/*
* This file is part of the LIRE project: http://lire-project.net
* 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: 03.08.13 09:07
*/
package net.semanticmetadata.lire.benchmarking;
import junit.framework.TestCase;
import net.semanticmetadata.lire.aggregators.AbstractAggregator;
import net.semanticmetadata.lire.aggregators.Aggregator;
import net.semanticmetadata.lire.aggregators.BOVW;
import net.semanticmetadata.lire.builders.DocumentBuilder;
import net.semanticmetadata.lire.imageanalysis.features.Extractor;
import net.semanticmetadata.lire.imageanalysis.features.GenericDoubleLireFeature;
import net.semanticmetadata.lire.imageanalysis.features.GlobalFeature;
import net.semanticmetadata.lire.imageanalysis.features.LocalFeatureExtractor;
import net.semanticmetadata.lire.imageanalysis.features.global.*;
import net.semanticmetadata.lire.imageanalysis.features.global.spatialpyramid.SPACC;
import net.semanticmetadata.lire.imageanalysis.features.global.spatialpyramid.SPCEDD;
import net.semanticmetadata.lire.imageanalysis.features.global.spatialpyramid.SPFCTH;
import net.semanticmetadata.lire.imageanalysis.features.global.spatialpyramid.SPJCD;
import net.semanticmetadata.lire.imageanalysis.features.local.opencvfeatures.CvSurfExtractor;
import net.semanticmetadata.lire.imageanalysis.features.local.simple.SimpleExtractor;
import net.semanticmetadata.lire.indexers.parallel.ParallelIndexer;
import net.semanticmetadata.lire.searchers.GenericFastImageSearcher;
import net.semanticmetadata.lire.searchers.ImageSearchHits;
import net.semanticmetadata.lire.searchers.ImageSearcher;
import net.semanticmetadata.lire.searchers.ImageSearcherUsingWSs;
import net.semanticmetadata.lire.utils.FileUtils;
import net.semanticmetadata.lire.utils.LuceneUtils;
import org.apache.lucene.document.Document;
import org.apache.lucene.index.DirectoryReader;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.index.MultiFields;
import org.apache.lucene.store.FSDirectory;
import org.apache.lucene.store.IOContext;
import org.apache.lucene.store.RAMDirectory;
import org.apache.lucene.util.Bits;
import javax.imageio.ImageIO;
import java.io.*;
import java.nio.file.Paths;
import java.util.*;
/**
* Created by Nektarios on 30/10/2014.
*
* @author Mathias Lux, mathias@juggle.at
* @author Nektarios Anagnostopoulos, nek.anag@gmail.com
*/
public class TestUniversal extends TestCase {
//UCID
private String db = "UCID";
private String indexPath = "ucid-index";
private String testExtensive = "testdata/UCID_png";
private final String groundTruth = "testdata/queries/ucid.v2.groundtruth.txt";
//UKBench
// private String db = "UKB";
// private String indexPath = "ukbench-index";
// private String testExtensive = "testdata/ukbench";
// private final String groundTruth = "testdata/queries/NisterQueries.txt";
//Wang
// private String db = "Wang";
// private String indexPath = "wang-index";
// private String testExtensive = "testdata/wang";
// private final String groundTruth = "testdata/queries/WangQueries.txt";
//Holidays
// private String db = "Hol";
// private String indexPath = "holidays-index";
// private String testExtensive = "testdata/holidays";
// private final String groundTruth = "testdata/queries/HolidaysQueries.txt";
private int numOfDocsForVocabulary = 500;
private Class<? extends AbstractAggregator> aggregator = BOVW.class;
private int[] numOfClusters = new int[] {32, 128, 512, 2048};
// private Class<? extends AbstractAggregator> aggregator = VLAD.class;
// private int[] numOfClusters = new int[] {16, 64};
private HashMap<String, List<String>> queries;
private HashMap<String, Integer> query2id;
protected void setUp() throws Exception {
super.setUp();
indexPath += "-" + System.currentTimeMillis() % (1000 * 60 * 60 * 24 * 7);
// Getting the queries:
BufferedReader br = new BufferedReader(new FileReader(groundTruth));
String line;
queries = new HashMap<String, List<String>>(260);
query2id = new HashMap<String, Integer>(260);
int qID = 1;
String currentQuery = null;
LinkedList<String> results = null;
while ((line = br.readLine()) != null) {
line = line.trim();
if (line.startsWith("#") || line.length() < 4)
continue;
else {
if (line.endsWith(":")) {
if (currentQuery != null) {
queries.put(currentQuery, results);
query2id.put(currentQuery, qID);
qID++;
}
currentQuery = line.replace(':', ' ').trim();
results = new LinkedList<String>();
} else {
results.add(line);
}
}
}
queries.put(currentQuery, results);
query2id.put(currentQuery, qID);
}
public void testMAP() throws IOException {
// INDEXING ...
ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive, numOfClusters, numOfDocsForVocabulary, aggregator);
// ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive, false);
// ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive);
//GLOBALS
parallelIndexer.addExtractor(ACCID.class);
parallelIndexer.addExtractor(CEDD.class);
parallelIndexer.addExtractor(COMO.class);
// parallelIndexer.addExtractor(FCTH.class);
// parallelIndexer.addExtractor(JCD.class);
parallelIndexer.addExtractor(AutoColorCorrelogram.class);
// parallelIndexer.addExtractor(BinaryPatternsPyramid.class);
// parallelIndexer.addExtractor(FuzzyColorHistogram.class);
// parallelIndexer.addExtractor(FuzzyOpponentHistogram.class);
// parallelIndexer.addExtractor(Gabor.class);
// parallelIndexer.addExtractor(JpegCoefficientHistogram.class);
// parallelIndexer.addExtractor(LocalBinaryPatterns.class);
// parallelIndexer.addExtractor(LuminanceLayout.class);
parallelIndexer.addExtractor(OpponentHistogram.class);
parallelIndexer.addExtractor(PHOG.class);
// parallelIndexer.addExtractor(RotationInvariantLocalBinaryPatterns.class);
// parallelIndexer.addExtractor(SimpleColorHistogram.class);
// parallelIndexer.addExtractor(Tamura.class);
// parallelIndexer.addExtractor(JointHistogram.class);
// parallelIndexer.addExtractor(LocalBinaryPatternsAndOpponent.class);
// parallelIndexer.addExtractor(RankAndOpponent.class);
parallelIndexer.addExtractor(ColorLayout.class);
// parallelIndexer.addExtractor(EdgeHistogram.class);
parallelIndexer.addExtractor(ScalableColor.class);
// parallelIndexer.addExtractor(SPCEDD.class);
// parallelIndexer.addExtractor(SPJCD.class);
// parallelIndexer.addExtractor(SPFCTH.class);
// parallelIndexer.addExtractor(SPACC.class);
// parallelIndexer.addExtractor(SPLBP.class);
//SIMPLE
// parallelIndexer.addExtractor(CEDD.class, SimpleExtractor.KeypointDetector.CVSURF);
// parallelIndexer.addExtractor(FCTH.class, SimpleExtractor.KeypointDetector.CVSURF);
// parallelIndexer.addExtractor(JCD.class, SimpleExtractor.KeypointDetector.CVSURF);
// parallelIndexer.addExtractor(AutoColorCorrelogram.class, SimpleExtractor.KeypointDetector.CVSURF);
// parallelIndexer.addExtractor(OpponentHistogram.class, SimpleExtractor.KeypointDetector.CVSURF);
// parallelIndexer.addExtractor(ColorLayout.class, SimpleExtractor.KeypointDetector.CVSURF);
// parallelIndexer.addExtractor(EdgeHistogram.class, SimpleExtractor.KeypointDetector.CVSURF);
// parallelIndexer.addExtractor(ScalableColor.class, SimpleExtractor.KeypointDetector.CVSURF);
//LOCAL
// parallelIndexer.addExtractor(CvSurfExtractor.class);
// parallelIndexer.addExtractor(CvSiftExtractor.class);
// parallelIndexer.addExtractor(SurfExtractor.class);
// parallelIndexer.addExtractor(SiftExtractor.class);
// parallelIndexer.addExtractor(SelfSimilaritiesExtractor.class);
parallelIndexer.run();
// READ FROM FILE:
// IndexWriter iw = LuceneUtils.createIndexWriter("tmpfeature", true);
// int i1 = LuceneUtils.writeFeaturesToIndex(new FileInputStream("eval/res_32.txt"), iw);
// System.out.println("# of features indexed = " + i1);
// IndexReader r2 = DirectoryReader.open(new RAMDirectory(FSDirectory.open(Paths.get("tmpfeature")), IOContext.READONCE));
// SEARCHING
IndexReader reader = DirectoryReader.open(new RAMDirectory(FSDirectory.open(Paths.get(indexPath)), IOContext.READONCE));
// IndexReader reader = DirectoryReader.open(FSDirectory.open(new File(indexPath)));
System.out.println("Documents in the reader: " + reader.maxDoc());
//
System.out.println("Feature\tMAP\tp@10\tER");
//
long start = System.currentTimeMillis();
//
computeMAP(new GenericFastImageSearcher(1000, ACCID.class, true, reader), "ACCID", reader);
computeMAP(new GenericFastImageSearcher(1000, CEDD.class, true, reader), "CEDD", reader);
// computeMAP(new GenericFastImageSearcher(1000, GenericGlobalDoubleFeature.class, true, r2), "RES_4", r2); // -----> READ FROM FILE
computeMAP(new GenericFastImageSearcher(1000, COMO.class, true, reader), "COMO", reader);
// computeMAP(new GenericFastImageSearcher(1000, FCTH.class, true, reader), "FCTH", reader);
