/**
 * 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
 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */
package org.openimaj.image.processing.face.detection.benchmarking;

import gnu.trove.set.hash.TDoubleHashSet;

import java.io.File;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

import org.openimaj.data.dataset.ListDataset;
import org.openimaj.image.objectdetection.filtering.OpenCVGrouping;
import org.openimaj.image.processing.face.detection.DetectedFace;
import org.openimaj.image.processing.face.detection.HaarCascadeDetector;
import org.openimaj.image.processing.face.detection.benchmarking.Matcher.Match;

public class FDDBEvaluation {
        public interface EvaluationDetector {
                List<? extends DetectedFace> getDetections(FDDBRecord record);
        }

        public List<Results> performEvaluation(ListDataset<FDDBRecord> dataset, EvaluationDetector detector) {
                // cumRes stores the cumulative results for all the images
                List<Results> cumRes = new ArrayList<Results>();
                final Matcher matcher = new Matcher();

                // Process each image
                final int numImages = dataset.size();
                for (int i = 0; i < numImages; i++) {
                        final FDDBRecord data = dataset.getInstance(i);
                        final String imName = data.getImageName();

                        final List<? extends DetectedFace> annot = data.getGroundTruth();
                        final List<? extends DetectedFace> det = detector.getDetections(data);

                        // imageResults holds the results for different thresholds
                        // applied to a single image
                        final List<Results> imageResults = new ArrayList<Results>();

                        if (det.size() == 0) {
                                // create the image results for zero detections
                                final Results r = new Results(imName, Double.MAX_VALUE, null, annot, det);
                                imageResults.add(r);
                        } else {
                                // find the unique values for detection scores
                                final double[] uniqueScores = getUniqueConfidences(det);

                                // For each unique score value st,
                                // (a) filter the detections with score >= st
                                // (b) compute the matching annot-det pairs
                                // (c) compute the result statistics
                                for (final double scoreThreshold : uniqueScores) {
                                        final ArrayList<DetectedFace> filteredDet = new ArrayList<DetectedFace>();
                                        // (a) filter the detections with score >= st
                                        for (int di = 0; di < det.size(); di++) {
                                                final DetectedFace rd = det.get(di);
                                                if (rd.getConfidence() >= scoreThreshold)
                                                        filteredDet.add(rd);
                                        }

                                        // (b) match annotations to detections
                                        final List<Match> mps = matcher.match(annot, filteredDet);

                                        // (c) compute the result statistics and append to the list
                                        final Results r = new Results(imName, scoreThreshold, mps, annot, filteredDet);
                                        imageResults.add(r);
                                }
                        }

                        // merge the list of results for this image (imageResults) with the
                        // global list (cumRes)
                        cumRes = Results.merge(cumRes, imageResults);
                }

                return cumRes;
        }

        /**
         * Get a list of unique confidences associated with the given list of faces.
         * 
         * @param faces
         *            the faces
         * @return the unique confidences, sorted in ascending order.
         */
        private double[] getUniqueConfidences(List<? extends DetectedFace> faces) {
                final TDoubleHashSet set = new TDoubleHashSet();

                for (final DetectedFace f : faces) {
                        set.add(f.getConfidence());
                }

                final double[] ret = set.toArray();

                Arrays.sort(ret);

                return ret;
        }

        public static void main(String[] args) throws IOException, InterruptedException {
                final File fddbGroundTruth = new File("/Users/jsh2/Downloads/FDDB-folds/FDDB-fold-01-ellipseList.txt");
                final File imageBase = new File("/Users/jsh2/Downloads/originalPics/");
                final FDDBDataset dataset = new FDDBDataset(fddbGroundTruth, imageBase, true);

                final HaarCascadeDetector det = HaarCascadeDetector.BuiltInCascade.frontalface_alt2.load();
                det.setGroupingFilter(new OpenCVGrouping(0));
                det.setMinSize(80);
                final EvaluationDetector evDet = new EvaluationDetector() {

                        @Override
                        public synchronized List<? extends DetectedFace> getDetections(FDDBRecord record) {
                                final List<DetectedFace> faces = det.detectFaces(record.getFImage());

                                // for (final DetectedFace f : faces)
                                // f.setConfidence(1);

                                return faces;
                        }
                };

                final FDDBEvaluation eval = new FDDBEvaluation();
                final List<Results> result = eval.performEvaluation(dataset, evDet);

                System.out.println(Results.getROCData(result));
        }
}