edu.anu.spice.Annotator.java Source code

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Here is the source code for edu.anu.spice.Annotator.java

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/*
 * Copyright (c) 2016, Peter Anderson <peter.anderson@anu.edu.au>
 *
 * This file is part of Semantic Propositional Image Caption Evaluation
 * (SPICE).
 * 
 * SPICE is free software: you can redistribute it and/or modify
 * it under the terms of the GNU Affero General Public License as published
 * by the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
    
 * SPICE 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 Affero General Public License for more details.
    
 * You should have received a copy of the GNU Affero General Public
 * License along with SPICE.  If not, see <http://www.gnu.org/licenses/>.
 * 
 */

package edu.anu.spice;

import java.util.ArrayList;
import java.util.List;
import java.util.Properties;

import com.google.common.base.Stopwatch;
import com.google.common.collect.Lists;

import edu.stanford.nlp.pipeline.Annotation;
import edu.stanford.nlp.pipeline.StanfordCoreNLP;

/**
 * Class to perform batched multi-threaded dependency parsing.
 */
public class Annotator {

    protected StanfordCoreNLP pipeline;
    protected int numThreads;
    protected int maxBatchSize;
    protected List<List<String>> batches;
    protected int batchNum;

    public Annotator(int numThreads, int batchSize) {
        this.pipeline = null;
        this.numThreads = numThreads;
        this.batches = null;
        this.batchNum = 0;
        this.maxBatchSize = batchSize;
    }

    private void initPipeline() {
        System.err.println("Initiating Stanford parsing pipeline");
        Properties props = new Properties();
        props.setProperty("annotators", "tokenize,ssplit,parse,lemma,ner");
        props.setProperty("depparse.extradependencies", "MAXIMAL");
        props.setProperty("threads", Integer.toString(this.numThreads));
        this.pipeline = new StanfordCoreNLP(props);
    }

    public void setInput(List<String> captions) {
        this.batches = Lists.partition(captions, this.maxBatchSize);
        this.batchNum = 0;
    }

    List<Annotation> parseNextBatch() {
        //Stopwatch timer = Stopwatch.createStarted();      
        List<Annotation> result = new ArrayList<Annotation>();
        if (this.batches != null && this.batchNum < this.batches.size()) {
            for (String caption : this.batches.get(batchNum)) {
                result.add(new Annotation(caption));
            }
            if (!result.isEmpty()) {
                if (this.pipeline == null) {
                    initPipeline();
                }
                this.pipeline.annotate(result);
            }
            batchNum++;
            if (batchNum >= this.batches.size()) {
                this.batches = null;
            }
        }
        //System.out.println("parseCaptions took: " + timer.stop());
        return result;
    }
}