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JAVA基于图片相似性算法实现以图搜图样例

 

一、简述

  本文主要讲如何利用图片相似性算法,基于LIRE来实现图片搜索。

二、依赖

   <dependencies>
        <!-- https://mvnrepository.com/artifact/org.apache.lucene/lucene-core -->
        <dependency>
            <groupId>org.apache.lucene</groupId>
            <artifactId>lucene-core</artifactId>
            <version>6.3.0</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.lucene/lucene-queryparser -->
        <dependency>
            <groupId>org.apache.lucene</groupId>
            <artifactId>lucene-queryparser</artifactId>
            <version>6.3.0</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.lucene/lucene-analyzers-common -->
        <dependency>
            <groupId>org.apache.lucene</groupId>
            <artifactId>lucene-analyzers-common</artifactId>
            <version>6.3.0</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/commons-io/commons-io -->
        <dependency>
            <groupId>commons-io</groupId>
            <artifactId>commons-io</artifactId>
            <version>2.6</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.commons/commons-math3 -->
        <dependency>
            <groupId>org.apache.commons</groupId>
            <artifactId>commons-math3</artifactId>
            <version>3.6.1</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/com.sangupta/jopensurf -->
        <dependency>
            <groupId>com.sangupta</groupId>
            <artifactId>jopensurf</artifactId>
            <version>1.0.0</version>
        </dependency>
    </dependencies>

 

二、样例1

  Data目录下存放所有图片的样本。

package com.dearcloud.imagesearch;

import net.semanticmetadata.lire.aggregators.AbstractAggregator;
import net.semanticmetadata.lire.aggregators.BOVW;
import net.semanticmetadata.lire.builders.DocumentBuilder;
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 net.semanticmetadata.lire.searchers.GenericFastImageSearcher;
import net.semanticmetadata.lire.searchers.ImageSearchHits;
import net.semanticmetadata.lire.searchers.ImageSearcher;
import net.semanticmetadata.lire.utils.FileUtils;
import net.semanticmetadata.lire.utils.ImageUtils;
import org.apache.lucene.index.DirectoryReader;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.store.FSDirectory;

import javax.imageio.ImageIO;
import java.io.File;
import java.io.IOException;
import java.nio.file.Paths;

public class IndexingAndSearchWithLocalFeatures {
    public static void main(String[] args) throws IOException {
        String indexPath = "D:\\以图搜图\\衬衣\\index";
        String imageData = "D:\\以图搜图\\衬衣\\Data";
        indexer(indexPath, imageData);

        String searchImage = "D:\\以图搜图\\衬衣\\search\\timg.jpg";
        String searchOutputFolder = "D:\\以图搜图\\衬衣\\output";
        search(indexPath, searchImage, searchOutputFolder);
    }

    /**
     * Indexing data using OpenCV and SURF as well as CEDD and SIMPLE.
     * @param indexFolder
     * @param imageDirectory
     */
    private static void indexer(String indexFolder, String imageDirectory) {
        // Checking if arg[0] is there and if it is a directory.
        boolean passed = false;
        // use ParallelIndexer to index all photos from args[0] into "index".
        int numOfDocsForVocabulary = 500;
        Class<? extends AbstractAggregator> aggregator = BOVW.class;
        int[] numOfClusters = new int[]{128};
        ParallelIndexer indexer = new ParallelIndexer(DocumentBuilder.NUM_OF_THREADS, indexFolder, imageDirectory, numOfClusters, numOfDocsForVocabulary, aggregator);
        indexer.setImagePreprocessor(image -> ImageUtils.createWorkingCopy(image));
        //Local
        indexer.addExtractor(CvSurfExtractor.class);
        //Simple
        indexer.addExtractor(CEDD.class, SimpleExtractor.KeypointDetector.CVSURF);

        indexer.run();
        System.out.println("Finished indexing.");
    }

    /**
     * Linear search on the indexed data.
     * @param indexPath
     * @throws IOException
     */
    public static void search(String indexPath, String searchFile, String searchOutputFolder) throws IOException {
        IndexReader reader = DirectoryReader.open(FSDirectory.open(Paths.get(indexPath)));

        // make sure that this matches what you used for indexing (see below) ...
        ImageSearcher imgSearcher = new GenericFastImageSearcher(1000, CEDD.class, SimpleExtractor.KeypointDetector.CVSURF, new BOVW(), 128, true, reader, indexPath + ".config");
        // just a static example with a given image.
        ImageSearchHits hits = imgSearcher.search(ImageIO.read(new File(searchFile)), reader);

        for (int i = 0; i < hits.length(); i++) {
            double score = hits.score(i);
            String imagePath = reader.document(hits.documentID(i)).getValues(DocumentBuilder.FIELD_NAME_IDENTIFIER)[0];
            System.out.printf("%.2f: (%d) %s\n", score, hits.documentID(i), imagePath);
        }
        String outputHtmlReport = FileUtils.saveImageResultsToHtml("search-", hits, searchFile, reader);
        System.out.println("Report:" + outputHtmlReport);
        org.apache.commons.io.FileUtils.copyFile(org.apache.commons.io.FileUtils.getFile(outputHtmlReport), org.apache.commons.io.FileUtils.getFile(searchOutputFolder, outputHtmlReport));
    }

}

 

