Exemplo n.º 1
0
 protected boolean isConfigured() {
   boolean isConfigured = true;
   // check if there are input files and if they exist.
   if (inputFiles.size() > 0) {
     for (Iterator<File> iterator = inputFiles.iterator(); iterator.hasNext(); ) {
       File next = iterator.next();
       if (!next.exists()) {
         isConfigured = false;
         System.err.println("Input file " + next.getPath() + " does not exist.");
       }
     }
   }
   return isConfigured;
 }
Exemplo n.º 2
0
 public void run() {
   // do it ...
   try {
     IndexWriter indexWriter =
         LuceneUtils.createIndexWriter(
             indexPath, overwriteIndex, LuceneUtils.AnalyzerType.WhitespaceAnalyzer);
     for (Iterator<File> iterator = inputFiles.iterator(); iterator.hasNext(); ) {
       File inputFile = iterator.next();
       if (verbose) System.out.println("Processing " + inputFile.getPath() + ".");
       if (verbose) System.out.println("Counting images.");
       run = 0;
       readFile(indexWriter, inputFile);
       if (verbose) System.out.printf("%d images found in the data file.\n", docCount);
       int numberOfRepresentatives = 1000; // TODO: clever selection.
       // select a number of representative "fixed stars" randomly from file
       if (numberOfRepresentatives > Math.sqrt(docCount))
         numberOfRepresentatives = (int) Math.sqrt(docCount);
       if (verbose)
         System.out.printf(
             "Selecting %d representative images for hashing.\n", numberOfRepresentatives);
       representativesID = new HashSet<Integer>(numberOfRepresentatives);
       while (representativesID.size() < numberOfRepresentatives) {
         representativesID.add((int) Math.floor(Math.random() * (docCount - 1)));
       }
       representatives = new ArrayList<LireFeature>(numberOfRepresentatives);
       docCount = 0;
       run = 1;
       if (verbose) System.out.println("Now getting representatives from the data file.");
       readFile(indexWriter, inputFile);
       docCount = 0;
       run = 2;
       if (verbose) System.out.println("Finally we start the indexing process, please wait ...");
       readFile(indexWriter, inputFile);
       if (verbose) System.out.println("Indexing finished.");
     }
     indexWriter.commit();
     indexWriter.close();
   } catch (Exception e) {
     e.printStackTrace();
   }
 }
Exemplo n.º 3
0
 private int[] getHashes(LireFeature feature) {
   // result = new int[maximumHits];
   hashingResultScoreDocs.clear();
   maxDistance = 0f;
   tmpScore = 0f;
   int rep = 0;
   LireFeature tmpFeature;
   for (Iterator<LireFeature> iterator = representatives.iterator(); iterator.hasNext(); ) {
     tmpFeature = iterator.next();
     tmpScore = tmpFeature.getDistance(feature);
     if (hashingResultScoreDocs.size() < maximumHits) {
       hashingResultScoreDocs.add(new SimpleResult(tmpScore, null, rep));
       maxDistance = Math.max(maxDistance, tmpScore);
     } else if (tmpScore < maxDistance) {
       hashingResultScoreDocs.add(new SimpleResult(tmpScore, null, rep));
     }
     while (hashingResultScoreDocs.size() > maximumHits) {
       hashingResultScoreDocs.remove(hashingResultScoreDocs.last());
       maxDistance = hashingResultScoreDocs.last().getDistance();
     }
     rep++;
   }
   rep = 0;
   for (Iterator<SimpleResult> iterator = hashingResultScoreDocs.iterator();
       iterator.hasNext(); ) {
     SimpleResult next = iterator.next();
     result[rep] = next.getIndexNumber();
     rep++;
   }
   return result;
 }