Examples with ListDisplayPanel boofcv.gui.ListDisplayPanel used on opensource projects

Example 16 with ListDisplayPanel

use of boofcv.gui.ListDisplayPanel in project BoofCV by lessthanoptimal.

the class ExampleDetectBlackPolygon method main.

public static void main(String[] args) {
    String[] imagesConvex = new String[] { "shapes/polygons01.jpg", "shapes/shapes02.png", "fiducial/image/examples/image01.jpg" };
    String[] imagesConcave = new String[] { "shapes/concave01.jpg" };
    ListDisplayPanel panel = new ListDisplayPanel();
    // first configure the detector to only detect convex shapes with 3 to 7 sides
    ConfigPolygonDetector config = new ConfigPolygonDetector(3, 7);
    DetectPolygonBinaryGrayRefine<GrayU8> detector = FactoryShapeDetector.polygon(config, GrayU8.class);
    processImages(imagesConvex, detector, panel);
    // now lets detect concave shapes with many sides
    config.detector.contourToPoly.maximumSides = 12;
    config.detector.contourToPoly.convex = false;
    detector = FactoryShapeDetector.polygon(config, GrayU8.class);
    processImages(imagesConcave, detector, panel);
    ShowImages.showWindow(panel, "Found Polygons", true);
}

Example 17 with ListDisplayPanel

use of boofcv.gui.ListDisplayPanel in project BoofCV by lessthanoptimal.

the class CommonFitPolygonChecks method renderDistortedRectangles.

public void renderDistortedRectangles(boolean blackShape, Class imageType) {
    orig = GeneralizedImageOps.createSingleBand(imageType, width, height);
    image = GeneralizedImageOps.createSingleBand(imageType, width, height);
    int white = blackShape ? this.white : this.black;
    int black = blackShape ? this.black : this.white;
    GImageMiscOps.fill(orig, white);
    GImageMiscOps.fill(image, white);
    distorted.clear();
    for (Rectangle2D_I32 q : rectangles) {
        if (fittingToBinaryImage)
            GImageMiscOps.fillRectangle(orig, black, q.x0, q.y0, q.x1 - q.x0 + 1, q.y1 - q.y0 + 1);
        else
            GImageMiscOps.fillRectangle(orig, black, q.x0, q.y0, q.x1 - q.x0, q.y1 - q.y0);
        Polygon2D_F64 tran = new Polygon2D_F64(4);
        AffinePointOps_F64.transform(transform, q.x0, q.y0, tran.get(0));
        AffinePointOps_F64.transform(transform, q.x0, q.y1, tran.get(1));
        AffinePointOps_F64.transform(transform, q.x1, q.y1, tran.get(2));
        AffinePointOps_F64.transform(transform, q.x1, q.y0, tran.get(3));
        distorted.add(tran);
    }
    new FDistort(orig, image).border(white).affine(transform).apply();
    if (showRendered) {
        ListDisplayPanel panel = new ListDisplayPanel();
        panel.addImage(orig, "Original");
        panel.addImage(image, "Image");
        ShowImages.showWindow(panel, "Rendered");
        try {
            Thread.sleep(4000);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
    }
}

Example 18 with ListDisplayPanel

use of boofcv.gui.ListDisplayPanel in project BoofCV by lessthanoptimal.

the class VisualizeSquareFiducial method process.

