/**
 * 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
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package org.openimaj.image.processing.face.detection;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.io.OutputStream;
import java.util.ArrayList;
import java.util.List;

import org.openimaj.citation.annotation.Reference;
import org.openimaj.citation.annotation.ReferenceType;
import org.openimaj.image.FImage;
import org.openimaj.image.objectdetection.filtering.DetectionFilter;
import org.openimaj.image.objectdetection.filtering.OpenCVGrouping;
import org.openimaj.image.objectdetection.haar.Detector;
import org.openimaj.image.objectdetection.haar.OCVHaarLoader;
import org.openimaj.image.objectdetection.haar.StageTreeClassifier;
import org.openimaj.image.processing.algorithm.EqualisationProcessor;
import org.openimaj.io.IOUtils;
import org.openimaj.math.geometry.shape.Rectangle;
import org.openimaj.util.hash.HashCodeUtil;
import org.openimaj.util.pair.ObjectIntPair;

/**
 * A face detector based on a Haar cascade. The cascades provided by
 * {@link BuiltInCascade} are the same as those available in OpenCV.
 * 
 * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
 */
@Reference(
                type = ReferenceType.Inproceedings,
                author = { "Viola, P.", "Jones, M." },
                title = "Rapid object detection using a boosted cascade of simple features",
                year = "2001",
                booktitle = "Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on",
                pages = { " I", "511 ", " I", "518 vol.1" },
                number = "",
                volume = "1",
                customData = {
                                "keywords",
                                " AdaBoost; background regions; boosted simple feature cascade; classifiers; face detection; image processing; image representation; integral image; machine learning; object specific focus-of-attention mechanism; rapid object detection; real-time applications; statistical guarantees; visual object detection; feature extraction; image classification; image representation; learning (artificial intelligence); object detection;",
                                "doi", "10.1109/CVPR.2001.990517",
                                "ISSN", "1063-6919 "
                })
public class HaarCascadeDetector implements FaceDetector<DetectedFace, FImage> {
        /**
         * The set of pre-trained cascades from OpenCV.
         * 
         * @author Jonathon Hare (jsh2@ecs.soton.ac.uk)
         */
        public enum BuiltInCascade {
                /**
                 * A eye detector
                 */
                eye("haarcascade_eye.xml"),
                /**
                 * A eye with glasses detector
                 */
                eye_tree_eyeglasses("haarcascade_eye_tree_eyeglasses.xml"),
                /**
                 * A frontal face detector
                 */
                frontalface_alt("haarcascade_frontalface_alt.xml"),
                /**
                 * A frontal face detector
                 */
                frontalface_alt2("haarcascade_frontalface_alt2.xml"),
                /**
                 * A frontal face detector
                 */
                frontalface_alt_tree("haarcascade_frontalface_alt_tree.xml"),
                /**
                 * A frontal face detector
                 */
                frontalface_default("haarcascade_frontalface_default.xml"),
                /**
                 * A fullbody detector
                 */
                fullbody("haarcascade_fullbody.xml"),
                /**
                 * A left eye detector
                 */
                lefteye_2splits("haarcascade_lefteye_2splits.xml"),
                /**
                 * A lower body detector
                 */
                lowerbody("haarcascade_lowerbody.xml"),
                /**
                 * A detector for a pair of eyes
                 */
                mcs_eyepair_big("haarcascade_mcs_eyepair_big.xml"),
                /**
                 * A detector for a pair of eyes
                 */
                mcs_eyepair_small("haarcascade_mcs_eyepair_small.xml"),
                /**
                 * A left eye detector
                 */
                mcs_lefteye("haarcascade_mcs_lefteye.xml"),
                /**
                 * A mouth detector
                 */
                mcs_mouth("haarcascade_mcs_mouth.xml"),
                /**
                 * A nose detector
                 */
                mcs_nose("haarcascade_mcs_nose.xml"),
                /**
                 * A right eye detector
                 */
                mcs_righteye("haarcascade_mcs_righteye.xml"),
                /**
                 * An upper body detector
                 */
                mcs_upperbody("haarcascade_mcs_upperbody.xml"),
                /**
                 * A profile face detector
                 */
                profileface("haarcascade_profileface.xml"),
                /**
                 * A right eye detector
                 */
                righteye_2splits("haarcascade_righteye_2splits.xml"),
                /**
                 * An upper body detector
                 */
                upperbody("haarcascade_upperbody.xml");

                private String classFile;

                private BuiltInCascade(String classFile) {
                        this.classFile = classFile;
                }

