北京网站建设方案书,网站的设计 更新,做网站为什么需要花钱,东莞市人才招聘网以图搜图#xff0c;涉及两大功能#xff1a;1、提取图像特征向量。2、相似向量检索。第一个功能我通过编写pytorch模型并在java端借助djl调用实现#xff0c;第二个功能通过elasticsearch7.6.2的dense_vector、cosineSimilarity实现。一、准备模型创建demo.py#xff0c;输…以图搜图涉及两大功能1、提取图像特征向量。2、相似向量检索。第一个功能我通过编写pytorch模型并在java端借助djl调用实现第二个功能通过elasticsearch7.6.2的dense_vector、cosineSimilarity实现。一、准备模型创建demo.py输入代码借助resnet提取图像特征import torch
import torch.nn as nn
import torchvision.models as modelsclass ImageFeatureExtractor(nn.Module):def __init__(self):super(ImageFeatureExtractor, self).__init__()self.resnet models.resnet50(pretrainedTrue)#最终输出维度1024的向量下文elastic search要设置dims为1024self.resnet.fc nn.Linear(2048, 1024)def forward(self, x):x self.resnet(x)return xif __name__ __main__:model ImageFeatureExtractor()model.eval()#根据模型随便创建一个输入input torch.rand([1, 3, 224, 224])output model(input)#以这种方式保存script torch.jit.trace(model, input)script.save(model.pt)保存好的model.pt文件放入java项目的resources中可以在java中引入Deep-Java-Library来调用二、创建Java项目创建项目引入djl和elasticsearch的依赖dependencygroupIdai.djl.pytorch/groupIdartifactIdpytorch-engine/artifactIdversion0.19.0/version/dependencydependencygroupIdai.djl.pytorch/groupIdartifactIdpytorch-native-cpu/artifactIdversion1.10.0/versionscoperuntime/scope/dependencydependencygroupIdai.djl.pytorch/groupIdartifactIdpytorch-jni/artifactIdversion1.10.0-0.19.0/version/dependencydependencygroupIdorg.elasticsearch.client/groupIdartifactIdelasticsearch-rest-high-level-client/artifactIdversion7.6.2/version/dependency然后随便从网上下载点图片比如猫5张图狗5张图什么的放到项目resources/随便 路径下一会要提取他们的特征向量并上传至elasticsearch三、es创建文档需要在elastic search中创建一个新文档。localhost:9200/isi (img search img)PUT /isi
{mappings: {properties: {vector: {type: dense_vector,dims: 1024},url : {type : keyword},user_id: {type: keyword}}}
}完成下文上传操作后测试搜索params中queryVector为随便选了个图像提取的特征向量POST /isi/_search
{query: {function_score: {query: {match_all: {}},script_score: {script: {source: cosineSimilarity(params.queryVector, vector) ,params: {queryVector: [-0.21950562, 0.0979692, 0.30605257, -0.04246464, 0.3086218, 0.2133326, -0.13531154, 0.16382562, 0.2505685, 0.35654455, 0.50346404, -0.2031727, -0.4501943, 0.23117387, 0.39451313, 0.044487886, -0.11032343, 0.47252116, 0.24667346, -0.2052311, -0.10872754, 0.22328046, 0.13366169, -0.5555884, 0.23139203, 0.024292288, 0.3071902, 0.23381571, -0.14484097, -0.80570614, 0.096950606, -0.034106746, 0.3221968, 0.35980088, -0.24408965, 0.10010342, 0.34878045, 0.25403115, 0.8813986, -0.23978959, -0.101492174, -0.34241566, -0.258092, 0.38593173, 0.24993907, -0.6891467, 0.5723483, -0.4987241, -0.46613082, 0.07435644, -0.32876882, 0.1923833, 0.41619772, 0.006919967, -0.35519657, -0.2463252, -0.07216969, -0.10412077, -0.3964988, -0.43174505, 0.6576338, -0.09753291, 0.058324523, -0.366405, -0.08003934, -0.41232625, -0.59834087, 0.35432702, -0.33971205, 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}四、调用pytorch模型代码创建Test类copy一下我的感兴趣可以去djl的官网学习更多内容。写完后就可以获取“随便”文件夹中的图像的特征向量上传到es里了。package org.gwen;import ai.djl.Device;
import ai.djl.Model;
import ai.djl.inference.Predictor;
import ai.djl.modality.cv.Image;
import ai.djl.modality.cv.ImageFactory;
import ai.djl.modality.cv.transform.Normalize;
import ai.djl.modality.cv.transform.Resize;
import ai.djl.modality.cv.transform.ToTensor;
