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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.tika.parser.recognition.tf;

import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.io.InputStream;
import java.net.URI;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.Set;

import org.apache.http.HttpResponse;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.client.methods.HttpPost;
import org.apache.http.entity.ByteArrayEntity;
import org.apache.http.impl.client.DefaultHttpClient;
import org.apache.tika.config.Field;
import org.apache.tika.config.InitializableProblemHandler;
import org.apache.tika.config.Param;
import org.apache.tika.exception.TikaConfigException;
import org.apache.tika.exception.TikaException;
import org.apache.tika.io.IOUtils;
import org.apache.tika.metadata.Metadata;
import org.apache.tika.mime.MediaType;
import org.apache.tika.parser.ParseContext;
import org.apache.tika.parser.recognition.ObjectRecogniser;
import org.apache.tika.parser.recognition.RecognisedObject;
import org.json.JSONArray;
import org.json.JSONObject;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.xml.sax.ContentHandler;
import org.xml.sax.SAXException;

/**
 * Tensor Flow image recogniser which has high performance.
 * This implementation uses Tensorflow via REST API.
 * 

* NOTE : //TODO: link to wiki page here * * @since Apache Tika 1.14 */ public class TensorflowRESTRecogniser implements ObjectRecogniser { private static final Logger LOG = LoggerFactory.getLogger(TensorflowRESTRecogniser.class); /** * Maximum buffer size for image */ private static final String LABEL_LANG = "en"; @Field private URI apiUri = URI.create("http://localhost:8764/inception/v4/classify?topk=10"); @Field private URI healthUri = URI.create("http://localhost:8764/inception/v4/ping"); private boolean available; protected URI getApiUri(Metadata metadata){ return apiUri; } @Override public Set getSupportedMimes() { return TensorflowImageRecParser.SUPPORTED_MIMES; } @Override public boolean isAvailable() { return available; } @Override public void initialize(Map params) throws TikaConfigException { try { DefaultHttpClient client = new DefaultHttpClient(); HttpResponse response = client.execute(new HttpGet(healthUri)); available = response.getStatusLine().getStatusCode() == 200; LOG.info("Available = {}, API Status = {}", available, response.getStatusLine()); } catch (Exception e) { available = false; throw new TikaConfigException(e.getMessage(), e); } } @Override public void checkInitialization(InitializableProblemHandler handler) throws TikaConfigException { //TODO -- what do we want to check? } @Override public List recognise(InputStream stream, ContentHandler handler, Metadata metadata, ParseContext context) throws IOException, SAXException, TikaException { List recObjs = new ArrayList<>(); try { DefaultHttpClient client = new DefaultHttpClient(); HttpPost request = new HttpPost(getApiUri(metadata)); try (ByteArrayOutputStream byteStream = new ByteArrayOutputStream()) { //TODO: convert this to stream, this might cause OOM issue // InputStreamEntity is not working // request.setEntity(new InputStreamEntity(stream, -1)); IOUtils.copy(stream, byteStream); request.setEntity(new ByteArrayEntity(byteStream.toByteArray())); } HttpResponse response = client.execute(request); try (InputStream reply = response.getEntity().getContent()) { String replyMessage = IOUtils.toString(reply); if (response.getStatusLine().getStatusCode() == 200) { JSONObject jReply = new JSONObject(replyMessage); JSONArray jClasses = jReply.getJSONArray("classnames"); JSONArray jConfidence = jReply.getJSONArray("confidence"); if (jClasses.length() != jConfidence.length()) { LOG.warn("Classes of size {} is not equal to confidence of size {}", jClasses.length(), jConfidence.length()); } assert jClasses.length() == jConfidence.length(); for (int i = 0; i < jClasses.length(); i++) { RecognisedObject recObj = new RecognisedObject(jClasses.getString(i), LABEL_LANG, jClasses.getString(i), jConfidence.getDouble(i)); recObjs.add(recObj); } } else { LOG.warn("Status = {}", response.getStatusLine()); LOG.warn("Response = {}", replyMessage); } } } catch (Exception e) { LOG.warn(e.getMessage(), e); } LOG.debug("Num Objects found {}", recObjs.size()); return recObjs; } }





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