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BoofCV is an open source Java library for real-time computer vision and robotics applications.
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/*
 * Copyright (c) 2021, 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.alg.fiducial.calib;

import boofcv.alg.descriptor.DescriptorDistance;
import boofcv.alg.fiducial.square.BaseDetectFiducialSquare;
import boofcv.alg.fiducial.square.FoundFiducial;
import boofcv.struct.image.ImageGray;
import georegression.struct.shapes.Quadrilateral_F64;
import org.ddogleg.struct.DogArray;

import java.util.List;

/**
 * A fiducial composed of {@link boofcv.alg.fiducial.square.BaseDetectFiducialSquare} intended for use in calibration.
 * It allows parts of the fiducial to be visible and uniquely determined across multiple cameras. The algorithm
 * simply looks for the expected fiducials in an image and saves the corners that they appear at. Does not check to
 * see if the ordering is correct. If the same fiducial appears multiple times that fiducial is ignored. Only one
 * grid fiducial is expected to be visible at any time.
 *
 * The user must provide a set of fiducial ID numbers. Each unique numbers corresponds to an expected fiducial. The
 * first number in the list refers to the fiducial in the top left corner (minus X and positive Y) in the fiducial's
 * frame. The other elements are added in a row-major order.
 *
 * 
 * 
 * 
 * Example of a grid of square binary fiducials. Any square fiducial can be used, including those with images inside.
 *
 * @author Peter Abeles
 */
public class DetectFiducialSquareGrid> {

	// dimension of grid. This only refers to black squares and not the white space between
	int numRows;
	int numCols;

	// expected id numbers of each fiducials in row major grid order
	long numbers[];

	// square fiducial detector
	BaseDetectFiducialSquare detector;

	// found squares inside the image
	DogArray detections = new DogArray<>(Detection::new);

	/**
	 * Configures the fiducial detector.
	 *
	 * @param numRows Number of rows in the grid
	 * @param numCols Number of columns in the grd
	 * @param numbers The fiducial ID numbers its expected to see. Order matters.
	 * @param detector Fiducial detector
	 */
	public DetectFiducialSquareGrid( int numRows, int numCols, long[] numbers,
									 BaseDetectFiducialSquare detector ) {
		this.numRows = numRows;
		this.numCols = numCols;
		this.numbers = numbers;
		this.detector = detector;
	}

	/**
	 * Searches for the fiducial inside the image.
	 * If at least a partial match is found true is returned.
	 *
	 * @param input Input image
	 * @return true if at least one of the component fiducials is detected. False otherwise
	 */
	public boolean detect( T input ) {

		detections.reset();

		detector.process(input);

		DogArray found = detector.getFound();

		for (int i = 0; i < found.size(); i++) {
			FoundFiducial fid = found.get(i);

			int gridIndex = isExpected(fid.id);
			if (gridIndex >= 0) {
				Detection d = lookupDetection(fid.id, gridIndex);
				d.location.setTo(fid.distortedPixels);
				d.numDetected++;
			}
		}

		for (int i = detections.size - 1; i >= 0; i--) {
			if (detections.get(i).numDetected != 1) {
				detections.remove(i);
			}
		}

		return detections.size > 0;
	}

	/**
	 * Checks to see if the provided ID number is expected or not
	 *
	 * @param found Fiducial ID number
	 * @return true if it's looking for this ID number
	 */
	private int isExpected( long found ) {

		int bestHamming = 2;
		int bestNumber = -1;
		for (int i = 0; i < numbers.length; i++) {

			int hamming = DescriptorDistance.hamming((int)found ^ (int)numbers[i]);

			if (hamming < bestHamming) {
				bestHamming = hamming;
				bestNumber = i;
			}
		}
		return bestNumber;
	}

	/**
	 * Looks up a detection given the fiducial ID number. If not seen before the gridIndex is saved and
	 * a new instance returned.
	 */
	private Detection lookupDetection( long found, int gridIndex ) {
		for (int i = 0; i < detections.size(); i++) {
			Detection d = detections.get(i);
			if (d.id == found) {
				return d;
			}
		}

		Detection d = detections.grow();
		d.reset();
		d.id = found;
		d.gridIndex = gridIndex;

		return d;
	}

	public List getDetections() {
		return detections.toList();
	}

	public BaseDetectFiducialSquare getDetector() {
		return detector;
	}

	/**
	 * A detected inner fiducial. Which one, where it is.
	 */
	public static class Detection {
		// number of times it was detected. Internally used to remove multiple detections
		public int numDetected;
		// location of each detected corner.
		public Quadrilateral_F64 location = new Quadrilateral_F64();
		// the id of the detection
		public long id;
		// where in the grid this detection belongs.
		public int gridIndex;

		public void reset() {
			numDetected = 0;
			id = -1;
			gridIndex = -1;
			location.a.setTo(0, 0);
			location.b.setTo(0, 0);
			location.c.setTo(0, 0);
			location.d.setTo(0, 0);
		}
	}
}