Java ShowImages.showWindow方法代码示例

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
@Override
public void run() {
    if (!streaming) {
        addMouseListener(panel);
    }
    JFrame window = ShowImages.showWindow(panel, PlaySet.class.getSimpleName(),true);
    window.addKeyListener(new KeyAdapter() {
        @Override
        public void keyTyped(KeyEvent e) {
            if (e.getKeyChar() == 'x' && previousSet != null) {
                System.out.println("'Not a Set!'");
                ImageSuppliers.WebcamSaverImageSupplier.save(image);
            }
        }
    });

    if (streaming) {
        while (true) {
            image = imageSupplier.get();
            newImage(image);
        }
    }
}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
public static void view(File directory) {
    ListDisplayPanel panel = new ListDisplayPanel();
    int numCols = 20;

    int numImagesPerLabel = -1;
    char prevNumLabel = ' ';
    for (File d : directory.listFiles((dir, name) -> !name.matches("\\..*"))) {
        String label = d.getName();
        BufferedImage[] bufferedImages = Arrays.stream(d.listFiles((dir, name) -> name.matches(".*\\.jpg")))
                .map(f -> UtilImageIO.loadImage(f.getAbsolutePath()))
                .map(bi -> resize(bi, bi.getWidth() / 3, bi.getHeight() / 3))
                .collect(Collectors.toList())
                .toArray(new BufferedImage[0]);
        panel.addItem(new ImageGridPanel((bufferedImages.length / numCols) + 1, numCols, bufferedImages), label);
        System.out.println(label + "\t" + bufferedImages.length);
        if (prevNumLabel != label.charAt(0)) {
            numImagesPerLabel = bufferedImages.length;
            prevNumLabel = label.charAt(0);
        } else if (numImagesPerLabel != bufferedImages.length) {
            throw new IllegalStateException("Expected " + numImagesPerLabel + " images, but only found " + bufferedImages.length + " for " + label);
        }
    }

    ShowImages.showWindow(panel, ViewLabelledImagesV2.class.getSimpleName(), true);
}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
protected void processRgb(FrameMode mode, ByteBuffer frame, int timestamp) {
	if (mode.getVideoFormat() != VideoFormat.RGB) {
		System.out.println("Bad rgb format!");
	}

	if (outRgb == null) {
		rgb.reshape(mode.getWidth(), mode.getHeight());
		outRgb = new BufferedImage(rgb.width, rgb.height, BufferedImage.TYPE_INT_RGB);
		guiRgb = ShowImages.showWindow(outRgb, "RGB Image");
	}

	App.bufferRgbToMsU8(frame, rgb);
	ConvertBufferedImage.convertTo_U8(rgb, outRgb, true);

	drawButton(buttonMove, outRgb);
	drawButton(buttonStop, outRgb);
	drawButton(buttonLeft, outRgb);
	drawButton(buttonRight, outRgb);

	processButtonStatePhaseTwo(buttonMove, outRgb);
	processButtonStatePhaseTwo(buttonStop, outRgb);
	processButtonStatePhaseTwo(buttonLeft, outRgb);
	processButtonStatePhaseTwo(buttonRight, outRgb);

	guiRgb.repaint();
}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
protected void processRgb(FrameMode mode, ByteBuffer frame, int timestamp) {
  if (mode.getVideoFormat() != VideoFormat.RGB) {
    System.out.println("Bad rgb format!");
  }

  System.out.println("Got rgb!   " + timestamp);

  if (outRgb == null) {
    rgb.reshape(mode.getWidth(), mode.getHeight());
    outRgb = new BufferedImage(rgb.width, rgb.height, BufferedImage.TYPE_INT_RGB);
    guiRgb = ShowImages.showWindow(outRgb, "RGB Image");
  }

  UtilOpenKinect.bufferRgbToMsU8(frame, rgb);
  ConvertBufferedImage.convertTo_U8(rgb, outRgb, true);

  guiRgb.repaint();
}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
public static void main(String args[]) {

//		ShowImageBlurApp<ImageFloat32> app
//				= new ShowImageBlurApp<ImageFloat32>(ImageFloat32.class);
		ShowLensDistortion<ImageUInt8> app
				= new ShowLensDistortion<ImageUInt8>(ImageUInt8.class);

		List<PathLabel> inputs = new ArrayList<PathLabel>();

		inputs.add(new PathLabel("shapes","../data/evaluation/shapes01.png"));
		inputs.add(new PathLabel("beach","../data/evaluation/scale/beach02.jpg"));
		inputs.add(new PathLabel("sunflowers","../data/evaluation/sunflowers.png"));

		app.setInputList(inputs);

		// wait for it to process one image so that the size isn't all screwed up
		while( !app.getHasProcessedImage() ) {
			Thread.yield();
		}