                /**
                 * @return The name of the cascade resource
                 */
                public String classFile() {
                        return classFile;
                }

                /**
                 * Create a new detector with the this cascade.
                 * 
                 * @return A new {@link HaarCascadeDetector}
                 */
                public HaarCascadeDetector load() {
                        try {
                                return new HaarCascadeDetector(classFile);
                        } catch (final Exception e) {
                                throw new RuntimeException(e);
                        }
                }
        }

        protected Detector detector;
        protected DetectionFilter<Rectangle, ObjectIntPair<Rectangle>> groupingFilter;
        protected boolean histogramEqualize = false;

        /**
         * Construct with the given cascade resource. See
         * {@link #setCascade(String)} to understand how the cascade is loaded.
         * 
         * @param cas
         *            The cascade resource.
         * @see #setCascade(String)
         */
        public HaarCascadeDetector(String cas) {
                try {
                        setCascade(cas);
                } catch (final Exception e) {
                        throw new RuntimeException(e);
                }
                groupingFilter = new OpenCVGrouping();
        }

        /**
         * Construct with the {@link BuiltInCascade#frontalface_default} cascade.
         */
        public HaarCascadeDetector() {
                this(BuiltInCascade.frontalface_default.classFile());
        }

        /**
         * Construct with the {@link BuiltInCascade#frontalface_default} cascade and
         * the given minimum search window size.
         * 
         * @param minSize
         *            minimum search window size
         */
        public HaarCascadeDetector(int minSize) {
                this();
                this.detector.setMinimumDetectionSize(minSize);
        }

        /**
         * Construct with the given cascade resource and the given minimum search
         * window size. See {@link #setCascade(String)} to understand how the
         * cascade is loaded.
         * 
         * @param cas
         *            The cascade resource.
         * @param minSize
         *            minimum search window size.
         * 
         * @see #setCascade(String)
         */
        public HaarCascadeDetector(String cas, int minSize) {
                this(cas);
                this.detector.setMinimumDetectionSize(minSize);
        }

        /**
         * @return The minimum detection window size
         */
        public int getMinSize() {
                return this.detector.getMinimumDetectionSize();
        }

        /**
         * Set the minimum detection window size
         * 
         * @param size
         *            the window size
         */
        public void setMinSize(int size) {
                this.detector.setMinimumDetectionSize(size);
        }

        /**
         * @return The maximum detection window size
         */
        public int getMaxSize() {
                return this.detector.getMaximumDetectionSize();
        }

        /**
         * Set the maximum detection window size
         * 
         * @param size
         *            the window size
         */
        public void setMaxSize(int size) {
                this.detector.setMaximumDetectionSize(size);
        }

        /**
         * @return The grouping filter
         */
        public DetectionFilter<Rectangle, ObjectIntPair<Rectangle>> getGroupingFilter() {
                return groupingFilter;
        }

        /**
         * Set the filter for merging detections
         * 
         * @param grouping
         */
        public void setGroupingFilter(DetectionFilter<Rectangle, ObjectIntPair<Rectangle>> grouping) {
                this.groupingFilter = grouping;
        }

