LIRe 源代码分析 3：基本接口（ImageSearcher）
上篇文章介绍了LIRe源代码里的DocumentBuilder的几个基本接口：
LIRe 源代码分析 2：基本接口（DocumentBuilder）
本文继续研究一下源代码里的ImageSearcher的几个基本接口。
下面来看看与ImageSearcher相关的类的定义：
ImageSearcher：接口，定义了基本的方法。
AbstractImageSearcher：纯虚类，实现了ImageSearcher接口。
ImageSearcherFactory：用于创建ImageSearcher。
ImageSearcher相关的类的继承关系如下图所示。可见，各种算法类都继承了AbstractImageSearcher，而AbstractImageSearcher实现了ImageSearcher接口。
此外还有一个结构体：
ImageSearchHits：用于存储搜索的结果。
详细的源代码如下所示：
ImageSearcher
/* * This file is part of the LIRe project: http://www.semanticmetadata.net/lire * LIRe is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * LIRe 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 General Public License for more details. * * You should have received a copy of the GNU General Public License * along with LIRe; if not, write to the Free Software * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * * We kindly ask you to refer the following paper in any publication mentioning Lire: * * Lux Mathias, Savvas A. Chatzichristofis. Lire: Lucene Image Retrieval 鈥? * An Extensible Java CBIR Library. In proceedings of the 16th ACM International * Conference on Multimedia, pp. 1085-1088, Vancouver, Canada, 2008 * * http://doi.acm.org/10.1145/1459359.1459577 * * Copyright statement: * -------------------- * (c) 2002-2011 by Mathias Lux (mathias@juggle.at) * http://www.semanticmetadata.net/lire */package net.semanticmetadata.lire.impl;import net.semanticmetadata.lire.ImageSearchHits;import org.apache.lucene.document.Document;import java.util.ArrayList;import java.util.Collection;import java.util.Iterator;/** * This file is part of the Caliph and Emir project: http://www.SemanticMetadata.net * <br>Date: 02.02.2006 * <br>Time: 23:56:15 * * @author Mathias Lux, mathias@juggle.at */public class SimpleImageSearchHits implements ImageSearchHits { ArrayList<SimpleResult> results; public SimpleImageSearchHits(Collection<SimpleResult> results, float maxDistance) { this.results = new ArrayList<SimpleResult>(results.size()); this.results.addAll(results); // this step normalizes and inverts the distance ... // although its now a score or similarity like measure its further called distance for (Iterator<SimpleResult> iterator = this.results.iterator(); iterator.hasNext(); ) { SimpleResult result = iterator.next(); result.setDistance(1f - result.getDistance() / maxDistance); } } /** * Returns the size of the result list. * * @return the size of the result list. */ public int length() { return results.size(); } /** * Returns the score of the document at given position. * Please note that the score in this case is a distance, * which means a score of 0 denotes the best possible hit. * The result list starts with position 0 as everything * in computer science does. * * @param position defines the position * @return the score of the document at given position. The lower the better (its a distance measure). */ public float score(int position) { return results.get(position).getDistance(); } /** * Returns the document at given position * * @param position defines the position. * @return the document at given position. */ public Document doc(int position) { return results.get(position).getDocument(); } private float sigmoid(float f) { double result = 0f; result = -1d + 2d / (1d + Math.exp(-2d * f / 0.6)); return (float) (1d - result); }}