		ShowImages.showWindow(app, "Lens Distortion");
	}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
public static void nogenerics( ImageSingleBand input )
{
	Class inputType = input.getClass();
	Class derivType = GImageDerivativeOps.getDerivativeType(inputType);

	ImageSingleBand blurred = GeneralizedImageOps.createSingleBand(inputType, input.width, input.height);
	ImageSingleBand derivX = GeneralizedImageOps.createSingleBand(derivType, input.width, input.height);
	ImageSingleBand derivY = GeneralizedImageOps.createSingleBand(derivType, input.width, input.height);

	// Gaussian blur: Convolve a Gaussian kernel
	GBlurImageOps.gaussian(input, blurred, -1, blurRadius, null);

	// Calculate image's derivative
	GImageDerivativeOps.sobel(blurred, derivX, derivY, BorderType.EXTENDED);

	// display the results
	BufferedImage outputImage = VisualizeImageData.colorizeSign(derivX,null,-1);
	ShowImages.showWindow(outputImage,"Generalized "+inputType.getSimpleName());
}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
public void process( BufferedImage image ) {
	I input = GeneralizedImageOps.createSingleBand(imageType, image.getWidth(), image.getHeight());
	I blur = GeneralizedImageOps.createSingleBand(imageType, image.getWidth(), image.getHeight());

	ConvertBufferedImage.convertFromSingle(image, input, imageType);
	GBlurImageOps.gaussian(input, blur, -1, 2, null);

	DetectLineHoughFoot<I,D> alg =  FactoryDetectLineAlgs.houghFoot(6, 12, 5, 25, 10, imageType, derivType);

	ImageLinePanel gui = new ImageLinePanel();
	gui.setBackground(image);
	gui.setLines(alg.detect(blur));
	gui.setPreferredSize(new Dimension(image.getWidth(),image.getHeight()));

	BufferedImage renderedTran = VisualizeImageData.grayMagnitude(alg.getTransform().getTransform(),null,-1);
	BufferedImage renderedBinary = VisualizeBinaryData.renderBinary(alg.getBinary(), null);

	ShowImages.showWindow(renderedBinary,"Detected Edges");
	ShowImages.showWindow(renderedTran,"Parameter Space");
	ShowImages.showWindow(gui,"Detected Lines");
}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
public void process() throws IOException {
	parseFrame(0);

	outRgb = new BufferedImage(rgb.getWidth(),rgb.getHeight(),BufferedImage.TYPE_INT_RGB);
	outDepth = new BufferedImage(depth.getWidth(),depth.getHeight(),BufferedImage.TYPE_INT_RGB);

	gui = new ImageGridPanel(1,2,outRgb,outDepth);
	ShowImages.showWindow(gui,"Kinect Data");

	int frame = 1;
	while( true ) {
		parseFrame(frame++);
		ConvertBufferedImage.convertTo_U8(rgb,outRgb);
		VisualizeImageData.disparity(depth, outDepth, 0, UtilOpenKinect.FREENECT_DEPTH_MM_MAX_VALUE, 0);
		gui.repaint();
		BoofMiscOps.pause(30);
	}
}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
public void process( BufferedImage image ) {
	I input = GeneralizedImageOps.createSingleBand(imageType, image.getWidth(), image.getHeight());
	I blur = GeneralizedImageOps.createSingleBand(imageType, image.getWidth(), image.getHeight());

	ConvertBufferedImage.convertFromSingle(image, input, imageType);
	GBlurImageOps.gaussian(input, blur, -1, 2, null);

	DetectLineHoughPolar<I,D> alg =  FactoryDetectLineAlgs.houghPolar(5, 10, 2, Math.PI / 180, 25, 10, imageType, derivType);

	List<LineParametric2D_F32> lines = alg.detect(blur);

	ImageLinePanel gui = new ImageLinePanel();
	gui.setBackground(image);
	gui.setLines(lines);
	gui.setPreferredSize(new Dimension(image.getWidth(),image.getHeight()));

	BufferedImage renderedTran = VisualizeImageData.grayMagnitude(alg.getTransform().getTransform(),null,-1);
	BufferedImage renderedBinary = VisualizeBinaryData.renderBinary(alg.getBinary(), null);

	ShowImages.showWindow(renderedBinary,"Detected Edges");
	ShowImages.showWindow(renderedTran,"Parameter Space");
	ShowImages.showWindow(gui,"Detected Lines");
}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
public static void main( String args[] ) {
		Class type = ImageFloat32.class;
		Class derivType = type;

//		Class type = ImageUInt8.class;
//		Class derivType = ImageSInt16.class;

		VideoMosaicSequentialPointApp app = new VideoMosaicSequentialPointApp(type,derivType);

		List<PathLabel> inputs = new ArrayList<PathLabel>();
		inputs.add(new PathLabel("Plane 1", "../data/applet/mosaic/airplane01.mjpeg"));
		inputs.add(new PathLabel("Plane 2", "../data/applet/mosaic/airplane02.mjpeg"));
		inputs.add(new PathLabel("Shake", "../data/applet/shake.mjpeg"));

		app.setInputList(inputs);

