/*
* This file is part of the LIRE project: http://www.semanticmetadata.net/lire
* LIRE is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
* LIRE is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with LIRE; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*
* We kindly ask you to refer the any or one of the following publications in
* any publication mentioning or employing Lire:
*
* Lux Mathias, Savvas A. Chatzichristofis. Lire: Lucene Image Retrieval –
* An Extensible Java CBIR Library. In proceedings of the 16th ACM International
* Conference on Multimedia, pp. 1085-1088, Vancouver, Canada, 2008
* URL: http://doi.acm.org/10.1145/1459359.1459577
*
* Lux Mathias. Content Based Image Retrieval with LIRE. In proceedings of the
* 19th ACM International Conference on Multimedia, pp. 735-738, Scottsdale,
* Arizona, USA, 2011
* URL: http://dl.acm.org/citation.cfm?id=2072432
*
* Mathias Lux, Oge Marques. Visual Information Retrieval using Java and LIRE
* Morgan & Claypool, 2013
* URL: http://www.morganclaypool.com/doi/abs/10.2200/S00468ED1V01Y201301ICR025
*
* Copyright statement:
* ====================
* (c) 2002-2013 by Mathias Lux (mathias@juggle.at)
* http://www.semanticmetadata.net/lire, http://www.lire-project.net
*
* Updated: 11.07.13 10:51
*/
package net.semanticmetadata.lire.impl;
import net.semanticmetadata.lire.AbstractImageSearcher;
import net.semanticmetadata.lire.DocumentBuilder;
import net.semanticmetadata.lire.ImageDuplicates;
import net.semanticmetadata.lire.ImageSearchHits;
import net.semanticmetadata.lire.imageanalysis.LireFeature;
import net.semanticmetadata.lire.utils.ImageUtils;
import org.apache.lucene.document.Document;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.MultiFields;
import org.apache.lucene.util.Bits;
import java.awt.image.BufferedImage;
import java.io.IOException;
import java.util.HashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.TreeSet;
import java.util.logging.Level;
import java.util.logging.Logger;
/**
* This file is part of the Caliph and Emir project: http://www.SemanticMetadata.net
* <br>Date: 01.02.2006
* <br>Time: 00:17:02
*
* @author Mathias Lux, mathias@juggle.at
* @deprecated
*/
public class GenericImageSearcher extends AbstractImageSearcher {
protected Logger logger = Logger.getLogger(getClass().getName());
Class<?> descriptorClass;
String fieldName;
private int maxHits = 10;
protected TreeSet<SimpleResult> docs;
private LireFeature cachedInstance;
public GenericImageSearcher(int maxHits, Class<?> descriptorClass, String fieldName) {
this.maxHits = maxHits;
docs = new TreeSet<SimpleResult>();
this.descriptorClass = descriptorClass;
this.fieldName = fieldName;
try {
cachedInstance = (LireFeature) descriptorClass.newInstance();
} catch (InstantiationException e) {
e.printStackTrace();
} catch (IllegalAccessException e) {
e.printStackTrace();
}
}
public ImageSearchHits search(BufferedImage image, IndexReader reader) throws IOException {
logger.finer("Starting extraction.");
LireFeature lireFeature = null;
SimpleImageSearchHits searchHits = null;
try {
lireFeature = (LireFeature) descriptorClass.newInstance();
// Scaling image is especially with the correlogram features very important!
BufferedImage bimg = image;
if (Math.max(image.getHeight(), image.getWidth()) > GenericDocumentBuilder.MAX_IMAGE_DIMENSION) {
bimg = ImageUtils.scaleImage(image, GenericDocumentBuilder.MAX_IMAGE_DIMENSION);
}
lireFeature.extract(bimg);
logger.fine("Extraction from image finished");
float maxDistance = findSimilar(reader, lireFeature);
searchHits = new SimpleImageSearchHits(this.docs, maxDistance);
} catch (InstantiationException e) {
logger.log(Level.SEVERE, "Error instantiating class for generic image searcher: " + e.getMessage());
} catch (IllegalAccessException e) {
logger.log(Level.SEVERE, "Error instantiating class for generic image searcher: " + e.getMessage());
}
return searchHits;
}
/**
* @param reader
* @param lireFeature
* @return the maximum distance found for normalizing.
* @throws java.io.IOException
*/
protected float findSimilar(IndexReader reader, LireFeature lireFeature) throws IOException {
float maxDistance = -1f, overallMaxDistance = -1f;
float tmpDistance = 0f;
// clear result set ...
docs.clear();
// Needed for check whether the document is deleted.
