001/**
002 * Copyright (c) 2011, The University of Southampton and the individual contributors.
003 * All rights reserved.
004 *
005 * Redistribution and use in source and binary forms, with or without modification,
006 * are permitted provided that the following conditions are met:
007 *
008 *   *  Redistributions of source code must retain the above copyright notice,
009 *      this list of conditions and the following disclaimer.
010 *
011 *   *  Redistributions in binary form must reproduce the above copyright notice,
012 *      this list of conditions and the following disclaimer in the documentation
013 *      and/or other materials provided with the distribution.
014 *
015 *   *  Neither the name of the University of Southampton nor the names of its
016 *      contributors may be used to endorse or promote products derived from this
017 *      software without specific prior written permission.
018 *
019 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
020 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
021 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
022 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
023 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
024 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
025 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
026 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
027 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
028 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
029 */
030package org.openimaj.ml.annotation.model;
031
032import java.util.ArrayList;
033import java.util.List;
034import java.util.Set;
035
036import org.openimaj.feature.FeatureExtractor;
037import org.openimaj.math.model.EstimatableModel;
038import org.openimaj.ml.annotation.Annotated;
039import org.openimaj.ml.annotation.BatchAnnotator;
040import org.openimaj.ml.annotation.ScoredAnnotation;
041import org.openimaj.util.pair.IndependentPair;
042
043/**
044 * An {@link BatchAnnotator} backed by a {@link EstimatableModel}. This only really makes
045 * sense if the dependent variable of the model can take a set of discrete
046 * values.
047 * 
048 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
049 * @author Sina Samangooei (ss@ecs.soton.ac.uk)
050 * 
051 * @param <OBJECT>
052 *            Type of object being annotated
053 * @param <ANNOTATION>
054 *            Type of annotation
055 * @param <FEATURE>
056 *            Type of feature extracted by the extractor
057 */
058public class ModelAnnotator<OBJECT, ANNOTATION, FEATURE>
059                extends
060                BatchAnnotator<OBJECT, ANNOTATION>
061{
062        EstimatableModel<FEATURE, ANNOTATION> model;
063        Set<ANNOTATION> annotations;
064        private FeatureExtractor<FEATURE, OBJECT> extractor;
065
066        /**
067         * Construct with the given parameters.
068         * 
069         * @param extractor
070         *            The feature extractor
071         * @param model
072         *            The model
073         * @param annotations
074         *            The set of annotations that the model can produce
075         */
076        public ModelAnnotator(FeatureExtractor<FEATURE, OBJECT> extractor, EstimatableModel<FEATURE, ANNOTATION> model,
077                        Set<ANNOTATION> annotations)
078        {
079                this.extractor = extractor;
080                this.model = model;
081                this.annotations = annotations;
082        }
083
084        @Override
085        public void train(List<? extends Annotated<OBJECT, ANNOTATION>> data) {
086                final List<IndependentPair<FEATURE, ANNOTATION>> featureData = new ArrayList<IndependentPair<FEATURE, ANNOTATION>>();
087
088                for (final Annotated<OBJECT, ANNOTATION> a : data) {
089                        final FEATURE f = extractor.extractFeature(a.getObject());
090
091                        for (final ANNOTATION ann : a.getAnnotations())
092                                featureData.add(IndependentPair.pair(f, ann));
093                }
094
095                model.estimate(featureData);
096        }
097
098        @Override
099        public Set<ANNOTATION> getAnnotations() {
100                return annotations;
101        }
102
103        @Override
104        public List<ScoredAnnotation<ANNOTATION>> annotate(OBJECT object) {
105                final FEATURE f = extractor.extractFeature(object);
106
107                final List<ScoredAnnotation<ANNOTATION>> result = new ArrayList<ScoredAnnotation<ANNOTATION>>();
108                result.add(new ScoredAnnotation<ANNOTATION>(model.predict(f), 1));
109
110                return result;
111        }
112}