Examples with JochreImage com.joliciel.jochre.graphics.JochreImage used on opensource projects

Example 11 with JochreImage

use of com.joliciel.jochre.graphics.JochreImage in project jochre by urieli.

the class DocumentController method getDocumentTree.

public TreeModel<TreeNode<DocOrImage>> getDocumentTree() {
    LOG.debug("getDocumentTree2");
    DocumentDao documentDao = DocumentDao.getInstance(jochreSession);
    List<JochreDocument> docs = documentDao.findDocuments();
    List<TreeNode<DocOrImage>> docNodeList = new ArrayList<>();
    for (JochreDocument doc : docs) {
        List<TreeNode<DocOrImage>> imageNodeList = new ArrayList<>();
        for (JochrePage page : doc.getPages()) {
            LOG.debug("page " + page.getIndex());
            for (JochreImage image : page.getImages()) {
                DefaultTreeNode<DocOrImage> imageNode = new DefaultTreeNode<DocumentController.DocOrImage>(new DocOrImage(image));
                imageNodeList.add(imageNode);
                if (imageId == image.getId())
                    currentImage = image;
            }
        // have images?
        }
        boolean open = docId == doc.getId();
        if (open)
            currentDoc = doc;
        DefaultTreeNode<DocOrImage> docNode = new DirectoryTreeNode<DocumentController.DocOrImage>(new DocOrImage(doc), imageNodeList, open);
        docNodeList.add(docNode);
    }
    DefaultTreeNode<DocOrImage> root = new DefaultTreeNode<DocumentController.DocOrImage>(null, docNodeList);
    TreeModel<TreeNode<DocOrImage>> docTree = new DefaultTreeModel<>(root);
    this.reloadDoc();
    this.reloadImage();
    return docTree;
}

Example 12 with JochreImage

use of com.joliciel.jochre.graphics.JochreImage in project jochre by urieli.

the class LetterFeatureTester method applyFeatures.

/**
 * Apply the features provided to all images currently marked as
 * ImageStatus.TRAINING_VALIDATED.
 *
 * @param minShapeId
 *            the first shape id to apply features to
 */
public void applyFeatures(Set<LetterFeature<?>> features, Set<String> letters, int minImageId, int minShapeId) {
    GraphicsDao graphicsDao = GraphicsDao.getInstance(jochreSession);
    List<JochreImage> images = graphicsDao.findImages(new ImageStatus[] { ImageStatus.TRAINING_VALIDATED });
    for (JochreImage image : images) {
        if (image.getId() >= minImageId) {
            this.testFeatures(image, features, letters, minShapeId);
        }
        image.clearMemory();
    }
}

Example 13 with JochreImage

use of com.joliciel.jochre.graphics.JochreImage in project jochre by urieli.

the class CorpusLexiconBuilder method buildLexicon.

/**
 * Build a lexicon from the training corpus.
 */
public TextFileLexicon buildLexicon() {
    TextFileLexicon lexicon = new TextFileLexicon();
    JochreCorpusImageReader imageReader = new JochreCorpusImageReader(jochreSession);
    imageReader.setSelectionCriteria(criteria);
    String wordText = "";
    while (imageReader.hasNext()) {
        JochreImage image = imageReader.next();
        for (Paragraph paragraph : image.getParagraphs()) {
            // rows ending in dashes can only be held-over within the same
            // paragraph.
            // to avoid strange things like a page number getting added to
            // the word,
            // if the dash is on the last row of the page.
            String holdoverWord = null;
            for (RowOfShapes row : paragraph.getRows()) {
                for (GroupOfShapes group : row.getGroups()) {
                    if (group.isBrokenWord())
                        continue;
                    wordText = "";
                    for (Shape shape : group.getShapes()) {
                        if (shape.getLetter() != null)
                            wordText += shape.getLetter();
                    }
                    if (wordText.length() == 0) {
                        lexicon.incrementEntry("");
                        continue;
                    }
                    List<String> words = jochreSession.getLinguistics().splitText(wordText);
                    int i = 0;
                    for (String word : words) {
                        if (i == 0) {
                            // first word
                            if (holdoverWord != null && holdoverWord.length() > 0) {
                                word = holdoverWord + word;
                                holdoverWord = null;
                            }
                        }
                        if (i == words.size() - 1) {
                            // last word
                            if (group.getIndex() == row.getGroups().size() - 1 && word.endsWith("-")) {
                                // a dash at the end of a line
                                if (group.isHardHyphen())
                                    holdoverWord = word;
                                else
                                    holdoverWord = word.substring(0, word.length() - 1);
                                word = "";
                            }
                        }
                        lexicon.incrementEntry(word);
                        i++;
                    }
                }
            }
        }
    }
    return lexicon;
}

Example 14 with JochreImage

use of com.joliciel.jochre.graphics.JochreImage in project jochre by urieli.

the class RecursiveShapeSplitterTest method testSplitShapeNoSplitMoreLikely.