Bits liveDocs = MultiFields.getLiveDocs(reader);
int docs = reader.numDocs();
Document d = null;
for (int i = 0; i < docs; i++) {
if (reader.hasDeletions() && !liveDocs.get(i)) continue; // if it is deleted, just ignore it.
d = reader.document(i);
tmpDistance = getDistance(d, lireFeature);
// if (distance < 0 || Float.isNaN(distance))
// System.out.println("X");
assert (tmpDistance >= 0);
// calculate the overall max distance to normalize score afterwards
if (overallMaxDistance < tmpDistance) {
overallMaxDistance = tmpDistance;
}
// if it is the first document:
if (maxDistance < 0) {
maxDistance = tmpDistance;
}
// if the array is not full yet:
if (this.docs.size() < maxHits) {
this.docs.add(new SimpleResult(tmpDistance, d, i));
if (tmpDistance > maxDistance) maxDistance = tmpDistance;
} else if (tmpDistance < maxDistance) {
// if it is nearer to the sample than at least on of the current set:
// remove the last one ...
this.docs.remove(this.docs.last());
// add the new one ...
this.docs.add(new SimpleResult(tmpDistance, d, i));
// and set our new distance border ...
maxDistance = this.docs.last().getDistance();
}
}
return maxDistance;
}
protected float getDistance(Document d, LireFeature lireFeature) {
float distance = 0f;
// cachedInstance = (LireFeature) descriptorClass.newInstance();
String[] cls = d.getValues(fieldName);
if (cls != null && cls.length > 0) {
cachedInstance.setStringRepresentation(cls[0]);
distance = lireFeature.getDistance(cachedInstance);
} else {
logger.warning("No feature stored in this document!");
}
return distance;
}
public ImageSearchHits search(Document doc, IndexReader reader) throws IOException {
SimpleImageSearchHits searchHits = null;
try {
LireFeature lireFeature = (LireFeature) descriptorClass.newInstance();
String[] cls = doc.getValues(fieldName);
if (cls != null && cls.length > 0)
lireFeature.setStringRepresentation(cls[0]);
float maxDistance = findSimilar(reader, lireFeature);
searchHits = new SimpleImageSearchHits(this.docs, maxDistance);
} catch (InstantiationException e) {
logger.log(Level.SEVERE, "Error instantiating class for generic image searcher: " + e.getMessage());
} catch (IllegalAccessException e) {
logger.log(Level.SEVERE, "Error instantiating class for generic image searcher: " + e.getMessage());
}
return searchHits;
}
public ImageDuplicates findDuplicates(IndexReader reader) throws IOException {
// get the first document:
SimpleImageDuplicates simpleImageDuplicates = null;
try {
// if (!IndexReader.indexExists(reader.directory()))
// throw new FileNotFoundException("No index found at this specific location.");
Document doc = reader.document(0);
LireFeature lireFeature = (LireFeature) descriptorClass.newInstance();
String[] cls = doc.getValues(fieldName);
if (cls != null && cls.length > 0)
lireFeature.setStringRepresentation(cls[0]);
HashMap<Float, List<String>> duplicates = new HashMap<Float, List<String>>();
// Needed for check whether the document is deleted.
Bits liveDocs = MultiFields.getLiveDocs(reader);
int docs = reader.numDocs();
int numDuplicates = 0;
for (int i = 0; i < docs; i++) {
if (reader.hasDeletions() && !liveDocs.get(i)) continue; // if it is deleted, just ignore it.
Document d = reader.document(i);
float distance = getDistance(d, lireFeature);
if (!duplicates.containsKey(distance)) {
duplicates.put(distance, new LinkedList<String>());
} else {
numDuplicates++;
}
duplicates.get(distance).add(d.getField(DocumentBuilder.FIELD_NAME_IDENTIFIER).stringValue());
}
if (numDuplicates == 0) return null;
LinkedList<List<String>> results = new LinkedList<List<String>>();
for (float f : duplicates.keySet()) {
if (duplicates.get(f).size() > 1) {
results.add(duplicates.get(f));
}
}
simpleImageDuplicates = new SimpleImageDuplicates(results);
} catch (InstantiationException e) {
logger.log(Level.SEVERE, "Error instantiating class for generic image searcher: " + e.getMessage());
} catch (IllegalAccessException e) {
logger.log(Level.SEVERE, "Error instantiating class for generic image searcher: " + e.getMessage());
}
return simpleImageDuplicates;
}
public String toString() {
return "GenericSearcher using " + descriptorClass.getName();
}
}