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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) 2011-2017, 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.abst.feature.detect.interest;

import boofcv.alg.feature.detect.interest.EasyGeneralFeatureDetector;
import boofcv.alg.feature.detect.interest.GeneralFeatureDetector;
import boofcv.struct.QueueCorner;
import boofcv.struct.image.ImageGray;
import georegression.struct.point.Point2D_F64;
import georegression.struct.point.Point2D_I16;
import org.ddogleg.struct.FastQueue;

/**
 * Allows a {@link GeneralFeatureDetector} to be used inside a {@link DetectorInterestPointMulti}.  The number of sets
 * depend upon if minimums and/or maximums are found by the detector.
 *
 * @author Peter Abeles
 */
public class GeneralToInterestMulti, D extends ImageGray>
		implements DetectorInterestPointMulti
{
	// point detector configured to detect minimums and maximums
	protected EasyGeneralFeatureDetector detector;

	// scale of detected objects
	protected double radius;

	// list of found points
	protected FastQueue foundMin = new FastQueue<>(10, Point2D_F64.class, true);
	protected FastQueue foundMax = new FastQueue<>(10, Point2D_F64.class, true);

	// sets for each type of detected feature
	protected FoundPointSO sets[];

	public GeneralToInterestMulti(GeneralFeatureDetector detector,
								  double radius,
								  Class imageType, Class derivType) {
		this.detector = new EasyGeneralFeatureDetector<>(detector, imageType, derivType);
		this.radius = radius;

		if( detector.isDetectMinimums() && detector.isDetectMaximums()) {
			sets = new FoundPointSO[]{new FoundMin(), new FoundMax()};
		} else if( detector.isDetectMaximums() ){
			sets = new FoundPointSO[]{new FoundMax()};
		} else if( detector.isDetectMinimums()) {
			sets = new FoundPointSO[]{new FoundMin()};
		}
	}

	@Override
	public void detect(T input) {
		foundMin.reset();
		foundMax.reset();

		detector.detect(input,null);

		QueueCorner min = detector.getMinimums();
		for( int i = 0; i < min.size; i++ ) {
			Point2D_I16 p = min.get(i);
			foundMin.grow().set(p.x,p.y);
		}
		QueueCorner max = detector.getMaximums();
		for( int i = 0; i < max.size; i++ ) {
			Point2D_I16 p = max.get(i);
			foundMax.grow().set(p.x,p.y);
		}
	}

	@Override
	public int getNumberOfSets() {
		return sets.length;
	}

	@Override
	public FoundPointSO getFeatureSet(int set) {
		return sets[set];
	}

	private class FoundMin implements FoundPointSO {
		@Override
		public int getNumberOfFeatures() {
			return foundMin.size;
		}

		@Override
		public Point2D_F64 getLocation(int featureIndex) {
			return foundMin.get(featureIndex);
		}

		@Override
		public double getRadius(int featureIndex) {
			return radius;
		}

		@Override
		public double getOrientation(int featureIndex) {
			return 0;
		}
	}

	private class FoundMax implements FoundPointSO {
		@Override
		public int getNumberOfFeatures() {
			return foundMax.size;
		}

		@Override
		public Point2D_F64 getLocation(int featureIndex) {
			return foundMax.get(featureIndex);
		}

		@Override
		public double getRadius(int featureIndex) {
			return radius;
		}

		@Override
		public double getOrientation(int featureIndex) {
			return 0;
		}
	}
}