import ai.djl.modality.cv.util.NDImageUtils;
import ai.djl.ndarray.NDArray;
import ai.djl.ndarray.NDList;
import ai.djl.ndarray.NDManager;
import ai.djl.translate.Transform;
import ai.djl.translate.Translator;
import ai.djl.translate.TranslatorContext;
import org.apache.http.HttpHost;
import org.elasticsearch.action.bulk.BulkRequest;
import org.elasticsearch.action.index.IndexRequest;
import org.elasticsearch.action.search.SearchRequest;
import org.elasticsearch.action.search.SearchResponse;
import org.elasticsearch.client.RequestOptions;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.elasticsearch.client.RestHighLevelClient;
import org.elasticsearch.client.transport.TransportClient;
import org.elasticsearch.common.settings.Settings;
import org.elasticsearch.common.xcontent.XContentType;
import org.elasticsearch.index.query.QueryBuilders;
import org.elasticsearch.index.query.ScriptQueryBuilder;
import org.elasticsearch.index.query.functionscore.FunctionScoreQueryBuilder;
import org.elasticsearch.index.query.functionscore.ScoreFunctionBuilders;
import org.elasticsearch.script.Script;
import org.elasticsearch.script.ScriptType;
import org.elasticsearch.search.SearchHit;
import org.elasticsearch.search.SearchHits;
import org.elasticsearch.search.builder.SearchSourceBuilder;
import org.gwen.entity.SearchResult;import java.io.File;
import java.io.IOException;
import java.io.InputStream;
import java.net.URI;
import java.net.URL;
import java.nio.file.Paths;
import java.util.*;public class Test {private static final String INDEX isi;private static final int IMAGE_SIZE 224;private static Model model; //模型private static PredictorImage, float[] predictor; //predictor.predict(input)相当于python中model(input)static {try {model Model.newInstance(model);//这里的model.pt是上面代码展示的那种方式保存的model.load(Test.class.getClassLoader().getResourceAsStream(model.pt));Transform resize new Resize(IMAGE_SIZE);Transform toTensor new ToTensor();Transform normalize new Normalize(new float[]{0.485f, 0.456f, 0.406f}, new float[]{0.229f, 0.224f, 0.225f});//Translator处理输入Image转为tensor、输出转为float[]TranslatorImage, float[] translator new TranslatorImage, float[]() {Overridepublic NDList processInput(TranslatorContext ctx, Image input) throws Exception {NDManager ndManager ctx.getNDManager();System.out.println(input: input.getWidth() , input.getHeight());NDArray transform normalize.transform(toTensor.transform(resize.transform(input.toNDArray(ndManager))));System.out.println(transform.getShape());NDList list new NDList();list.add(transform);return list;}Overridepublic float[] processOutput(TranslatorContext ctx, NDList ndList) throws Exception {return ndList.get(0).toFloatArray();}};predictor new Predictor(model, translator, Device.cpu(), true);} catch (Exception e) {e.printStackTrace();}}
}五、es上传和搜索上传遍历每张图片获取每张图片的特征上传到es搜索获取输入图像的特征创建SearchRequest在es中通过painless脚本进行余弦相似度对比检索。首先创建SearchResult类表示es搜索的结果包括图像url和相关度评分scoreData
AllArgsConstructor
public class SearchResult {private String url;private Float score;
