/*
* 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
*/
package net.semanticmetadata.lire.indexers;
import junit.framework.TestCase;
import net.semanticmetadata.lire.aggregators.AbstractAggregator;
import net.semanticmetadata.lire.aggregators.BOVW;
import net.semanticmetadata.lire.builders.DocumentBuilder;
import net.semanticmetadata.lire.classifiers.Cluster;
import net.semanticmetadata.lire.imageanalysis.features.GlobalFeature;
import net.semanticmetadata.lire.imageanalysis.features.LocalFeatureExtractor;
import net.semanticmetadata.lire.imageanalysis.features.global.CEDD;
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 java.io.IOException;
import java.util.LinkedList;
/**
* Created by Nektarios on 28/5/2015.
*
* @author Nektarios Anagnostopoulos, nek.anag@gmail.com
* (c) 2015 by Nektarios Anagnostopoulos
*/
public class TestIndexing extends TestCase {
Class<? extends GlobalFeature> globalFeatureClass = CEDD.class;
Class<? extends LocalFeatureExtractor> localFeatureClass = CvSurfExtractor.class;
SimpleExtractor.KeypointDetector keypointDetector = SimpleExtractor.KeypointDetector.CVSURF;
Class<? extends AbstractAggregator> aggregatorClass = BOVW.class;
private final String indexPath = "test-index";
private final String indexPathSeparate = "test-separate";
private final String testExtensive = "testdata/UCID_png";
// private final String testExtensive = "testdata/ferrari";
private final String testExtensiveBlack = "testdata/ferrari/black";
private final String testExtensiveRed = "testdata/ferrari/red";
private final String testExtensiveWhite = "testdata/ferrari/white";
private final String testExtensiveYellow = "testdata/ferrari/yellow";
String codebookPath = "./src/test/resources/codebooks/";
private int numOfDocsForVocabulary = 500;
// private int numOfClusters = 512;
private int[] numsOfClusters = new int[] {32, 128};
//Create new index
public void testCreateNewIndex() throws IOException {
// ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive);
// ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive, numOfClusters, numOfDocsForVocabulary);
// ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive, numOfClusters, numOfDocsForVocabulary, aggregatorClass);
//
// ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive, numsOfClusters, numOfDocsForVocabulary);
// ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive, numsOfClusters, numOfDocsForVocabulary, aggregatorClass);
Cluster[] codebook32 = Cluster.readClusters(codebookPath + "CvSURF32");
Cluster[] codebook128 = Cluster.readClusters(codebookPath + "SIMPLEdetCVSURFCEDD128");
Cluster[] codebook512 = Cluster.readClusters(codebookPath + "SIMPLEdetCVSURFCEDD512");
LinkedList<Cluster[]> myList = new LinkedList<Cluster[]>();
myList.add(codebook128);
myList.add(codebook512);
ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive, numsOfClusters, numOfDocsForVocabulary, aggregatorClass);
parallelIndexer.addExtractor(globalFeatureClass);
parallelIndexer.addExtractor(localFeatureClass);
// parallelIndexer.addExtractor(localFeatureClass, codebook32);
parallelIndexer.addExtractor(globalFeatureClass, keypointDetector, myList);
parallelIndexer.run();
}
//APPEND
public void testAppendExistingIndex() throws IOException {
//Create an index
ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive, numsOfClusters, numOfDocsForVocabulary, aggregatorClass);
parallelIndexer.addExtractor(globalFeatureClass);
parallelIndexer.addExtractor(localFeatureClass);
parallelIndexer.addExtractor(globalFeatureClass, keypointDetector);
parallelIndexer.run();
//Append new images in that index
ParallelIndexer parallelIndexerAppend = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensiveYellow, false);
parallelIndexerAppend.run();
}
//USE EXISTING SETUP
public void testIndexUsingExistingSetup(){
//Create an index
ParallelIndexer parallelIndexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPath, testExtensive, numsOfClusters, numOfDocsForVocabulary, aggregatorClass);
parallelIndexer.addExtractor(globalFeatureClass);
parallelIndexer.addExtractor(localFeatureClass);
parallelIndexer.addExtractor(globalFeatureClass, keypointDetector);
parallelIndexer.run();
//Create index using another indexe's setup
ParallelIndexer parallelIndexerSeparate = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexPathSeparate, testExtensiveRed, indexPath);
parallelIndexerSeparate.run();
}
}