// computeMAP(new GenericFastImageSearcher(1000, JCD.class, true, reader), "JCD", reader);
computeMAP(new GenericFastImageSearcher(1000, AutoColorCorrelogram.class, true, reader), "AutoColorCorrelogram", reader);
// computeMAP(new GenericFastImageSearcher(1000, BinaryPatternsPyramid.class, true, reader), "BinaryPatternsPyramid", reader);
// computeMAP(new GenericFastImageSearcher(1000, FuzzyColorHistogram.class, true, reader), "FuzzyColorHistogram", reader);
// computeMAP(new GenericFastImageSearcher(1000, FuzzyOpponentHistogram.class, true, reader), "FuzzyOpponentHistogram", reader);
// computeMAP(new GenericFastImageSearcher(1000, Gabor.class, true, reader), "Gabor", reader);
// computeMAP(new GenericFastImageSearcher(1000, JpegCoefficientHistogram.class, true, reader), "JpegCoefficientHistogram", reader);
// computeMAP(new GenericFastImageSearcher(1000, LocalBinaryPatterns.class, true, reader), "LocalBinaryPatterns", reader);
// computeMAP(new GenericFastImageSearcher(1000, LuminanceLayout.class, true, reader), "LuminanceLayout", reader);
computeMAP(new GenericFastImageSearcher(1000, OpponentHistogram.class, true, reader), "OpponentHistogram", reader);
computeMAP(new GenericFastImageSearcher(1000, PHOG.class, true, reader), "PHOG", reader);
// computeMAP(new GenericFastImageSearcher(1000, RotationInvariantLocalBinaryPatterns.class, true, reader), "RotationInvariantLocalBinaryPatterns", reader);
// computeMAP(new GenericFastImageSearcher(1000, SimpleColorHistogram.class, true, reader), "SimpleColorHistogram", reader);
// computeMAP(new GenericFastImageSearcher(1000, Tamura.class, true, reader), "Tamura", reader);
// computeMAP(new GenericFastImageSearcher(1000, JointHistogram.class, true, reader), "JointHistogram", reader);
// computeMAP(new GenericFastImageSearcher(1000, LocalBinaryPatternsAndOpponent.class, true, reader), "LocalBinaryPatternsAndOpponent", reader);
// computeMAP(new GenericFastImageSearcher(1000, RankAndOpponent.class, true, reader), "RankAndOpponent", reader);
computeMAP(new GenericFastImageSearcher(1000, ColorLayout.class, true, reader), "ColorLayout", reader);
// computeMAP(new GenericFastImageSearcher(1000, EdgeHistogram.class, true, reader), "EdgeHistogram", reader);
computeMAP(new GenericFastImageSearcher(1000, ScalableColor.class, true, reader), "ScalableColor", reader);
// computeMAP(new GenericFastImageSearcher(1000, SPCEDD.class, true, reader), "SPCEDD", reader);
// computeMAP(new GenericFastImageSearcher(1000, SPJCD.class, true, reader), "SPJCD", reader);
// computeMAP(new GenericFastImageSearcher(1000, SPFCTH.class, true, reader), "SPFCTH", reader);
// computeMAP(new GenericFastImageSearcher(1000, SPACC.class, true, reader), "SPACC", reader);
// computeMAP(new GenericFastImageSearcher(1000, SPLBP.class, true, reader), "SPLBP", reader);
//BOVW
for (int i = 0; i < numOfClusters.length; i++) {
// computeMAP(new GenericFastImageSearcher(1000, CEDD.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple BOVW CEDD CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, FCTH.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple BOVW FCTH CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, JCD.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple BOVW JCD CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, AutoColorCorrelogram.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple BOVW AutoColorCorrelogram CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, OpponentHistogram.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple BOVW OpponentHistogram CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, ColorLayout.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple BOVW ColorLayout CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, EdgeHistogram.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple BOVW EdgeHistogram CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, ScalableColor.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple BOVW ScalableColor CVSURF", reader, numOfClusters[i]);
// performWSs(CEDD.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "Simple BOVW CEDD CVSURF");
