/**
 * Copyright (c) 2011, The University of Southampton and the individual contributors.
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without modification,
 * are permitted provided that the following conditions are met:
 *
 *   *  Redistributions of source code must retain the above copyright notice,
 *      this list of conditions and the following disclaimer.
 *
 *   *  Redistributions in binary form must reproduce the above copyright notice,
 *      this list of conditions and the following disclaimer in the documentation
 *      and/or other materials provided with the distribution.
 *
 *   *  Neither the name of the University of Southampton nor the names of its
 *      contributors may be used to endorse or promote products derived from this
 *      software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
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 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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package org.openimaj.image.feature.global;

import gnu.trove.map.hash.TObjectFloatHashMap;
import gnu.trove.procedure.TObjectFloatProcedure;

import org.openimaj.citation.annotation.Reference;
import org.openimaj.citation.annotation.ReferenceType;
import org.openimaj.feature.DoubleFV;
import org.openimaj.feature.FeatureVectorProvider;
import org.openimaj.image.MBFImage;
import org.openimaj.image.analyser.ImageAnalyser;
import org.openimaj.image.pixel.ConnectedComponent;
import org.openimaj.image.pixel.PixelSet;
import org.openimaj.image.saliency.AchantaSaliency;
import org.openimaj.image.saliency.YehSaliency;
import org.openimaj.image.segmentation.FelzenszwalbHuttenlocherSegmenter;
import org.openimaj.math.geometry.point.Point2dImpl;

/**
 * Implementation of the rule-of-thirds algorithm described by Yeh et al.
 * <p>
 * I've assumed that the distances to the power-points should be normalized with
 * respect to the image size - this isn't explicit in the paper, but given that
 * the sigma of the gaussian is fixed, it seems likely...
 *
 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
 */
@Reference(
                type = ReferenceType.Inproceedings,
                author = { "Che-Hua Yeh", "Yuan-Chen Ho", "Brian A. Barsky", "Ming Ouhyoung" },
                title = "Personalized Photograph Ranking and Selection System",
                year = "2010",
                booktitle = "Proceedings of ACM Multimedia",
                pages = { "211", "220" },
                month = "October",
                customData = { "location", "Florence, Italy" })
public class RuleOfThirds implements ImageAnalyser<MBFImage>, FeatureVectorProvider<DoubleFV> {
        private static final double SIGMA = 0.17;
        private static final Point2dImpl[] powerPoints = getPowerPoints();

        YehSaliency saliencyGenerator;
        private double asSum;
        private double aseSum;

        /**
         * Construct a new {@link RuleOfThirds} with the default settings for the
         * {@link YehSaliency} algorithm.
         */
        public RuleOfThirds() {
                saliencyGenerator = new YehSaliency();
        }

        /**
         * Construct a new {@link RuleOfThirds} with the given values for the
         * {@link YehSaliency} algorithm.
         *
         * @param saliencySigma
         *            smoothing for the {@link AchantaSaliency} class
         * @param segmenterSigma
         *            smoothing for {@link FelzenszwalbHuttenlocherSegmenter}.
         * @param k
         *            k value for {@link FelzenszwalbHuttenlocherSegmenter}.
         * @param minSize
         *            minimum region size for
         *            {@link FelzenszwalbHuttenlocherSegmenter}.
         */
        public RuleOfThirds(float saliencySigma, float segmenterSigma, float k, int minSize) {
                saliencyGenerator = new YehSaliency(saliencySigma, segmenterSigma, k, minSize);
        }

        @Override
        public DoubleFV getFeatureVector() {
                if (asSum == 0)
                        new DoubleFV(new double[] { 0 });
                return new DoubleFV(new double[] { aseSum / asSum });
        }

        /*
         * (non-Javadoc)
         *
         * @see
         * org.openimaj.image.processor.ImageProcessor#processImage(org.openimaj
         * .image.Image)
         */
        @Override
        public void analyseImage(MBFImage image) {
                final int width = image.getWidth();
                final int height = image.getHeight();

                image.analyseWith(saliencyGenerator);
                final TObjectFloatHashMap<ConnectedComponent> componentMap = saliencyGenerator.getSaliencyComponents();

                asSum = 0;
                aseSum = 0;
                componentMap.forEachEntry(new TObjectFloatProcedure<ConnectedComponent>() {
                        @Override
                        public boolean execute(ConnectedComponent c, float s) {
                                final double as = c.calculateArea() * s;

                                final double D = closestDistance(c, width, height);

                                asSum += as;
                                aseSum += as * Math.exp(-(D * D) / (2 * SIGMA));

                                return true;
                        }
                });
        }

        private double closestDistance(PixelSet cc, int width, int height) {
                final double centroid[] = cc.calculateCentroid();
                double minDistance = Double.MAX_VALUE;

                for (final Point2dImpl pt : powerPoints) {
                        final double dx = (centroid[0] / width) - pt.x;
                        final double dy = (centroid[1] / width) - pt.y;
                        final double d = dx * dx + dy * dy;

                        if (d < minDistance)
                                minDistance = d;
                }

                return Math.sqrt(minDistance);
        }

        private static Point2dImpl[] getPowerPoints() {
                return new Point2dImpl[] {
                                new Point2dImpl(1 / 3f, 1 / 3f),
                                new Point2dImpl(2 / 3f, 1 / 3f),
                                new Point2dImpl(1 / 3f, 2 / 3f),
                                new Point2dImpl(2 / 3f, 2 / 3f) };
        }
}