		// wait for it to process one image so that the size isn't all screwed up
		while( !app.getHasProcessedImage() ) {
			Thread.yield();
		}

		ShowImages.showWindow(app, "Video Image Mosaic");
	}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
public static void main( String args[] ) {
	DemoBinaryImageLabelOpsApp app = new DemoBinaryImageLabelOpsApp(ImageFloat32.class);

	List<PathLabel> inputs = new ArrayList<PathLabel>();
	inputs.add(new PathLabel("particles","../data/evaluation/particles01.jpg"));
	inputs.add(new PathLabel("shapes","../data/evaluation/shapes01.png"));

	app.setInputList(inputs);

	// wait for it to process one image so that the size isn't all screwed up
	while( !app.getHasProcessedImage() ) {
		Thread.yield();
	}

	ShowImages.showWindow(app, "Label Binary Blobs");

	System.out.println("Done");
}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
/**
 * There is no real perfect way that everyone agrees on for converting color images into gray scale
 * images.  Two examples of how to convert a MultiSpectral image into a gray scale image are shown 
 * in this example.
 */
public static void convertToGray( BufferedImage input ) {
	// convert the BufferedImage into a MultiSpectral
	MultiSpectral<ImageUInt8> image = ConvertBufferedImage.convertFromMulti(input,null,ImageUInt8.class);
	
	ImageUInt8 gray = new ImageUInt8( image.width,image.height);
	
	// creates a gray scale image by averaging intensity value across pixels
	GPixelMath.averageBand(image, gray);
	BufferedImage outputAve = ConvertBufferedImage.convertTo(gray,null);

	// create an output image just from the first band
	BufferedImage outputBand0 = ConvertBufferedImage.convertTo(image.getBand(0),null);

	ShowImages.showWindow(outputAve,"Average");
	ShowImages.showWindow(outputBand0,"Band 0");
}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
@Override
public void updateGUI(BufferedImage guiImage, T origImage) {
	Graphics2D g2 = guiImage.createGraphics();

	for (int i = 0; i < corners.size(); i++) {
		Point2D_I16 pt = corners.get(i);

		g2.setColor(Color.BLACK);
		g2.fillOval(pt.x - 4, pt.y - 4, 9, 9);
		g2.setColor(Color.RED);
		g2.fillOval(pt.x - 2, pt.y - 2, 5, 5);
	}

	if (panel == null) {
		panel = ShowImages.showWindow(guiImage, "Image Sequence");
		addComponent(panel);
	} else {
		panel.setBufferedImage(guiImage);
		panel.repaint();
	}
}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
public static void main( String args[] ) {
		EvaluateInterpolateEnlargeApp app = new EvaluateInterpolateEnlargeApp(ImageFloat32.class);
//		EvaluateInterpolateEnlargeApp app = new EvaluateInterpolateEnlargeApp(ImageUInt8.class);

		app.setPreferredSize(new Dimension(500,500));

		app.setBaseDirectory("../data/applet/");
		app.loadInputData("../data/applet/interpolation.txt");

//		java.util.List<PathLabel> inputs = new ArrayList<PathLabel>();
//		inputs.add(new PathLabel("eye 1","../data/evaluation/eye01.jpg"));
//		inputs.add(new PathLabel("eye 2","../data/evaluation/eye02.jpg"));
//
//		app.setInputList(inputs);

		// wait for it to process one image so that the size isn't all screwed up
		while( !app.getHasProcessedImage() ) {
			Thread.yield();
		}

		ShowImages.showWindow(app,"Interpolation Enlarge");
	}
 

import boofcv.gui.image.ShowImages; //导入方法依赖的package包/类
public static void main( String args[] ) {
	RemoveLensDistortionApp app = new RemoveLensDistortionApp();

	// camera config, image left, image right
	String calibDir = "../data/applet/calibration/mono/Sony_DSC-HX5V_Chess/";
	String imageDir = "../data/evaluation/structure/";
	String bumbleDir = "../data/evaluation/calibration/stereo/Bumblebee2_Chess/";

	java.util.List<PathLabel> inputs = new ArrayList<PathLabel>();
	inputs.add(new PathLabel("Sony HX5V",calibDir + "intrinsic.xml",imageDir + "dist_cyto_01.jpg"));
	inputs.add(new PathLabel("BumbleBee2",bumbleDir+"intrinsicLeft.xml",bumbleDir + "left01.jpg"));

	app.setInputList(inputs);

	// wait for it to process one image so that the size isn't all screwed up
	while( !app.getHasProcessedImage() ) {
		Thread.yield();
	}
	ShowImages.showWindow(app, "Remove Lens Distortion");

	System.out.println("Done");
}