public void process(String nameImage, String nameIntrinsic) {
    CameraPinholeRadial intrinsic = nameIntrinsic == null ? null : (CameraPinholeRadial) CalibrationIO.load(nameIntrinsic);
    GrayF32 input = UtilImageIO.loadImage(nameImage, GrayF32.class);
    GrayF32 undistorted = new GrayF32(input.width, input.height);
    Detector detector = new Detector();
    if (intrinsic != null) {
        CameraPinholeRadial paramUndist = new CameraPinholeRadial();
        ImageDistort<GrayF32, GrayF32> undistorter = LensDistortionOps.changeCameraModel(AdjustmentType.EXPAND, BorderType.EXTENDED, intrinsic, new CameraPinhole(intrinsic), paramUndist, ImageType.single(GrayF32.class));
        detector.configure(new LensDistortionRadialTangential(paramUndist), paramUndist.width, paramUndist.height, false);
        undistorter.apply(input, undistorted);
    } else {
        undistorted.setTo(input);
    }
    detector.process(undistorted);
    System.out.println("Total Found: " + detector.squares.size());
    FastQueue<FoundFiducial> fiducials = detector.getFound();
    int N = Math.min(20, detector.squares.size());
    ListDisplayPanel squares = new ListDisplayPanel();
    for (int i = 0; i < N; i++) {
        squares.addImage(ConvertBufferedImage.convertTo(detector.squares.get(i), null), " " + i);
    }
    BufferedImage output = new BufferedImage(input.width, input.height, BufferedImage.TYPE_INT_RGB);
    VisualizeBinaryData.renderBinary(detector.getBinary(), false, output);
    Graphics2D g2 = output.createGraphics();
    g2.setRenderingHint(RenderingHints.KEY_ANTIALIASING, RenderingHints.VALUE_ANTIALIAS_ON);
    g2.setColor(Color.RED);
    g2.setStroke(new BasicStroke(2));
    if (intrinsic != null) {
        Point2Transform2_F64 add_p_to_p = LensDistortionOps.narrow(intrinsic).distort_F64(true, true);
        for (int i = 0; i < N; i++) {
            // add back in lens distortion
            Quadrilateral_F64 q = fiducials.get(i).distortedPixels;
            apply(add_p_to_p, q.a, q.a);
            apply(add_p_to_p, q.b, q.b);
            apply(add_p_to_p, q.c, q.c);
            apply(add_p_to_p, q.d, q.d);
            VisualizeShapes.draw(q, g2);
        }
    }
    BufferedImage outputGray = new BufferedImage(input.width, input.height, BufferedImage.TYPE_INT_RGB);
    ConvertBufferedImage.convertTo(undistorted, outputGray);
    g2 = outputGray.createGraphics();
    g2.setRenderingHint(RenderingHints.KEY_ANTIALIASING, RenderingHints.VALUE_ANTIALIAS_ON);
    for (int i = 0; i < N; i++) {
        // add back in lens distortion
        Quadrilateral_F64 q = fiducials.get(i).distortedPixels;
        // g2.setStroke(new BasicStroke(2));
        // VisualizeBinaryData.render(detector.getSquareDetector().getUsedContours(),Color.BLUE,outputGray);
        VisualizeShapes.drawArrowSubPixel(q, 3, 1, g2);
    }
    ShowImages.showWindow(output, "Binary");
    ShowImages.showWindow(outputGray, "Gray");
    ShowImages.showWindow(squares, "Candidates");
}

Example 19 with ListDisplayPanel

use of boofcv.gui.ListDisplayPanel in project BoofCV by lessthanoptimal.

the class ExampleRgbToGray method main.