@SuppressWarnings("unchecked")
@Test
public void testSplitShapeNoSplitMoreLikely() throws Exception {
    System.setProperty("config.file", "src/test/resources/test.conf");
    ConfigFactory.invalidateCaches();
    Config config = ConfigFactory.load();
    JochreSession jochreSession = new JochreSession(config);
    BufferedImage originalImage = new BufferedImage(256, 256, BufferedImage.TYPE_INT_RGB);
    final JochreImage jochreImage = new JochreImage(originalImage, jochreSession);
    final Shape shape = new Shape(jochreImage, 0, 0, 63, 15, jochreSession);
    shape.setBaseLine(12);
    shape.setMeanLine(4);
    final Shape shape1 = new Shape(jochreImage, 0, 0, 31, 15, jochreSession);
    shape1.setBaseLine(12);
    shape1.setMeanLine(4);
    final Shape shape2 = new Shape(jochreImage, 32, 0, 63, 15, jochreSession);
    shape2.setBaseLine(12);
    shape2.setMeanLine(4);
    final SplitCandidateFinder splitCandidateFinder = mock(SplitCandidateFinder.class);
    final DecisionMaker decisionMaker = mock(DecisionMaker.class);
    Split split = new Split(shape, jochreSession);
    split.setPosition(31);
    List<Split> splits = new ArrayList<>();
    splits.add(split);
    when(splitCandidateFinder.findSplitCandidates(shape)).thenReturn(splits);
    Decision yesDecision = new Decision(SplitOutcome.DO_SPLIT.name(), 0.4);
    Decision noDecision = new Decision(SplitOutcome.DO_NOT_SPLIT.name(), 0.6);
    List<Decision> decisions = new ArrayList<>();
    decisions.add(yesDecision);
    decisions.add(noDecision);
    when(decisionMaker.decide(anyList())).thenReturn(decisions);
    Split split1 = new Split(shape1, jochreSession);
    split1.setPosition(15);
    List<Split> splits1 = new ArrayList<>();
    splits1.add(split1);
    when(splitCandidateFinder.findSplitCandidates(shape1)).thenReturn(splits1);
    Split split2 = new Split(shape2, jochreSession);
    split2.setPosition(15);
    List<Split> splits2 = new ArrayList<>();
    splits2.add(split2);
    when(splitCandidateFinder.findSplitCandidates(shape2)).thenReturn(splits2);
    Set<SplitFeature<?>> splitFeatures = new TreeSet<>();
    RecursiveShapeSplitter splitter = new RecursiveShapeSplitter(splitCandidateFinder, splitFeatures, decisionMaker, jochreSession);
    splitter.setBeamWidth(10);
    splitter.setMaxDepth(2);
    splitter.setMinWidthRatio(1.0);
    List<ShapeSequence> shapeSequences = splitter.split(shape);
    assertEquals(5, shapeSequences.size());
    int i = 0;
    double prob = 1.0;
    double twoThirds = 0.4 / 0.6;
    LOG.debug("twoThirds: " + twoThirds);
    for (ShapeSequence shapeSequence : shapeSequences) {
        LOG.debug("sequence " + i + " decisions:");
        for (Decision decision : shapeSequence.getDecisions()) LOG.debug("" + decision.getProbability());
        if (i == 0) {
            prob = 1.0;
            assertEquals(prob, shapeSequence.getScore(), 0.0001);
            assertEquals(1, shapeSequence.size());
        } else if (i == 1) {
            prob = 1.0 * twoThirds;
            assertEquals(prob, shapeSequence.getScore(), 0.0001);
            assertEquals(2, shapeSequence.size());
        } else if (i == 2) {
            prob = 1.0 * twoThirds * twoThirds;
            assertEquals(prob, shapeSequence.getScore(), 0.0001);
            assertEquals(3, shapeSequence.size());
        } else if (i == 3) {
            prob = 1.0 * twoThirds * twoThirds;
            assertEquals(prob, shapeSequence.getScore(), 0.0001);
            assertEquals(3, shapeSequence.size());
        } else if (i == 4) {
            prob = 1.0 * twoThirds * twoThirds * twoThirds;
            assertEquals(prob, shapeSequence.getScore(), 0.0001);
            assertEquals(4, shapeSequence.size());
        }
        i++;
    }
}

Example 15 with JochreImage

use of com.joliciel.jochre.graphics.JochreImage in project jochre by urieli.

the class RecursiveShapeSplitterTest method testSplitShapeSplitMoreLikely.

