boofcv.examples.fiducial.ExampleFiducialImage Maven / Gradle / Ivy

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/*
 * Copyright (c) 2011-2019, Peter Abeles. All Rights Reserved.
 *
 * This file is part of BoofCV (http://boofcv.org).
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package boofcv.examples.fiducial;

import boofcv.abst.fiducial.SquareImage_to_FiducialDetector;
import boofcv.alg.distort.LensDistortionNarrowFOV;
import boofcv.alg.distort.brown.LensDistortionBrown;
import boofcv.factory.fiducial.ConfigFiducialImage;
import boofcv.factory.fiducial.FactoryFiducial;
import boofcv.factory.filter.binary.ConfigThreshold;
import boofcv.factory.filter.binary.ThresholdType;
import boofcv.gui.feature.VisualizeShapes;
import boofcv.gui.fiducial.VisualizeFiducial;
import boofcv.gui.image.ShowImages;
import boofcv.io.UtilIO;
import boofcv.io.calibration.CalibrationIO;
import boofcv.io.image.ConvertBufferedImage;
import boofcv.io.image.UtilImageIO;
import boofcv.struct.calib.CameraPinholeBrown;
import boofcv.struct.image.GrayF32;
import boofcv.struct.image.ImageType;
import georegression.struct.point.Point2D_F64;
import georegression.struct.se.Se3_F64;
import georegression.struct.shapes.Polygon2D_F64;

import java.awt.*;
import java.awt.image.BufferedImage;
import java.io.File;

import static boofcv.io.image.UtilImageIO.loadImage;

/**
 * Detects square binary fiducials inside an image, writes out there pose, and visualizes a virtual flat cube
 * above them in the input image.
 *
 * @author Peter Abeles
 */
public class ExampleFiducialImage {
	public static void main(String[] args) {

		String imagePath   = UtilIO.pathExample("fiducial/image/examples/");
		String patternPath = UtilIO.pathExample("fiducial/image/patterns/");

//		String imageName = "image00.jpg";
		String imageName = "image01.jpg";
//		String imageName = "image02.jpg";

		// load the lens distortion parameters and the input image
		CameraPinholeBrown param = CalibrationIO.load(new File(imagePath, "intrinsic.yaml"));
		LensDistortionNarrowFOV lensDistortion = new LensDistortionBrown(param);
		BufferedImage input = UtilImageIO.loadImage(imagePath, imageName);
		GrayF32 original = ConvertBufferedImage.convertFrom(input, true, ImageType.single(GrayF32.class));

		// Detect the fiducial
		SquareImage_to_FiducialDetector detector = FactoryFiducial.squareImage(
				new ConfigFiducialImage(), ConfigThreshold.local(ThresholdType.LOCAL_MEAN, 21), GrayF32.class);
//				new ConfigFiducialImage(), ConfigThreshold.fixed(100), GrayF32.class);

		// give it a description of all the targets
		double width = 4; // 4 cm
		detector.addPatternImage(loadImage(patternPath , "ke.png",          GrayF32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath , "dog.png",         GrayF32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath , "yu.png",          GrayF32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath , "yu_inverted.png", GrayF32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath , "pentarose.png",   GrayF32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath , "text_boofcv.png", GrayF32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath , "leaf01.png",      GrayF32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath , "leaf02.png",      GrayF32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath , "hand01.png",      GrayF32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath , "chicken.png",     GrayF32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath , "h2o.png",         GrayF32.class), 100, width);
		detector.addPatternImage(loadImage(patternPath , "yinyang.png",     GrayF32.class), 100, width);

		detector.setLensDistortion(lensDistortion,param.width,param.height);

		detector.detect(original);

		// print the results
		Graphics2D g2 = input.createGraphics();
		Se3_F64 targetToSensor = new Se3_F64();
		Point2D_F64 locationPixel = new Point2D_F64();
		Polygon2D_F64 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);
			}
		}

		ShowImages.showWindow(input,"Fiducials",true);
	}
}