Examples with ImageGridPanel boofcv.gui.image.ImageGridPanel used on opensource projects

Example 1 with ImageGridPanel

use of boofcv.gui.image.ImageGridPanel in project BoofCV by lessthanoptimal.

the class ExampleBackgroundRemovalMoving method main.

public static void main(String[] args) {
    // Example with a moving camera.  Highlights why motion estimation is sometimes required
    String fileName = UtilIO.pathExample("tracking/chipmunk.mjpeg");
    // Camera has a bit of jitter in it.  Static kinda works but motion reduces false positives
    // String fileName = UtilIO.pathExample("background/horse_jitter.mp4");
    // Comment/Uncomment to switch input image type
    ImageType imageType = ImageType.single(GrayF32.class);
    // ImageType imageType = ImageType.il(3, InterleavedF32.class);
    // ImageType imageType = ImageType.il(3, InterleavedU8.class);
    // Configure the feature detector
    ConfigGeneralDetector confDetector = new ConfigGeneralDetector();
    confDetector.threshold = 10;
    confDetector.maxFeatures = 300;
    confDetector.radius = 6;
    // Use a KLT tracker
    PointTracker tracker = FactoryPointTracker.klt(new int[] { 1, 2, 4, 8 }, confDetector, 3, GrayF32.class, null);
    // This estimates the 2D image motion
    ImageMotion2D<GrayF32, Homography2D_F64> motion2D = FactoryMotion2D.createMotion2D(500, 0.5, 3, 100, 0.6, 0.5, false, tracker, new Homography2D_F64());
    ConfigBackgroundBasic configBasic = new ConfigBackgroundBasic(30, 0.005f);
    // Configuration for Gaussian model.  Note that the threshold changes depending on the number of image bands
    // 12 = gray scale and 40 = color
    ConfigBackgroundGaussian configGaussian = new ConfigBackgroundGaussian(12, 0.001f);
    configGaussian.initialVariance = 64;
    configGaussian.minimumDifference = 5;
    // Note that GMM doesn't interpolate the input image. Making it harder to model object edges.
    // However it runs faster because of this.
    ConfigBackgroundGmm configGmm = new ConfigBackgroundGmm();
    configGmm.initialVariance = 1600;
    configGmm.significantWeight = 1e-1f;
    // Comment/Uncomment to switch background mode
    BackgroundModelMoving background = FactoryBackgroundModel.movingBasic(configBasic, new PointTransformHomography_F32(), imageType);
    // FactoryBackgroundModel.movingGaussian(configGaussian, new PointTransformHomography_F32(), imageType);
    // FactoryBackgroundModel.movingGmm(configGmm,new PointTransformHomography_F32(), imageType);
    background.setUnknownValue(1);
    MediaManager media = DefaultMediaManager.INSTANCE;
    SimpleImageSequence video = media.openVideo(fileName, background.getImageType());
    // media.openCamera(null,640,480,background.getImageType());
    // ====== Initialize Images
    // storage for segmented image.  Background = 0, Foreground = 1
    GrayU8 segmented = new GrayU8(video.getNextWidth(), video.getNextHeight());
    // Grey scale image that's the input for motion estimation
    GrayF32 grey = new GrayF32(segmented.width, segmented.height);
    // coordinate frames
    Homography2D_F32 firstToCurrent32 = new Homography2D_F32();
    Homography2D_F32 homeToWorld = new Homography2D_F32();
    homeToWorld.a13 = grey.width / 2;
    homeToWorld.a23 = grey.height / 2;
    // Create a background image twice the size of the input image.  Tell it that the home is in the center
    background.initialize(grey.width * 2, grey.height * 2, homeToWorld);
    BufferedImage visualized = new BufferedImage(segmented.width, segmented.height, BufferedImage.TYPE_INT_RGB);
    ImageGridPanel gui = new ImageGridPanel(1, 2);
    gui.setImages(visualized, visualized);
    ShowImages.showWindow(gui, "Detections", true);
    double fps = 0;
    // smoothing factor for FPS
    double alpha = 0.01;
    while (video.hasNext()) {
        ImageBase input = video.next();
        long before = System.nanoTime();
        GConvertImage.convert(input, grey);
        if (!motion2D.process(grey)) {
            throw new RuntimeException("Should handle this scenario");
        }
        Homography2D_F64 firstToCurrent64 = motion2D.getFirstToCurrent();
        ConvertMatrixData.convert(firstToCurrent64, firstToCurrent32);
        background.segment(firstToCurrent32, input, segmented);
        background.updateBackground(firstToCurrent32, input);
        long after = System.nanoTime();
        fps = (1.0 - alpha) * fps + alpha * (1.0 / ((after - before) / 1e9));
        VisualizeBinaryData.renderBinary(segmented, false, visualized);
        gui.setImage(0, 0, (BufferedImage) video.getGuiImage());
        gui.setImage(0, 1, visualized);
        gui.repaint();
        System.out.println("FPS = " + fps);
        try {
            Thread.sleep(5);
        } catch (InterruptedException e) {
        }
    }
}