        @Override
        public List<DetectedFace> detectFaces(FImage image) {
                if (histogramEqualize)
                        image.processInplace(new EqualisationProcessor());

                final List<Rectangle> rects = detector.detect(image);
                final List<ObjectIntPair<Rectangle>> filteredRects = groupingFilter.apply(rects);

                final List<DetectedFace> results = new ArrayList<DetectedFace>();
                for (final ObjectIntPair<Rectangle> r : filteredRects) {
                        results.add(new DetectedFace(r.first, image.extractROI(r.first), r.second));
                }

                return results;
        }

        /**
         * @see Detector#getScaleFactor()
         * @return The detector scale factor
         */
        public double getScaleFactor() {
                return detector.getScaleFactor();
        }

        /**
         * Set the cascade classifier for this detector. The cascade file is first
         * searched for as a java resource, and if it is not found then a it is
         * assumed to be a file on the filesystem.
         * 
         * @param cascadeResource
         *            The cascade to load.
         * @throws Exception
         *             if there is a problem loading the cascade.
         */
        public void setCascade(String cascadeResource) throws Exception {
                // try to load serialized cascade from external XML file
                InputStream in = null;
                try {
                        in = OCVHaarLoader.class.getResourceAsStream(cascadeResource);

                        if (in == null) {
                                in = new FileInputStream(new File(cascadeResource));
                        }
                        final StageTreeClassifier cascade = OCVHaarLoader.read(in);

                        if (this.detector == null)
                                this.detector = new Detector(cascade);
                        else
                                this.detector = new Detector(cascade, this.detector.getScaleFactor());
                } catch (final Exception e) {
                        throw e;
                } finally {
                        if (in != null) {
                                try {
                                        in.close();
                                } catch (final IOException e) {
                                }
                        }
                }
        }

        /**
         * Set the detector scale factor
         * 
         * @see Detector#setScaleFactor(float)
         * 
         * @param scaleFactor
         *            the scale factor
         */
        public void setScale(float scaleFactor) {
                this.detector.setScaleFactor(scaleFactor);
        }

        /**
         * Serialize the detector using java serialization to the given stream
         * 
         * @param os
         *            the stream
         * @throws IOException
         */
        public void save(OutputStream os) throws IOException {
                final ObjectOutputStream oos = new ObjectOutputStream(os);
                oos.writeObject(this);
        }

        /**
         * Deserialize the detector from a stream. The detector must have been
         * written with a previous invokation of {@link #save(OutputStream)}.
         * 
         * @param is
         * @return {@link HaarCascadeDetector} read from stream.
         * @throws IOException
         * @throws ClassNotFoundException
         */
        public static HaarCascadeDetector read(InputStream is) throws IOException, ClassNotFoundException {
                final ObjectInputStream ois = new ObjectInputStream(is);
                return (HaarCascadeDetector) ois.readObject();
        }

        @Override
        public int hashCode() {
                int hashCode = HashCodeUtil.SEED;

                hashCode = HashCodeUtil.hash(hashCode, this.detector.getMinimumDetectionSize());
                hashCode = HashCodeUtil.hash(hashCode, this.detector.getScaleFactor());
                hashCode = HashCodeUtil.hash(hashCode, this.detector.getClassifier().getName());
                hashCode = HashCodeUtil.hash(hashCode, this.groupingFilter);
                hashCode = HashCodeUtil.hash(hashCode, this.histogramEqualize);

                return hashCode;
        }

        @Override
        public void readBinary(DataInput in) throws IOException {
                this.detector = IOUtils.read(in);
                this.groupingFilter = IOUtils.read(in);

                histogramEqualize = in.readBoolean();
        }

        @Override
        public byte[] binaryHeader() {
                return "HAAR".getBytes();
        }

        @Override
        public void writeBinary(DataOutput out) throws IOException {
                IOUtils.write(detector, out);
                IOUtils.write(groupingFilter, out);

                out.writeBoolean(histogramEqualize);
        }

        @Override
        public String toString() {
                return "HaarCascadeDetector[cascade=" + detector.getClassifier().getName() + "]";
        }

        /**
         * @return the underlying Haar cascade.
         */
        public StageTreeClassifier getCascade() {
                return detector.getClassifier();
        }

        /**
         * @return the underlying {@link Detector}.
         */
        public Detector getDetector() {
                return detector;
        }
}