount); }
From source file:com.github.mbillingr.correlationcheck.ImageProcessor.java
License:Open Source License
public List<Point> extractPoints() { Mat gray = new Mat();//work_width, work_height, CvType.CV_8UC1); Mat binary = new Mat(); Mat kernel = Mat.ones(3, 3, CvType.CV_8UC1); debugreset();//from w ww . ja v a 2s . com Mat image = load_transformed(); working_image = image.clone(); debugsave(image, "source"); Imgproc.cvtColor(image, gray, Imgproc.COLOR_RGB2GRAY); debugsave(gray, "grayscale"); Imgproc.GaussianBlur(gray, gray, new Size(15, 15), 0); debugsave(gray, "blurred"); //Imgproc.equalizeHist(gray, gray); //debugsave(gray, "equalized"); Imgproc.adaptiveThreshold(gray, binary, 255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C, Imgproc.THRESH_BINARY_INV, 129, 5); //Imgproc.threshold(gray, binary, 0, 255, Imgproc.THRESH_BINARY_INV + Imgproc.THRESH_OTSU); //Imgproc.threshold(gray, binary, 128, 255, Imgproc.THRESH_BINARY_INV); debugsave(binary, "binary"); Imgproc.morphologyEx(binary, binary, Imgproc.MORPH_CLOSE, kernel); debugsave(binary, "closed"); Imgproc.morphologyEx(binary, binary, Imgproc.MORPH_OPEN, kernel); debugsave(binary, "opened"); List<MatOfPoint> contours = new ArrayList<>(); Mat hierarchy = new Mat(); Imgproc.findContours(binary, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE); // is binary is now changed Imgproc.drawContours(image, contours, -1, new Scalar(0, 0, 255), 3); debugsave(image, "contours"); List<PointAndArea> points = new ArrayList<>(); for (MatOfPoint cnt : contours) { MatOfPoint2f c2f = new MatOfPoint2f(); c2f.fromArray(cnt.toArray()); RotatedRect rr = Imgproc.minAreaRect(c2f); double area = Imgproc.contourArea(cnt); if (rr.size.width / rr.size.height < 3 && rr.size.height / rr.size.width < 3 && rr.size.width < 64 && rr.size.height < 64 && area > 9 && area < 10000) { points.add(new PointAndArea((int) area, rr.center)); } } List<Point> final_points = new ArrayList<>(); Collections.sort(points); Collections.reverse(points); int prev = -1; for (PointAndArea p : points) { Log.i("area", Integer.toString(p.area)); if (prev == -1 || p.area >= prev / 2) { prev = p.area; Imgproc.circle(image, p.point, 10, new Scalar(0, 255, 0), 5); final_points.add(new Point(1 - p.point.y / work_height, 1 - p.point.x / work_width)); } } debugsave(image, "circles"); return final_points; }
From source file:com.mitzuli.core.ocr.OcrPreprocessor.java
License:Open Source License
/** * Binarizes and cleans the input image for OCR, saving debugging images in the given directory. * * @param input the input image, which is recycled by this method, so the caller should make a defensive copy of it if necessary. * @param debugDir the directory to write the debugging images to, or null to disable debugging. * @return the preprocessed image./* www. j a va 2 s . c om*/ */ static Image preprocess(final Image input, final File debugDir) { // TODO Temporary workaround to allow to manually enable debugging (the global final variable should be used) boolean DEBUG = debugDir != null; // Initialization final Mat mat = input.toGrayscaleMat(); final Mat debugMat = DEBUG ? input.toRgbMat() : null; input.recycle(); final Mat aux = new Mat(mat.size(), CvType.CV_8UC1); final Mat binary = new Mat(mat.size(), CvType.CV_8UC1); if (DEBUG) Image.fromMat(mat).write(new File(debugDir, "1_input.jpg")); // Binarize