Example 2 with ImageGridPanel

use of boofcv.gui.image.ImageGridPanel in project BoofCV by lessthanoptimal.

the class ExampleBackgroundRemovalStationary method main.

public static void main(String[] args) {
    String fileName = UtilIO.pathExample("background/street_intersection.mp4");
    // String fileName = UtilIO.pathExample("background/rubixfire.mp4"); // dynamic background
    // String fileName = UtilIO.pathExample("background/horse_jitter.mp4"); // degraded performance because of jitter
    // String fileName = UtilIO.pathExample("tracking/chipmunk.mjpeg"); // Camera moves.  Stationary will fail here
    // Comment/Uncomment to switch input image type
    ImageType imageType = ImageType.single(GrayF32.class);
    // ImageType imageType = ImageType.il(3, InterleavedF32.class);
    // ImageType imageType = ImageType.il(3, InterleavedU8.class);
    ConfigBackgroundGmm configGmm = new ConfigBackgroundGmm();
    // Comment/Uncomment to switch algorithms
    BackgroundModelStationary background = FactoryBackgroundModel.stationaryBasic(new ConfigBackgroundBasic(35, 0.005f), imageType);
    // FactoryBackgroundModel.stationaryGmm(configGmm, imageType);
    MediaManager media = DefaultMediaManager.INSTANCE;
    SimpleImageSequence video = media.openVideo(fileName, background.getImageType());
    // media.openCamera(null,640,480,background.getImageType());
    // Declare storage for segmented image.  1 = moving foreground and 0 = background
    GrayU8 segmented = new GrayU8(video.getNextWidth(), video.getNextHeight());
    BufferedImage visualized = new BufferedImage(segmented.width, segmented.height, BufferedImage.TYPE_INT_RGB);
    ImageGridPanel gui = new ImageGridPanel(1, 2);
    gui.setImages(visualized, visualized);
    ShowImages.showWindow(gui, "Static Scene: Background Segmentation", true);
    double fps = 0;
    // smoothing factor for FPS
    double alpha = 0.01;
    while (video.hasNext()) {
        ImageBase input = video.next();
        long before = System.nanoTime();
        background.updateBackground(input, segmented);
        long after = System.nanoTime();
        fps = (1.0 - alpha) * fps + alpha * (1.0 / ((after - before) / 1e9));
        VisualizeBinaryData.renderBinary(segmented, false, visualized);
        gui.setImage(0, 0, (BufferedImage) video.getGuiImage());
        gui.setImage(0, 1, visualized);
        gui.repaint();
        System.out.println("FPS = " + fps);
        try {
            Thread.sleep(5);
        } catch (InterruptedException e) {
        }
    }
    System.out.println("done!");
}

Example 3 with ImageGridPanel

use of boofcv.gui.image.ImageGridPanel in project BoofCV by lessthanoptimal.

the class ExampleVideoMosaic method main.