/**
 * If a split is always more likely (e.g. 60% likelihood), ensure the shape
 * sequences are ordered correctly.
 */
@SuppressWarnings("unchecked")
@Test
public void testSplitShapeSplitMoreLikely() throws Exception {
    System.setProperty("config.file", "src/test/resources/test.conf");
    ConfigFactory.invalidateCaches();
    Config config = ConfigFactory.load();
    JochreSession jochreSession = new JochreSession(config);
    BufferedImage originalImage = new BufferedImage(256, 256, BufferedImage.TYPE_INT_RGB);
    final JochreImage jochreImage = new JochreImage(originalImage, jochreSession);
    final Shape shape = new Shape(jochreImage, 0, 0, 63, 15, jochreSession);
    shape.setBaseLine(12);
    shape.setMeanLine(4);
    final Shape shape1 = new Shape(jochreImage, 0, 0, 31, 15, jochreSession);
    shape1.setBaseLine(12);
    shape1.setMeanLine(4);
    final Shape shape2 = new Shape(jochreImage, 32, 0, 63, 15, jochreSession);
    shape2.setBaseLine(12);
    shape2.setMeanLine(4);
    final SplitCandidateFinder splitCandidateFinder = mock(SplitCandidateFinder.class);
    final DecisionMaker decisionMaker = mock(DecisionMaker.class);
    Split split = new Split(shape, jochreSession);
    split.setPosition(31);
    List<Split> splits = new ArrayList<>();
    splits.add(split);
    when(splitCandidateFinder.findSplitCandidates(shape)).thenReturn(splits);
    Decision yesDecision = new Decision(SplitOutcome.DO_SPLIT.name(), 0.6);
    Decision noDecision = new Decision(SplitOutcome.DO_NOT_SPLIT.name(), 0.4);
    List<Decision> decisions = new ArrayList<>();
    decisions.add(yesDecision);
    decisions.add(noDecision);
    when(decisionMaker.decide(anyList())).thenReturn(decisions);
    Split split1 = new Split(shape1, jochreSession);
    split1.setPosition(15);
    List<Split> splits1 = new ArrayList<>();
    splits1.add(split1);
    when(splitCandidateFinder.findSplitCandidates(shape1)).thenReturn(splits1);
    Split split2 = new Split(shape2, jochreSession);
    split2.setPosition(15);
    List<Split> splits2 = new ArrayList<>();
    splits2.add(split2);
    when(splitCandidateFinder.findSplitCandidates(shape2)).thenReturn(splits2);
    Set<SplitFeature<?>> splitFeatures = new TreeSet<>();
    RecursiveShapeSplitter splitter = new RecursiveShapeSplitter(splitCandidateFinder, splitFeatures, decisionMaker, jochreSession);
    splitter.setBeamWidth(10);
    splitter.setMaxDepth(2);
    splitter.setMinWidthRatio(1.0);
    List<ShapeSequence> shapeSequences = splitter.split(shape);
    assertEquals(5, shapeSequences.size());
    int i = 0;
    for (ShapeSequence shapeSequence : shapeSequences) {
        LOG.debug("sequence " + i + " shapes:");
        for (ShapeInSequence shapeInSequence : shapeSequence) {
            Shape oneShape = shapeInSequence.getShape();
            LOG.debug("Shape: " + oneShape.getLeft() + "," + oneShape.getRight());
        }
        LOG.debug("" + shapeSequence.getScore());
        i++;
    }
    i = 0;
    double prob = 1.0;
    double twoThirds = 0.4 / 0.6;
    LOG.debug("twoThirds: " + twoThirds);
    for (ShapeSequence shapeSequence : shapeSequences) {
        LOG.debug("sequence " + i + " decisions:");
        for (Decision decision : shapeSequence.getDecisions()) LOG.debug("" + decision.getProbability());
        if (i == 0) {
            prob = 1.0;
            assertEquals(prob, shapeSequence.getScore(), 0.0001);
            assertEquals(4, shapeSequence.size());
        } else if (i == 1) {
            prob = 1.0 * twoThirds;
            assertEquals(prob, shapeSequence.getScore(), 0.0001);
            assertEquals(3, shapeSequence.size());
        } else if (i == 2) {
            prob = 1.0 * twoThirds;
            assertEquals(prob, shapeSequence.getScore(), 0.0001);
            assertEquals(3, shapeSequence.size());
        } else if (i == 3) {
            prob = 1.0 * twoThirds * twoThirds;
            assertEquals(prob, shapeSequence.getScore(), 0.0001);
            assertEquals(2, shapeSequence.size());
        } else if (i == 4) {
            prob = 1.0 * twoThirds * twoThirds * twoThirds;
            assertEquals(prob, shapeSequence.getScore(), 0.0001);
            assertEquals(1, shapeSequence.size());
        }
        i++;
    }
}