the input image in mat through adaptive Gaussian thresholding Imgproc.adaptiveThreshold(mat, binary, 255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C, Imgproc.THRESH_BINARY, 51, 13); // Imgproc.adaptiveThreshold(mat, binary, 255, Imgproc.ADAPTIVE_THRESH_GAUSSIAN_C, Imgproc.THRESH_BINARY, 31, 7); // Edge detection Imgproc.morphologyEx(mat, mat, Imgproc.MORPH_OPEN, KERNEL_3X3); // Open Imgproc.morphologyEx(mat, aux, Imgproc.MORPH_CLOSE, KERNEL_3X3); // Close Core.addWeighted(mat, 0.5, aux, 0.5, 0, mat); // Average Imgproc.morphologyEx(mat, mat, Imgproc.MORPH_GRADIENT, KERNEL_3X3); // Gradient Imgproc.threshold(mat, mat, 0, 255, Imgproc.THRESH_BINARY | Imgproc.THRESH_OTSU); // Edge map if (DEBUG) Image.fromMat(mat).write(new File(debugDir, "2_edges.jpg")); // Extract word level connected-components from the dilated edge map Imgproc.dilate(mat, mat, KERNEL_3X3); if (DEBUG) Image.fromMat(mat).write(new File(debugDir, "3_dilated_edges.jpg")); final List<MatOfPoint> wordCCs = new ArrayList<MatOfPoint>(); Imgproc.findContours(mat, wordCCs, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); // Filter word level connected-components individually and calculate their average attributes final List<MatOfPoint> individuallyFilteredWordCCs = new ArrayList<MatOfPoint>(); final List<MatOfPoint> removedWordCCs = new ArrayList<MatOfPoint>(); double avgWidth = 0, avgHeight = 0, avgArea = 0; for (MatOfPoint cc : wordCCs) { final Rect boundingBox = Imgproc.boundingRect(cc); if (boundingBox.height >= 6 // bounding box height >= 6 && boundingBox.area() >= 50 // bounding box area >= 50 && (double) boundingBox.width / (double) boundingBox.height >= 0.25 // bounding box aspect ratio >= 1:4 && boundingBox.width <= 0.75 * mat.width() // bounding box width <= 0.75 image width && boundingBox.height <= 0.75 * mat.height()) // bounding box height <= 0.75 image height { individuallyFilteredWordCCs.add(cc); avgWidth += boundingBox.width; avgHeight += boundingBox.height; avgArea += boundingBox.area(); } else { if (DEBUG) removedWordCCs.add(cc); } } wordCCs.clear(); avgWidth /= individuallyFilteredWordCCs.size(); avgHeight /= individuallyFilteredWordCCs.size(); avgArea /= individuallyFilteredWordCCs.size(); if (DEBUG) { Imgproc.drawContours(debugMat, removedWordCCs, -1, BLUE, -1); removedWordCCs.clear(); } // Filter word level connected-components in relation to their average attributes final List<MatOfPoint> filteredWordCCs = new ArrayList<MatOfPoint>(); for (MatOfPoint cc : individuallyFilteredWordCCs) { final Rect boundingBox = Imgproc.boundingRect(cc); if (boundingBox.width >= 0.125 * avgWidth // bounding box width >= 0.125 average width && boundingBox.width <= 8 * avgWidth // bounding box width <= 8 average width && boundingBox.height >= 0.25 * avgHeight // bounding box height >= 0.25 average height && boundingBox.height <= 4 * avgHeight) // bounding box height <= 4 average height { filteredWordCCs.add(cc); } else { if (DEBUG) removedWordCCs.add(cc); } } individuallyFilteredWordCCs.clear(); if (DEBUG) { Imgproc.drawContours(debugMat, filteredWordCCs, -1, GREEN, -1); Imgproc.drawContours(debugMat, removedWordCCs, -1, PURPLE, -1); removedWordCCs.clear(); } // Extract paragraph level connected-components mat.setTo(BLACK); Imgproc.drawContours(mat, filteredWordCCs, -1, WHITE, -1); final List<MatOfPoint> paragraphCCs = new ArrayList<MatOfPoint>(); Imgproc.morphologyEx(mat, aux, Imgproc.MORPH_CLOSE, KERNEL_30X30); Imgproc.findContours(aux, paragraphCCs, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); // Filter paragraph level connected-components according to the word level connected-components inside final List<MatOfPoint> textCCs = new ArrayList<MatOfPoint>(); for (MatOfPoint paragraphCC : paragraphCCs) { final List<MatOfPoint> wordCCsInParagraphCC = new ArrayList<MatOfPoint>(); aux.setTo(BLACK); Imgproc.drawContours(aux, Collections.singletonList(paragraphCC), -1, WHITE, -1); Core.bitwise_and(mat, aux, aux); Imgproc.findContours(aux, wordCCsInParagraphCC, new Mat(), Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE); final Rect boundingBox = Imgproc.boundingRect(paragraphCC); final double center = mat.size().width / 2; final double distToCenter = center > boundingBox.x + boundingBox.width ? center - boundingBox.x - boundingBox.width : center < boundingBox.x ? boundingBox.x - center : 0.0; if (DEBUG) { System.err.println("****************************************"); System.err.println("\tArea: " + boundingBox.area()); System.err.println("\tDistance to center: " + distToCenter); System.err.println("\tCCs inside: " + wordCCsInParagraphCC.size()); } if ((wordCCsInParagraphCC.size() >= 10 || wordCCsInParagraphCC.size() >= 0.3 * filteredWordCCs.size()) && mat.size().width / distToCenter >= 4) { textCCs.addAll(wordCCsInParagraphCC); if (DEBUG) { System.err.println("\tText: YES"); Imgproc.drawContours(debugMat, Collections.singletonList(paragraphCC), -1, DARK_GREEN, 5); } } else { if (DEBUG) { System.err.println("\tText: NO"); Imgproc.drawContours(debugMat, Collections.singletonList(paragraphCC), -1, DARK_RED, 5); } } } filteredWordCCs.clear(); paragraphCCs.clear(); mat.setTo(WHITE); Imgproc.drawContours(mat, textCCs, -1, BLACK, -1); textCCs.clear(); if (DEBUG) Image.fromMat(debugMat).write(new File(debugDir, "4_filtering.jpg")); // Obtain the final text mask from the filtered connected-components Imgproc.erode(mat, mat, KERNEL_15X15); Imgproc.morphologyEx(mat, mat, Imgproc.MORPH_OPEN, KERNEL_30X30); if (DEBUG) Image.fromMat(mat).write(new File(debugDir, "5_text_mask.jpg")); // Apply the text mask to the binarized image if (DEBUG) Image.fromMat(binary).write(new File(debugDir, "6_binary.jpg")); binary.setTo(WHITE, mat); if (DEBUG) Image.fromMat(binary).write(new File(debugDir, "7_binary_text.jpg")); // Dewarp the text using Leptonica Pix pixs = Image.fromMat(binary).toGrayscalePix(); Pix pixsDewarp = Dewarp.dewarp(pixs, 0, Dewarp.DEFAULT_SAMPLING, 5, true); final Image result = Image.fromGrayscalePix(pixsDewarp); if (DEBUG) result.write(new File(debugDir, "8_dewarp.jpg")); // Clean up pixs.recycle(); mat.release(); aux.release(); binary.release(); if (debugMat != null) debugMat.release(); return result; }
From source file:com.mycompany.objectdetection.ObjectDetector.java