public static void main(String[] args) {
    // Configure the feature detector
    ConfigGeneralDetector confDetector = new ConfigGeneralDetector();
    confDetector.threshold = 1;
    confDetector.maxFeatures = 300;
    confDetector.radius = 3;
    // Use a KLT tracker
    PointTracker<GrayF32> tracker = FactoryPointTracker.klt(new int[] { 1, 2, 4, 8 }, confDetector, 3, GrayF32.class, GrayF32.class);
    // This estimates the 2D image motion
    // An Affine2D_F64 model also works quite well.
    ImageMotion2D<GrayF32, Homography2D_F64> motion2D = FactoryMotion2D.createMotion2D(220, 3, 2, 30, 0.6, 0.5, false, tracker, new Homography2D_F64());
    // wrap it so it output color images while estimating motion from gray
    ImageMotion2D<Planar<GrayF32>, Homography2D_F64> motion2DColor = new PlToGrayMotion2D<>(motion2D, GrayF32.class);
    // This fuses the images together
    StitchingFromMotion2D<Planar<GrayF32>, Homography2D_F64> stitch = FactoryMotion2D.createVideoStitch(0.5, motion2DColor, ImageType.pl(3, GrayF32.class));
    // Load an image sequence
    MediaManager media = DefaultMediaManager.INSTANCE;
    String fileName = UtilIO.pathExample("mosaic/airplane01.mjpeg");
    SimpleImageSequence<Planar<GrayF32>> video = media.openVideo(fileName, ImageType.pl(3, GrayF32.class));
    Planar<GrayF32> frame = video.next();
    // shrink the input image and center it
    Homography2D_F64 shrink = new Homography2D_F64(0.5, 0, frame.width / 4, 0, 0.5, frame.height / 4, 0, 0, 1);
    shrink = shrink.invert(null);
    // The mosaic will be larger in terms of pixels but the image will be scaled down.
    // To change this into stabilization just make it the same size as the input with no shrink.
    stitch.configure(frame.width, frame.height, shrink);
    // process the first frame
    stitch.process(frame);
    // Create the GUI for displaying the results + input image
    ImageGridPanel gui = new ImageGridPanel(1, 2);
    gui.setImage(0, 0, new BufferedImage(frame.width, frame.height, BufferedImage.TYPE_INT_RGB));
    gui.setImage(0, 1, new BufferedImage(frame.width, frame.height, BufferedImage.TYPE_INT_RGB));
    gui.setPreferredSize(new Dimension(3 * frame.width, frame.height * 2));
    ShowImages.showWindow(gui, "Example Mosaic", true);
    boolean enlarged = false;
    // process the video sequence one frame at a time
    while (video.hasNext()) {
        frame = video.next();
        if (!stitch.process(frame))
            throw new RuntimeException("You should handle failures");
        // if the current image is close to the image border recenter the mosaic
        StitchingFromMotion2D.Corners corners = stitch.getImageCorners(frame.width, frame.height, null);
        if (nearBorder(corners.p0, stitch) || nearBorder(corners.p1, stitch) || nearBorder(corners.p2, stitch) || nearBorder(corners.p3, stitch)) {
            stitch.setOriginToCurrent();
            // only enlarge the image once
            if (!enlarged) {
                enlarged = true;
                // double the image size and shift it over to keep it centered
                int widthOld = stitch.getStitchedImage().width;
                int heightOld = stitch.getStitchedImage().height;
                int widthNew = widthOld * 2;
                int heightNew = heightOld * 2;
                int tranX = (widthNew - widthOld) / 2;
                int tranY = (heightNew - heightOld) / 2;
                Homography2D_F64 newToOldStitch = new Homography2D_F64(1, 0, -tranX, 0, 1, -tranY, 0, 0, 1);
                stitch.resizeStitchImage(widthNew, heightNew, newToOldStitch);
                gui.setImage(0, 1, new BufferedImage(widthNew, heightNew, BufferedImage.TYPE_INT_RGB));
            }
            corners = stitch.getImageCorners(frame.width, frame.height, null);
        }
        // display the mosaic
        ConvertBufferedImage.convertTo(frame, gui.getImage(0, 0), true);
        ConvertBufferedImage.convertTo(stitch.getStitchedImage(), gui.getImage(0, 1), true);
        // draw a red quadrilateral around the current frame in the mosaic
        Graphics2D g2 = gui.getImage(0, 1).createGraphics();
        g2.setColor(Color.RED);
        g2.drawLine((int) corners.p0.x, (int) corners.p0.y, (int) corners.p1.x, (int) corners.p1.y);
        g2.drawLine((int) corners.p1.x, (int) corners.p1.y, (int) corners.p2.x, (int) corners.p2.y);
        g2.drawLine((int) corners.p2.x, (int) corners.p2.y, (int) corners.p3.x, (int) corners.p3.y);
        g2.drawLine((int) corners.p3.x, (int) corners.p3.y, (int) corners.p0.x, (int) corners.p0.y);
        gui.repaint();
        // throttle the speed just in case it's on a fast computer
        BoofMiscOps.pause(50);
    }
}