// performWSs(FCTH.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "Simple BOVW FCTH CVSURF");
// performWSs(JCD.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "Simple BOVW JCD CVSURF");
// performWSs(AutoColorCorrelogram.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "Simple BOVW AutoColorCorrelogram CVSURF");
// performWSs(OpponentHistogram.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "Simple BOVW OpponentHistogram CVSURF");
// performWSs(ColorLayout.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "Simple BOVW ColorLayout CVSURF");
// performWSs(EdgeHistogram.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "Simple BOVW EdgeHistogram CVSURF");
// performWSs(ScalableColor.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "Simple BOVW ScalableColor CVSURF");
// computeMAP(new GenericFastImageSearcher(1000, CvSurfExtractor.class, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "CVSURF BOVW", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, CvSiftExtractor.class, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "CVSIFT BOVW", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, SurfExtractor.class, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "SURF BOVW", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, SiftExtractor.class, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "SIFT BOVW", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, SelfSimilaritiesExtractor.class, new BOVW(), numOfClusters[i], true, reader, indexPath + ".config"), "SelfSimilarities BOVW", reader, numOfClusters[i]);
// performWSs(CvSurfExtractor.class, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "CVSURF BOVW");
// performWSs(CvSiftExtractor.class, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "CVSIFT BOVW");
// performWSs(SurfExtractor.class, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "SURF BOVW");
// performWSs(SiftExtractor.class, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "SIFT BOVW");
// performWSs(SelfSimilaritiesExtractor.class, new BOVW(), numOfClusters[i], reader, indexPath + ".config", "SelfSimilarities BOVW");
}
//VLAD
// for (int i = 0; i < numOfClusters.length; i++) {
// computeMAP(new GenericFastImageSearcher(1000, CEDD.class, SimpleExtractor.KeypointDetector.CVSURF, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple VLAD CEDD CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, FCTH.class, SimpleExtractor.KeypointDetector.CVSURF, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple VLAD FCTH CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, JCD.class, SimpleExtractor.KeypointDetector.CVSURF, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple VLAD JCD CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, AutoColorCorrelogram.class, SimpleExtractor.KeypointDetector.CVSURF, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple VLAD AutoColorCorrelogram CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, OpponentHistogram.class, SimpleExtractor.KeypointDetector.CVSURF, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple VLAD OpponentHistogram CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, ColorLayout.class, SimpleExtractor.KeypointDetector.CVSURF, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple VLAD ColorLayout CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, EdgeHistogram.class, SimpleExtractor.KeypointDetector.CVSURF, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple VLAD EdgeHistogram CVSURF", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, ScalableColor.class, SimpleExtractor.KeypointDetector.CVSURF, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "Simple VLAD ScalableColor CVSURF", reader, numOfClusters[i]);
////
// computeMAP(new GenericFastImageSearcher(1000, CvSurfExtractor.class, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "CVSURF VLAD", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, CvSiftExtractor.class, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "CVSIFT VLAD", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, SurfExtractor.class, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "SURF VLAD", reader, numOfClusters[i]);