三、样例2

  1、Indexer

package com.dearcloud.imagesearch;

import net.semanticmetadata.lire.builders.GlobalDocumentBuilder;
import net.semanticmetadata.lire.imageanalysis.features.global.AutoColorCorrelogram;
import net.semanticmetadata.lire.imageanalysis.features.global.CEDD;
import net.semanticmetadata.lire.imageanalysis.features.global.FCTH;
import net.semanticmetadata.lire.utils.FileUtils;
import org.apache.lucene.analysis.core.WhitespaceAnalyzer;
import org.apache.lucene.document.Document;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.index.IndexWriterConfig;
import org.apache.lucene.store.FSDirectory;

import javax.imageio.ImageIO;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import java.nio.file.Paths;
import java.util.ArrayList;
import java.util.Iterator;

public class LireIndexer {
    public static void main(String[] args) throws IOException {
        String indexPath = "D:\\以图搜图\\全部\\index";
        String imageData = "D:\\以图搜图\\全部\\Data";
        index(indexPath, imageData);
    }

    private static void index(String indexFolder, String imageDirectory) throws IOException {
        // Getting all images from a directory and its sub directories.
        ArrayList<String> images = FileUtils.getAllImages(new File(imageDirectory), true);

        // Creating a CEDD document builder and indexing all files.
        GlobalDocumentBuilder globalDocumentBuilder = new GlobalDocumentBuilder(false, false);
        /*
            If you want to use DocValues, which makes linear search much faster, then use.
            However, you then have to use a specific searcher!
         */
        // GlobalDocumentBuilder globalDocumentBuilder = new GlobalDocumentBuilder(false, true);

        /*
            Then add those features we want to extract in a single run:
         */
        globalDocumentBuilder.addExtractor(CEDD.class);
        globalDocumentBuilder.addExtractor(FCTH.class);
        globalDocumentBuilder.addExtractor(AutoColorCorrelogram.class);

        // Creating an Lucene IndexWriter
        IndexWriterConfig conf = new IndexWriterConfig(new WhitespaceAnalyzer());
        IndexWriter iw = new IndexWriter(FSDirectory.open(Paths.get(indexFolder)), conf);
        // Iterating through images building the low level features
        for (Iterator<String> it = images.iterator(); it.hasNext(); ) {
            String imageFilePath = it.next();
            System.out.println("Indexing " + imageFilePath);
            try {
                BufferedImage img = ImageIO.read(new FileInputStream(imageFilePath));
                if (img == null) continue;
                Document document = globalDocumentBuilder.createDocument(img, imageFilePath);
                iw.addDocument(document);
            } catch (Exception e) {
                System.err.println("Error reading image or indexing it.");
                e.printStackTrace();
            }
        }
        // closing the IndexWriter
        iw.close();
        System.out.println("Finished indexing.");
    }
}

  2、Searcher

package com.dearcloud.imagesearch;

import net.semanticmetadata.lire.builders.DocumentBuilder;
import net.semanticmetadata.lire.imageanalysis.features.global.CEDD;
import net.semanticmetadata.lire.searchers.GenericFastImageSearcher;
import net.semanticmetadata.lire.searchers.ImageSearchHits;
import net.semanticmetadata.lire.searchers.ImageSearcher;
import org.apache.commons.io.FileUtils;
import org.apache.lucene.index.DirectoryReader;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.store.FSDirectory;

import javax.imageio.ImageIO;
import java.awt.image.BufferedImage;
import java.io.IOException;
import java.nio.file.Paths;

public class LireSearcher {
    public static void main(String[] args) throws IOException {
        String indexPath = "D:\\以图搜图\\全部\\index";
        String searchImage = "D:\\以图搜图\\全部\\search\\timg.jpg";
        String searchOutputFolder = "D:\\以图搜图\\全部\\output";
        search(indexPath, searchImage, searchOutputFolder);
    }

    private static void search(String indexFolder, String searchFile, String searchOutputFolder) throws IOException {
        BufferedImage img = ImageIO.read(FileUtils.getFile(searchFile));

        IndexReader reader = DirectoryReader.open(FSDirectory.open(Paths.get(indexFolder)));
        ImageSearcher searcher = new GenericFastImageSearcher(30, CEDD.class);
        // ImageSearcher searcher = new GenericFastImageSearcher(30, AutoColorCorrelogram.class); // for another image descriptor ...

        /*
            If you used DocValues while Indexing, use the following searcher:
         */
        // ImageSearcher searcher = new GenericDocValuesImageSearcher(30, CEDD.class, ir);
        // searching with a image file ...
        ImageSearchHits hits = searcher.search(img, reader);
        // searching with a Lucene document instance ...
        // ImageSearchHits hits = searcher.search(ir.document(0), ir);
        for (int i = 0; i < hits.length(); i++) {
            String fileName = reader.document(hits.documentID(i)).getValues(DocumentBuilder.FIELD_NAME_IDENTIFIER)[0];
            System.out.println(hits.score(i) + ": \t" + fileName);
        }
        String outputHtmlReport = net.semanticmetadata.lire.utils.FileUtils.saveImageResultsToHtml("search-", hits, searchFile, reader);
        System.out.println("Report:" + outputHtmlReport);
        org.apache.commons.io.FileUtils.copyFile(org.apache.commons.io.FileUtils.getFile(outputHtmlReport), org.apache.commons.io.FileUtils.getFile(searchOutputFolder, outputHtmlReport));
    }
}

 

四、素材

       

  

 

 

 

 

五、LIRE支持的算法

  

  

 

posted @ 2019-03-13 17:40  宋兴柱  阅读(1015)  评论(2编辑  收藏