public static void main(String[] args) {
    // load the image and convert it into a BoofCV data type
    BufferedImage buffered = UtilImageIO.loadImage(UtilIO.pathExample("segment/berkeley_man.jpg"));
    Planar<GrayU8> color = ConvertBufferedImage.convertFrom(buffered, true, ImageType.pl(3, GrayU8.class));
    // Declare storage space for converted gray scale images
    GrayU8 weighted = new GrayU8(color.width, color.height);
    GrayU8 unweighted = new GrayU8(color.width, color.height);
    // Now run a benchmark to demonstrate the speed differences between the two approaches.  Both are very fast...
    System.out.println("Running benchmark.  Should take a few seconds on a modern computer.\n");
    long startTime;
    int N = 2000;
    startTime = System.nanoTime();
    for (int i = 0; i < N; i++) {
        // weigh the bands based on how human vision sees each color
        ColorRgb.rgbToGray_Weighted(color, weighted);
    }
    double weightedFPS = N / ((System.nanoTime() - startTime) * 1e-9);
    startTime = System.nanoTime();
    for (int i = 0; i < N; i++) {
        // this equally averages all the bands together
        ConvertImage.average(color, unweighted);
    }
    double unweightedFPS = N / ((System.nanoTime() - startTime) * 1e-9);
    System.out.println("FPS  averaged over " + N + " images");
    System.out.println("      (higher is better)");
    System.out.println();
    System.out.printf("  weighted    %8.2f\n", weightedFPS);
    System.out.printf("  unweighted  %8.2f\n", unweightedFPS);
    System.out.println();
    System.out.printf("Unweighted is %6.1f times faster.\n", (unweightedFPS / weightedFPS));
    System.out.println();
    System.out.println("WARNING:  This is a poorly implemented microbenchmark " + "and results might not be accurate or consistent.");
    // Display the results
    ListDisplayPanel gui = new ListDisplayPanel();
    gui.addImage(weighted, "Weighted");
    gui.addImage(unweighted, "Unweighted");
    gui.addImage(buffered, "RGB");
    ShowImages.showWindow(gui, "RGB to Gray", true);
}

Example 20 with ListDisplayPanel

use of boofcv.gui.ListDisplayPanel in project BoofCV by lessthanoptimal.

the class ExampleThresholding method threshold.

public static void threshold(String imageName) {
    BufferedImage image = UtilImageIO.loadImage(imageName);
    // convert into a usable format
    GrayF32 input = ConvertBufferedImage.convertFromSingle(image, null, GrayF32.class);
    GrayU8 binary = new GrayU8(input.width, input.height);
    // Display multiple images in the same window
    ListDisplayPanel gui = new ListDisplayPanel();
    // Global Methods
    GThresholdImageOps.threshold(input, binary, ImageStatistics.mean(input), true);
    gui.addImage(VisualizeBinaryData.renderBinary(binary, false, null), "Global: Mean");
    GThresholdImageOps.threshold(input, binary, GThresholdImageOps.computeOtsu(input, 0, 255), true);
    gui.addImage(VisualizeBinaryData.renderBinary(binary, false, null), "Global: Otsu");
    GThresholdImageOps.threshold(input, binary, GThresholdImageOps.computeEntropy(input, 0, 255), true);
    gui.addImage(VisualizeBinaryData.renderBinary(binary, false, null), "Global: Entropy");
    // Local method
    GThresholdImageOps.localMean(input, binary, ConfigLength.fixed(57), 1.0, true, null, null);
    gui.addImage(VisualizeBinaryData.renderBinary(binary, false, null), "Local: Square");
    GThresholdImageOps.blockMinMax(input, binary, ConfigLength.fixed(21), 1.0, true, 15);
    gui.addImage(VisualizeBinaryData.renderBinary(binary, false, null), "Local: Block Min-Max");
    GThresholdImageOps.blockMean(input, binary, ConfigLength.fixed(21), 1.0, true);
    gui.addImage(VisualizeBinaryData.renderBinary(binary, false, null), "Local: Block Mean");
    GThresholdImageOps.blockOtsu(input, binary, false, ConfigLength.fixed(21), 0.5, 1.0, true);
    gui.addImage(VisualizeBinaryData.renderBinary(binary, false, null), "Local: Block Otsu");
    GThresholdImageOps.localGaussian(input, binary, ConfigLength.fixed(85), 1.0, true, null, null);
    gui.addImage(VisualizeBinaryData.renderBinary(binary, false, null), "Local: Gaussian");
    GThresholdImageOps.localSauvola(input, binary, ConfigLength.fixed(11), 0.30f, true);
    gui.addImage(VisualizeBinaryData.renderBinary(binary, false, null), "Local: Sauvola");
    // Sauvola is tuned for text image.  Change radius to make it run better in others.
    // Show the image image for reference
    gui.addImage(ConvertBufferedImage.convertTo(input, null), "Input Image");
    String fileName = imageName.substring(imageName.lastIndexOf('/') + 1);
    ShowImages.showWindow(gui, fileName);
}