// computeMAP(new GenericFastImageSearcher(1000, SiftExtractor.class, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "SIFT VLAD", reader, numOfClusters[i]);
//// computeMAP(new GenericFastImageSearcher(1000, SelfSimilaritiesExtractor.class, new VLAD(), numOfClusters[i], true, reader, indexPath + ".config"), "SelfSimilarities VLAD", reader, numOfClusters[i]);
// }
double h = (System.currentTimeMillis() - start) / 3600000.0;
double m = (h - Math.floor(h)) * 60.0;
double s = (m - Math.floor(m)) * 60;
System.out.printf("Total time of searching: %s.\n", String.format("%s%02d:%02d", (((int)h > 0)? String.format("%02d:", (int) h) : ""), (int)m, (int)s));
}
public void performWSs (Class<? extends GlobalFeature> globalFeature, SimpleExtractor.KeypointDetector detector, Aggregator aggregator, int codebookSize, IndexReader reader, String codebooksDir, String prefix) throws IOException
{
computeMAP(new ImageSearcherUsingWSs(1000, globalFeature, detector, aggregator, codebookSize, reader, codebooksDir, false, false, false), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, globalFeature, detector, aggregator, codebookSize, reader, codebooksDir, false, false, true), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, globalFeature, detector, aggregator, codebookSize, reader, codebooksDir, false, true, false), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, globalFeature, detector, aggregator, codebookSize, reader, codebooksDir, false, true, true), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, globalFeature, detector, aggregator, codebookSize, reader, codebooksDir, true, false, false), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, globalFeature, detector, aggregator, codebookSize, reader, codebooksDir, true, false, true), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, globalFeature, detector, aggregator, codebookSize, reader, codebooksDir, true, true, false), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, globalFeature, detector, aggregator, codebookSize, reader, codebooksDir, true, true, true), prefix, reader, codebookSize);
}
public void performWSs (Class<? extends LocalFeatureExtractor> localFeatureExtractor, Aggregator aggregator, int codebookSize, IndexReader reader, String codebooksDir, String prefix) throws IOException
{
computeMAP(new ImageSearcherUsingWSs(1000, localFeatureExtractor, aggregator, codebookSize, reader, codebooksDir, false, false, false), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, localFeatureExtractor, aggregator, codebookSize, reader, codebooksDir, false, false, true), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, localFeatureExtractor, aggregator, codebookSize, reader, codebooksDir, false, true, false), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, localFeatureExtractor, aggregator, codebookSize, reader, codebooksDir, false, true, true), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, localFeatureExtractor, aggregator, codebookSize, reader, codebooksDir, true, false, false), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, localFeatureExtractor, aggregator, codebookSize, reader, codebooksDir, true, false, true), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, localFeatureExtractor, aggregator, codebookSize, reader, codebooksDir, true, true, false), prefix, reader, codebookSize);
computeMAP(new ImageSearcherUsingWSs(1000, localFeatureExtractor, aggregator, codebookSize, reader, codebooksDir, true, true, true), prefix, reader, codebookSize);
}
private void computeMAP(GenericFastImageSearcher genericFastImageSearcher, String prefix, IndexReader reader) throws IOException {
computeMAP(genericFastImageSearcher, prefix, reader, 0);
}
private void computeMAP(ImageSearcher searcher, String prefix, IndexReader reader, int clusters) throws IOException {
long start = System.currentTimeMillis();
long timeOfSearch = 0, ms;
double queryCount = 0d;
double errorRate = 0;
double map = 0;
double p10 = 0;
int errorCount=0;
// Needed for check whether the document is deleted.
