/*
 * Copyright (c) 2011-2016, 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.app.calib;

import boofcv.alg.geo.calibration.CalibrationObservation;
import boofcv.alg.geo.calibration.Zhang99CalibrationMatrixFromHomographies;
import boofcv.alg.geo.calibration.Zhang99ComputeTargetHomography;
import georegression.struct.point.Point2D_F64;
import org.ejml.data.DenseMatrix64F;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

/**
 * Estimates if there is enough geometry diversity to compute an initial estimate of the camera calibration parameters
 * by computing a linear estimate and looking at its singular values.  There should only be one null space.
 *
 * @author Peter Abeles
 */
public class ComputeGeometryScore {

	Zhang99ComputeTargetHomography computeHomography;
	Zhang99CalibrationMatrixFromHomographies computeCalib;

	List<DenseMatrix64F> homographies = new ArrayList<>();

	double score = 0;

	public ComputeGeometryScore(boolean assumeZeroSkew, List<Point2D_F64> worldPoints) {
		computeCalib = new Zhang99CalibrationMatrixFromHomographies(assumeZeroSkew);
		computeHomography = new Zhang99ComputeTargetHomography(worldPoints);
	}

	public void addObservations( CalibrationObservation observations ) {
		computeHomography.computeHomography(observations);
		homographies.add( computeHomography.getHomography().copy() );

		try {
			computeCalib.process(homographies);

			double values[] = computeCalib.getSvd().getSingularValues();
			Arrays.sort(values,0,3);

			System.out.println("raw singularity score = "+(values[1]/values[2]));

			// 0.2 was a threshold that was emperically determined
			score = Math.min(1.0,(values[1]/values[2])/0.2 );
		} catch( RuntimeException e ) {
			score = 0;
		}
	}

	/**
	 * A number from 0 to 1.0 for how close to having the correct geometry it is.  1.0 = done
	 */
	public double getScore() {
		return score;
	}
}