public void findObjects() { // Imgproc.cvtColor(img, imgGrayscale, Imgproc.COLOR_RGBA2GRAY, 1); // Core.convertScaleAbs(img, imgGrayscale); // Core.normalize(imgGrayscale, imgMeanShifted, 0.0, 1.0, NORM_MINMAX); preProcessImg();/*from w w w. ja v a 2s . c o m*/ toGrayScale(imgMeanShifted); detectEdges(imgGrayscale); Imgproc.findContours(imgCanny, contours, imgCanny, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE); objList = new ArrayList(); for (MatOfPoint mop : contours) { MatOfPoint2f m2p; m2p = new MatOfPoint2f(mop.toArray()); Double peri = Imgproc.arcLength(m2p, true); Imgproc.approxPolyDP(m2p, m2p, 0.02 * peri, true); Imgproc.drawContours(imgOut, contours, -1, new Scalar(0, 0, 255), 2); float area = img.width() * img.height(); Rect rect = Imgproc.boundingRect(mop); objList.add(rect); Imgproc.rectangle(imgOut, rect.tl(), rect.br(), new Scalar(255, 0, 0)); } Collections.sort(objList, new Comparator<Rect>() { @Override public int compare(Rect r1, Rect r2) { return (int) (r2.area() - r1.area()); } }); List<Rect> arr = objList; while (arr.size() > 0) { //System.out.println("---->" + arr); Rect bigRect = arr.get(0); arr.remove(0); Rect bigRect2 = new Rect(); while (!equals(bigRect, bigRect2)) { bigRect2 = bigRect; for (int i = 0; i < arr.size(); ++i) { // System.out.println("elotte"+arr.get(i)); if (doOverlap(bigRect, arr.get(i))) { //System.out.println("utana"+arr.get(i)); bigRect = union(bigRect, arr.get(i)); arr.remove(i); break; } } } mainRect = bigRect; if (objList.size() > 5 && mainRect.area() >= img.width() * img.height() * 3 / 100) { Imgproc.rectangle(imgOut, bigRect.tl(), bigRect.br(), new Scalar(255, 255, 0)); mainObjects.add(mainRect); } else if (objList.size() <= 5) { mainObjects.add(mainRect); } } }
From source file:com.orange.documentare.core.image.connectedcomponents.ConnectedComponentsDetector.java
License:Open Source License
/** * Retrieve image connected components in image * @param imageMat/* w w w . ja v a 2 s . co m*/ * @param filter to apply to remove some connected components (based on size, etc) * @return connected components */ private ConnectedComponents detect(Mat imageMat, ConnectedComponentsFilter filter) { Mat binaryMat = Binarization.getFrom(imageMat); List<MatOfPoint> contours = new ArrayList<>(); Mat hierarchy = new Mat(); Imgproc.findContours(binaryMat, contours, hierarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE); return buildConnectedComponents(contours, filter); }
From source file:com.sikulix.core.Finder.java
License:Open Source License
public boolean hasChanges(Mat base, Mat current) { int PIXEL_DIFF_THRESHOLD = 5; int IMAGE_DIFF_THRESHOLD = 5; Mat bg = new Mat(); Mat cg = new Mat(); Mat diff = new Mat(); Mat tdiff = new Mat(); Imgproc.cvtColor(base, bg, Imgproc.COLOR_BGR2GRAY); Imgproc.cvtColor(current, cg, Imgproc.COLOR_BGR2GRAY); Core.absdiff(bg, cg, diff);/*from w w w . j a va 2 s .c o m*/ Imgproc.threshold(diff, tdiff, PIXEL_DIFF_THRESHOLD, 0.0, Imgproc.THRESH_TOZERO); if (Core.countNonZero(tdiff) <= IMAGE_DIFF_THRESHOLD) { return false; } Imgproc.threshold(diff, diff, PIXEL_DIFF_THRESHOLD, 255, Imgproc.THRESH_BINARY); Imgproc.dilate(diff, diff, new Mat()); Mat se = Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, new Size(5, 5)); Imgproc.morphologyEx(diff, diff, Imgproc.MORPH_CLOSE, se); List<MatOfPoint> points = new ArrayList<MatOfPoint>(); Mat contours = new Mat(); Imgproc.findContours(diff, points, contours, Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE); int n = 0; for (Mat pm : points) { log.trace("(%d) %s", n++, pm); printMatI(pm); } log.trace("contours: %s", contours); printMatI(contours); return true; }
From source file:com.ttolley.pongbot.opencv.CvWorker.java