Bits liveDocs = MultiFields.getLiveDocs(reader);
PrintWriter fw;
if (searcher.toString().contains("ImageSearcherUsingWSs")) {
(new File("eval/" + db + "/" + prefix.replace(' ', '_') + "/" + clusters + "/")).mkdirs();
fw = new PrintWriter(new File("eval/" + db + "/" + prefix.replace(' ', '_') + "/" + clusters + "/" + prefix.replace(' ', '_') + "-" + db + clusters + searcher.toString().split("\\s+")[searcher.toString().split("\\s+").length - 1] + ".txt"));
}else {
// (new File("eval/#WithMirFlickr/" + db + "/")).mkdirs();
(new File("eval/" + db + "/")).mkdirs();
if (clusters>0)
fw = new PrintWriter(new File("eval/" + db + "/" + prefix.replace(' ', '_') + "-" + db + clusters +".txt"));
else
// fw = new PrintWriter(new File("eval/#WithMirFlickr/" + db + "/" + prefix.replace(' ', '_') + "-" + db + "Global.txt")); //forGlobal
fw = new PrintWriter(new File("eval/" + db + "/" + prefix.replace(' ', '_') + "-" + db + "Global.txt")); //forGlobal
}
Hashtable<Integer, String> evalText = new Hashtable<Integer, String>(260);
for (int i = 0; i < reader.maxDoc(); i++) {
if (reader.hasDeletions() && !liveDocs.get(i)) continue; // if it is deleted, just ignore it.
String fileName = getIDfromFileName(reader.document(i).getValues(DocumentBuilder.FIELD_NAME_IDENTIFIER)[0]);
if (queries.keySet().contains(fileName)) {
String tmpEval = "";
queryCount += 1d;
// ok, we've got a query here for a document ...
Document queryDoc = reader.document(i);
ms = System.currentTimeMillis();
ImageSearchHits hits = searcher.search(queryDoc, reader);
timeOfSearch += System.currentTimeMillis() - ms;
double rank = 0;
double avgPrecision = 0;
double found = 0;
double tmpP10 = 0;
Locale.setDefault(Locale.US);
for (int y = 0; y < hits.length(); y++) {
// String hitFile = getIDfromFileName(hits.doc(y).getValues(DocumentBuilder.FIELD_NAME_IDENTIFIER)[0]);
String hitFile = getIDfromFileName(reader.document(hits.documentID(y)).getValues(DocumentBuilder.FIELD_NAME_IDENTIFIER)[0]);
// String hitFile = getIDfromFileName(hits.path(y));
// TODO: Sort by query ID!
tmpEval += String.format(Locale.US, "%d 1 %s %d %.2f test\n", query2id.get(fileName), hitFile.substring(0, hitFile.lastIndexOf('.')), (int) rank + 1, hits.score(y));
// if (!hitFile.equals(fileName)) {
rank++;
// if ((queries.get(fileName).contains(hitFile) || hitFile.equals(fileName))&&(!fileName.equals(hitFile))) { // it's a hit.
if (queries.get(fileName).contains(hitFile) || hitFile.equals(fileName)) { // it's a hit.
found++;
// TODO: Compute error rate, etc. here.
avgPrecision += found / rank;// * (1d/queries.get(fileName).size());
// avgPrecision += found / (rank-1);// * (1d/queries.get(fileName).size());
// if (rank<=60) System.out.print('X');
if (rank <= 10) tmpP10++;
} else { // nothing has been found.
if (rank == 1) errorRate += 1d;
// if (rank<=60) System.out.print('-');
}
}
// }
// System.out.println();
avgPrecision /= (double) (1d + queries.get(fileName).size());
// avgPrecision /= (double) (queries.get(fileName).size());
if (!(found - queries.get(fileName).size() == 1)){
// some of the results have not been found. We have to deal with it ...
errorCount++;
}
// assertTrue(found - queries.get(fileName).size() == 0);
map += avgPrecision;
p10 += tmpP10;
evalText.put(query2id.get(fileName), tmpEval);
}
}
for (int i = 0; i < query2id.size(); i++) {
fw.write(evalText.get(i + 1));
}
fw.close();
errorRate = errorRate / queryCount;
map = map / queryCount;
p10 = p10 / (queryCount * 10d);
double h = (System.currentTimeMillis() - start) / 3600000.0;
double m = (h - Math.floor(h)) * 60.0;
double s = (m - Math.floor(m)) * 60;
String str = String.format("%s%02d:%02d", (((int)h > 0)? String.format("%02d:", (int) h) : ""), (int)m, (int)s) + " ~ ";
if (searcher.toString().contains("ImageSearcherUsingWSs"))
str += String.format("%s%s\t%.4f\t%.4f\t%.4f\t(%s)", prefix, ((clusters>0)? ("\t"+clusters):"") , map, p10, errorRate, searcher.toString().split("\\s+")[searcher.toString().split("\\s+").length-1]);
else
str += String.format("%s%s\t%.4f\t%.4f\t%.4f", prefix, ((clusters>0)? ("\t"+clusters):""), map, p10, errorRate);
if (errorCount>0) {
// some of the results have not been found. We have to deal with it ...