Example 4 with ImageGridPanel

use of boofcv.gui.image.ImageGridPanel in project BoofCV by lessthanoptimal.

the class ExampleVideoStabilization method main.

public static void main(String[] args) {
    // Configure the feature detector
    ConfigGeneralDetector confDetector = new ConfigGeneralDetector();
    confDetector.threshold = 10;
    confDetector.maxFeatures = 300;
    confDetector.radius = 2;
    // Use a KLT tracker
    PointTracker<GrayF32> tracker = FactoryPointTracker.klt(new int[] { 1, 2, 4, 8 }, confDetector, 3, GrayF32.class, GrayF32.class);
    // This estimates the 2D image motion
    // An Affine2D_F64 model also works quite well.
    ImageMotion2D<GrayF32, Homography2D_F64> motion2D = FactoryMotion2D.createMotion2D(200, 3, 2, 30, 0.6, 0.5, false, tracker, new Homography2D_F64());
    // wrap it so it output color images while estimating motion from gray
    ImageMotion2D<Planar<GrayF32>, Homography2D_F64> motion2DColor = new PlToGrayMotion2D<>(motion2D, GrayF32.class);
    // This fuses the images together
    StitchingFromMotion2D<Planar<GrayF32>, Homography2D_F64> stabilize = FactoryMotion2D.createVideoStitch(0.5, motion2DColor, ImageType.pl(3, GrayF32.class));
    // Load an image sequence
    MediaManager media = DefaultMediaManager.INSTANCE;
    String fileName = UtilIO.pathExample("shake.mjpeg");
    SimpleImageSequence<Planar<GrayF32>> video = media.openVideo(fileName, ImageType.pl(3, GrayF32.class));
    Planar<GrayF32> frame = video.next();
    // The output image size is the same as the input image size
    stabilize.configure(frame.width, frame.height, null);
    // process the first frame
    stabilize.process(frame);
    // Create the GUI for displaying the results + input image
    ImageGridPanel gui = new ImageGridPanel(1, 2);
    gui.setImage(0, 0, new BufferedImage(frame.width, frame.height, BufferedImage.TYPE_INT_RGB));
    gui.setImage(0, 1, new BufferedImage(frame.width, frame.height, BufferedImage.TYPE_INT_RGB));
    gui.autoSetPreferredSize();
    ShowImages.showWindow(gui, "Example Stabilization", true);
    // process the video sequence one frame at a time
    while (video.hasNext()) {
        if (!stabilize.process(video.next()))
            throw new RuntimeException("Don't forget to handle failures!");
        // display the stabilized image
        ConvertBufferedImage.convertTo(frame, gui.getImage(0, 0), true);
        ConvertBufferedImage.convertTo(stabilize.getStitchedImage(), gui.getImage(0, 1), true);
        gui.repaint();
        // throttle the speed just in case it's on a fast computer
        BoofMiscOps.pause(50);
    }
}

Example 5 with ImageGridPanel

use of boofcv.gui.image.ImageGridPanel in project BoofCV by lessthanoptimal.

the class ExampleFourierTransform method displayTransform.

/**
 * Display the fourier transform's magnitude and phase.
 */
public static void displayTransform(InterleavedF32 transform, String name) {
    // declare storage
    GrayF32 magnitude = new GrayF32(transform.width, transform.height);
    GrayF32 phase = new GrayF32(transform.width, transform.height);
    // Make a copy so that you don't modify the input
    transform = transform.clone();
    // shift the zero-frequency into the image center, as is standard in image processing
    DiscreteFourierTransformOps.shiftZeroFrequency(transform, true);
    // Compute the transform's magnitude and phase
    DiscreteFourierTransformOps.magnitude(transform, magnitude);
    DiscreteFourierTransformOps.phase(transform, phase);
    // Convert it to a log scale for visibility
    PixelMath.log(magnitude, magnitude);
    // Display the results
    BufferedImage visualMag = VisualizeImageData.grayMagnitude(magnitude, null, -1);
    BufferedImage visualPhase = VisualizeImageData.colorizeSign(phase, null, Math.PI);
    ImageGridPanel dual = new ImageGridPanel(1, 2, visualMag, visualPhase);
    ShowImages.showWindow(dual, "Magnitude and Phase of " + name);
}