@Override protected Void doInBackground() throws Exception { try {/*from ww w . ja v a 2s. c o m*/ //-- 2. Read the video stream Mat webcam_image = new Mat(); if (capture.isOpened()) { while (true) { capture.read(webcam_image); if (!webcam_image.empty()) { PublishObject publishObject = new PublishObject(webcam_image); for (Map.Entry<FilterType, Filter> entry : filters.entrySet()) { Mat hsv_image = new Mat(); Mat thresholded = new Mat(); Filter filter = entry.getValue(); // One way to select a range of colors by Hue Imgproc.cvtColor(webcam_image, hsv_image, Imgproc.COLOR_BGR2HSV); Core.inRange(hsv_image, filter.hsv_min, filter.hsv_max, thresholded); // Morph open final Size erodeSizeObj = new Size(filter.erodeSize, filter.erodeSize); final Size dilateSizeObj = new Size(filter.dilateSize, filter.dilateSize); Imgproc.erode(thresholded, thresholded, Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, erodeSizeObj)); Imgproc.dilate(thresholded, thresholded, Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, erodeSizeObj)); // Morph close Imgproc.dilate(thresholded, thresholded, Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, dilateSizeObj)); Imgproc.erode(thresholded, thresholded, Imgproc.getStructuringElement(Imgproc.MORPH_ELLIPSE, dilateSizeObj)); Mat temp = new Mat(); thresholded.copyTo(temp); List<MatOfPoint> contours = new ArrayList(); Mat heirarchy = new Mat(); Imgproc.findContours(temp, contours, heirarchy, Imgproc.RETR_TREE, Imgproc.CHAIN_APPROX_SIMPLE); FilteredObject.Target largestTarget = findTarget(contours, webcam_image, filter); publishObject.addObject(entry.getKey(), new FilteredObject(largestTarget, thresholded)); } publish(publishObject); } else { System.out.println(" --(!) No captured frame -- Break!"); break; } } } } catch (Exception ex) { System.out.println("Unable to loop"); System.out.println(getStackTrace(ex)); } return null; }
From source file:cpsd.ImageGUI.java
private void AnalyzeButtonActionPerformed(java.awt.event.ActionEvent evt) {//GEN-FIRST:event_AnalyzeButtonActionPerformed try {//from ww w . j a v a 2s .c o m double pixelArea = 1; double imageSize = 1; if (magnification == 50) pixelArea = 1.2996; else if (magnification == 100) pixelArea = 0.329476; else if (magnification == 200) pixelArea = 0.08162; else { imageSize = pow(10, 10) * pow(magnification, -2); pixelArea = (imageSize) / (resolution1 * resolution2); } Mat source = ImageClass.getInstance().getImage(); Mat destination = new Mat(source.rows(), source.cols(), source.type()); //Imgproc.adaptiveThreshold(source,destination,255,ADAPTIVE_THRESH_GAUSSIAN_C,THRESH_BINARY_INV,13,2); //Imgproc.GaussianBlur(destination,destination,new org.opencv.core.Size(0,0),5); threshold(source, destination, 30, 255, CV_THRESH_BINARY); distanceTransform(destination, destination, CV_DIST_L2, 3); normalize(destination, destination, 0, 1, NORM_MINMAX); threshold(destination, destination, 0.5, 1, CV_THRESH_BINARY); destination.convertTo(destination, CV_8U); /*ImageClass.getInstance().setImage(destination); displayImage();*/ ArrayList<MatOfPoint> contours = new ArrayList<MatOfPoint>(); MatOfInt4 hierarchy = new MatOfInt4(); // Rect roi = new Rect(100,100,destination.cols()-100,destination.rows()-100); // Mat imageROI = destination.submat(roi); /*ImageClass.getInstance().setImage(imageROI); displayImage();*/ //Imgproc.Canny(source,destination,0.05,0.15); Imgproc.findContours(destination, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE); int