str += "\t~~\tDid not find result ;(\t(" + errorCount + ")";
}
h = timeOfSearch / 3600000.0;
m = (h - Math.floor(h)) * 60.0;
s = (m - Math.floor(m)) * 60;
str += " ~ TimeOfsearch: " + String.format("%s%02d:%02d", (((int)h > 0)? String.format("%02d:", (int) h) : ""), (int)m, (int)s);
System.out.println(str);
}
private String getIDfromFileName(String path) {
// That's the one for Windows. Change for Linux ...
return path.substring(path.lastIndexOf('\\') + 1);
}
public void testIndexingSpeed() throws IOException {
ArrayList<String> images = FileUtils.getAllImages(new File(testExtensive), false);
testFeatureSpeed(images, AutoColorCorrelogram.class);
testFeatureSpeed(images, CEDD.class);
testFeatureSpeed(images, FCTH.class);
testFeatureSpeed(images, JCD.class);
testFeatureSpeed(images, SPACC.class);
testFeatureSpeed(images, SPCEDD.class);
testFeatureSpeed(images, SPFCTH.class);
testFeatureSpeed(images, SPJCD.class);
}
public void testSearchSpeed() throws IOException {
testSearchSpeed(AutoColorCorrelogram.class);
testSearchSpeed(CEDD.class);
testSearchSpeed(FCTH.class);
testSearchSpeed(JCD.class);
testSearchSpeed(SPACC.class);
testSearchSpeed(SPCEDD.class);
testSearchSpeed(SPFCTH.class);
testSearchSpeed(SPJCD.class);
}
private void testSearchSpeed(Class<? extends GlobalFeature> featureClass) throws IOException {
ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive, true);
parallelIndexer.addExtractor(featureClass);
parallelIndexer.run();
IndexReader reader = DirectoryReader.open(new RAMDirectory(FSDirectory.open(Paths.get(indexPath)), IOContext.READONCE));
Bits liveDocs = MultiFields.getLiveDocs(reader);
double queryCount = 0d;
ImageSearcher searcher = new GenericFastImageSearcher(100, featureClass);
long ms = System.currentTimeMillis();
String fileName;
Document queryDoc;
ImageSearchHits hits;
for (int i = 0; i < reader.maxDoc(); i++) {
if (reader.hasDeletions() && !liveDocs.get(i)) continue; // if it is deleted, just ignore it.
fileName = getIDfromFileName(reader.document(i).getValues(DocumentBuilder.FIELD_NAME_IDENTIFIER)[0]);
if (queries.keySet().contains(fileName)) {
queryCount += 1d;
// ok, we've got a query here for a document ...
queryDoc = reader.document(i);
hits = searcher.search(queryDoc, reader);
}
}
ms = System.currentTimeMillis() - ms;
System.out.printf("%s \t %3.1f \n", featureClass.getName().substring(featureClass.getName().lastIndexOf('.') + 1), (double) ms / queryCount);
}
private void testFeatureSpeed(ArrayList<String> images, Class<? extends Extractor> extractorClass) throws IOException {
Extractor extractor;
long ms;
try {
extractor = extractorClass.newInstance();
ms = System.currentTimeMillis();
for (String s : images) {
extractor.extract(ImageIO.read(new File(s)));
}
ms = System.currentTimeMillis() - ms;
System.out.printf("%s \t %3.1f \n", extractor.getClass().getName().substring(extractor.getClass().getName().lastIndexOf('.') + 1), (double) ms / (double) images.size());
} catch (InstantiationException e) {
e.printStackTrace();
} catch (IllegalAccessException e) {
e.printStackTrace();
}
}
}