Examples with BackgroundModelStationary boofcv.alg.background.BackgroundModelStationary used on opensource projects

Example 1 with BackgroundModelStationary

use of boofcv.alg.background.BackgroundModelStationary 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 2 with BackgroundModelStationary

use of boofcv.alg.background.BackgroundModelStationary in project narchy by automenta.

the class ExampleBackgroundRemovalStationary method main.

public static void main(String[] args) {
    WebCam c = new WebCam();
    Tex output = new Tex();
    SpaceGraph.window(new Gridding(c.view(), output.view()), 800, 800);
    // 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);
    // 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(40, 0.0005f);
    configGaussian.initialVariance = 100;
    configGaussian.minimumDifference = 10f;
    // Comment/Uncomment to switch algorithms
    BackgroundModelStationary background = // FactoryBackgroundModel.stationaryBasic(new ConfigBackgroundBasic(35, 0.005f), imageType);
    FactoryBackgroundModel.stationaryGaussian(configGaussian, imageType);
    // Declare storage for segmented image.  1 = moving foreground and 0 = background
    GrayU8 segmented = new GrayU8(c.width, c.height);
    GrayF32 input = new GrayF32(c.width, c.height);
    BufferedImage segmentedVis = new BufferedImage(c.width, c.height, BufferedImage.TYPE_INT_RGB);
    new Loop(10f) {

        @Override
        public boolean next() {
            BufferedImage img = c.image;
            if (img != null) {
                ConvertBufferedImage.convertFrom(img, input, true);
                // long before = System.nanoTime();
                background.segment(input, segmented);
                background.updateBackground(input);
                byte[] b = segmented.data;
                for (int i = 0; i < b.length; i++) {
                    if (b[i] != 0)
                        b[i] = 127;
                }
                output.update(// segmented
                ConvertBufferedImage.convertTo(segmented, segmentedVis));
            }
            // }
            return true;
        }
    };
}