total = contours.size(); int count = 0; //System.out.println(total); MatOfPoint[] cntrs = contours.toArray(new MatOfPoint[contours.size()]); ArrayList<Double> value = new ArrayList<Double>(); double temp = 0; for (int i = 0; i < contours.size(); i++) { if (contourArea(cntrs[i]) > 1/*&& contourArea(cntrs[i])<3000*/) { temp = 2 * Math.sqrt((contourArea(cntrs[i]) * (pixelArea)) / Math.PI); //temp = contourArea(cntrs[i]); if (temp > 0) { value.add(count, temp); System.out.println("area of contour " + count++ + " is : " + contourArea(cntrs[i])); } } } System.out.println("total number of contours : " + count); double[] values = new double[count]; for (int i = 0; i < count; i++) { //temp = value.get(i);//2*Math.sqrt((value.get(i)*127.024)/Math.PI); //if(temp>0) values[i] = value.get(i); //System.out.println("the diameter of particle "+i+ "is "+values[i]); // values[i]=(contourArea(cntrs[i])*127.024)/100; } //int number = 300; /*HistogramDataset dataset = new HistogramDataset(); dataset.setType(HistogramType.FREQUENCY); XYSeries series = new XYSeries("Particle Size Distribution"); try{ dataset.addSeries("Histogram1",values,number,0,300); for(int i=0;i<300;i++){ if(dataset.getYValue(0,i)>0) series.add(dataset.getXValue(0,i),dataset.getYValue(0,i)); } // XYDataset xydataset = new XYSeriesCollection(series); }catch(Exception e) { e.printStackTrace(); } XYDataset xydataset = new XYSeriesCollection(series); String plotTitle = "Particle Size Distribution"; String xAxis = "particle diameter in microns"; String yAxis = "particle count"; PlotOrientation orientation = PlotOrientation.VERTICAL; boolean show = true; boolean toolTips = true; boolean urls = false; JFreeChart chart1 = ChartFactory.createXYLineChart(plotTitle,xAxis,yAxis,xydataset,orientation,show,toolTips,urls); JFreeChart chart2 = ChartFactory.createHistogram(plotTitle,xAxis,yAxis,dataset,orientation,show,toolTips,urls); int width1 = 500; int height1 = 500; ChartFrame frame1 = new ChartFrame("Coal PSD",chart1); frame1.setSize(width1,height1); frame1.setVisible(true); frame1.setDefaultCloseOperation(DISPOSE_ON_CLOSE); int width2 = 500; int height2 = 500; ChartFrame frame2 = new ChartFrame("Coal PSD",chart2); frame2.setSize(width2,height2); frame2.setVisible(true); frame2.setDefaultCloseOperation(DISPOSE_ON_CLOSE);*/ } catch (NullPointerException e) { System.err.println("..........Please load a valid Image.........."); } // TODO add your handling code here: }
From source file:cubesolversimulator.VisualInputForm.java
private void getContour() { Mat dilate = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(7, 7)); Imgproc.dilate(edge, edge, dilate);// w w w . ja va2s .c o m Imgproc.dilate(edge, edge, dilate); Highgui.imwrite("dilate.jpg", edge); List<MatOfPoint> contours = new ArrayList<>(); Imgproc.findContours(edge, contours, new Mat(), Imgproc.RETR_LIST, Imgproc.CHAIN_APPROX_SIMPLE); Imgproc.drawContours(contour, contours, -1, new Scalar(255, 255, 255)); Highgui.imwrite("Contour.jpg", contour); img4 = new JLabel(""); img4.setSize(jPanel7.getSize()); image4 = new ImageIcon(new ImageIcon("D:\\Project_work\\CubeSolverSimulator\\dilate.jpg").getImage() .getScaledInstance(img4.getWidth(), img4.getHeight(), Image.SCALE_FAST)); img4.setIcon(image4); img4.repaint(); jPanel7.add(img4); jPanel7.repaint(); findRect(contours); }