Difference between revisions of "Example Fiducial Square Hamming"

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Demonstration how to detect square fiducials which match targets based on hamming distance, e.g. ArUci and AprilTags.
Demonstration how to detect square fiducials which match targets based on hamming distance, e.g. ArUco and AprilTags.


Example Code:
Example Code:
* [https://github.com/lessthanoptimal/BoofCV/blob/v0.39/examples/src/main/java/boofcv/examples/fiducial/ExampleFiducialHamming.java ExampleFiducialHamming.java]
* [https://github.com/lessthanoptimal/BoofCV/blob/v0.40/examples/src/main/java/boofcv/examples/fiducial/ExampleFiducialHamming.java ExampleFiducialHamming.java]


Concepts:
Concepts:
Line 61: Line 61:


// Load the image
// Load the image
BufferedImage buffered = UtilImageIO.loadImage(new File(directory, name).getPath());
BufferedImage buffered = UtilImageIO.loadImageNotNull(new File(directory, name).getPath());


// Convert to a BoofCV format
// Convert to a BoofCV format
Line 71: Line 71:
// Render a 3D compute on top of all detections
// Render a 3D compute on top of all detections
Graphics2D g2 = buffered.createGraphics();
Graphics2D g2 = buffered.createGraphics();
Se3_F64 targetToSensor = new Se3_F64();
var targetToSensor = new Se3_F64();
Point2D_F64 locationPixel = new Point2D_F64();
var locationPixel = new Point2D_F64();
Polygon2D_F64 bounds = new Polygon2D_F64();
var bounds = new Polygon2D_F64();
for (int i = 0; i < detector.totalFound(); i++) {
for (int i = 0; i < detector.totalFound(); i++) {
detector.getCenter(i, locationPixel);
detector.getCenter(i, locationPixel);

Latest revision as of 15:42, 17 January 2022

Demonstration how to detect square fiducials which match targets based on hamming distance, e.g. ArUco and AprilTags.

Example Code:

Concepts:

  • Fiducials
  • Pose estimation

Relevant Examples/Tutorials:

Videos

Example Code

/**
 * Hamming fiducials are an entire family of markers/tags which work by identifying unique ID's by minimizing
 * the hamming distance. This family includes ArUco, ArUco 3, AprilTag, and others. Several prebuilt dictionaries
 * are included with BoofCV and you can specify your own easily. Hamming tags have error correction capabilities
 * can are resiliant to noise. How resilient depends on the dictionary. In general the fewer unique IDs available
 * the better it is at error correction. The recommended dictionary is ARUCO_MIP_25h7.
 *
 * See:
 * Aruco https://www.uco.es/investiga/grupos/ava/node/26
 * AprilTag https://april.eecs.umich.edu/software/apriltag
 *
 * @author Peter Abeles
 */
public class ExampleFiducialHamming {
	public static void main( String[] args ) {
		String directory = UtilIO.pathExample("fiducial/square_hamming/aruco_25h7");

		// load the lens distortion parameters and the input image
		CameraPinholeBrown param = CalibrationIO.load(new File(directory, "intrinsic.yaml"));
		LensDistortionNarrowFOV lensDistortion = new LensDistortionBrown(param);

		// You need to create a different configuration for each dictionary type
		ConfigHammingMarker configMarker = ConfigHammingMarker.loadDictionary(HammingDictionary.ARUCO_MIP_25h7);
		FiducialDetector<GrayF32> detector = FactoryFiducial.squareHamming(configMarker, /*detector*/null, GrayF32.class);

		// Provide it lens parameters so that a 3D pose estimate is possible
		detector.setLensDistortion(lensDistortion, param.width, param.height);

		// Load and process all example images
		ListDisplayPanel gui = new ListDisplayPanel();
		for (int imageID = 1; imageID <= 3; imageID++) {
			String name = String.format("image%02d.jpg", imageID);
			System.out.println("processing: " + name);

			// Load the image
			BufferedImage buffered = UtilImageIO.loadImageNotNull(new File(directory, name).getPath());

			// Convert to a BoofCV format
			GrayF32 input = ConvertBufferedImage.convertFrom(buffered, (GrayF32)null);

			// Run the detector
			detector.detect(input);

			// Render a 3D compute on top of all detections
			Graphics2D g2 = buffered.createGraphics();
			var targetToSensor = new Se3_F64();
			var locationPixel = new Point2D_F64();
			var bounds = new Polygon2D_F64();
			for (int i = 0; i < detector.totalFound(); i++) {
				detector.getCenter(i, locationPixel);
				detector.getBounds(i, bounds);

				g2.setColor(new Color(50, 50, 255));
				g2.setStroke(new BasicStroke(10));
				VisualizeShapes.drawPolygon(bounds, true, 1.0, g2);

				if (detector.hasID())
					System.out.println("Target ID = " + detector.getId(i));
				if (detector.hasMessage())
					System.out.println("Message   = " + detector.getMessage(i));
				System.out.println("2D Image Location = " + locationPixel);

				if (detector.is3D()) {
					detector.getFiducialToCamera(i, targetToSensor);
					System.out.println("3D Location:");
					System.out.println(targetToSensor);
					VisualizeFiducial.drawCube(targetToSensor, param, detector.getWidth(i), 3, g2);
					VisualizeFiducial.drawLabelCenter(targetToSensor, param, "" + detector.getId(i), g2);
				} else {
					VisualizeFiducial.drawLabel(locationPixel, "" + detector.getId(i), g2);
				}
			}
			gui.addImage(buffered, name, ScaleOptions.ALL);
		}
		ShowImages.showWindow(gui, "Example Fiducial Hamming", true);
	}
}