}然后在Test里实现upload和search public static void upload() throws Exception {RestHighLevelClient client new RestHighLevelClient(RestClient.builder(new HttpHost(localhost, 9200, http)));//批量上传请求BulkRequest bulkRequest new BulkRequest(INDEX);File file new File(C:\\Users\\Administrator\\IdeaProjects\\img_search_img\\src\\main\\resources\\随便);for (File listFile : file.listFiles()) {float[] vector predictor.predict(ImageFactory.getInstance().fromInputStream(Test.class.getClassLoader().getResourceAsStream(随便/ listFile.getName())));// 构建文档MapString, Object jsonMap new HashMap();jsonMap.put(url, listFile.getAbsolutePath());jsonMap.put(vector, vector);jsonMap.put(user_id, user123);IndexRequest request new IndexRequest(INDEX).source(jsonMap, XContentType.JSON);bulkRequest.add(request);}client.bulk(bulkRequest, RequestOptions.DEFAULT);client.close();}//接收待搜索图片的inputstream搜索与其相似的图片public static ListSearchResult search(InputStream input) throws Throwable {float[] vector predictor.predict(ImageFactory.getInstance().fromInputStream(input));System.out.println(Arrays.toString(vector));//展示k个结果int k 100;// 连接Elasticsearch服务器RestHighLevelClient client new RestHighLevelClient(RestClient.builder(new HttpHost(localhost, 9200, http)));SearchRequest searchRequest new SearchRequest(INDEX);Script script new Script(ScriptType.INLINE,painless,cosineSimilarity(params.queryVector, doc[vector]),Collections.singletonMap(queryVector, vector));FunctionScoreQueryBuilder functionScoreQueryBuilder QueryBuilders.functionScoreQuery(QueryBuilders.matchAllQuery(),ScoreFunctionBuilders.scriptFunction(script));SearchSourceBuilder searchSourceBuilder new SearchSourceBuilder();searchSourceBuilder.query(functionScoreQueryBuilder).fetchSource(null, vector) //不返回vector字段太多了没用还耗时.size(k);searchRequest.source(searchSourceBuilder);SearchResponse searchResponse client.search(searchRequest, RequestOptions.DEFAULT);SearchHits hits searchResponse.getHits();ListSearchResult list new ArrayList();for (SearchHit hit : hits) {// 处理搜索结果System.out.println(hit.toString());SearchResult result new SearchResult((String) hit.getSourceAsMap().get(url), hit.getScore());list.add(result);}client.close();return list;}六、测试RestController
CrossOrigin
public class SearchController {PostMapping(search)public ResponseEntity search(MultipartFile file) {try {ListSearchResult list Test.search(file.getInputStream());return ResponseEntity.ok(list);} catch (Throwable e) {return ResponseEntity.status(400).body(null);}}
}页面!DOCTYPE html
html langen
headmeta charsetUTF-8titleTitle/titlestylebody {background: url(/img/bg.jpg);background-attachment: fixed;background-size: 100% 100%;}body div {width: 1000px;margin: 50px auto;padding: 10px 20px;border: 1px solid lightgray;border-radius: 20px;box-sizing: border-box;background: rgba(255, 255, 255, 0.7);}.upload {display: inline-block;width: 300px;height: 280px;border: 1px dashed lightcoral;vertical-align: top;}.upload .cover {width: 200px;height: 200px;margin: 10px 50px;border: 1px solid black;box-sizing: border-box;text-align: center;line-height: 200px;position: relative;}.upload img {width: 198px;height: 198px;position: absolute;left:0;top: 0;}.upload input {margin-left: 50px;}.upload button {width: 80px;height: 30px;margin-left: 110px;}.result-block {display: inline-block;margin-left: 40px;border: 1px solid lightgray;border-radius: 10px;min-height: 500px;width: 600px;}.result-block h1 {text-align: center;margin-top: 100px;}.result {padding: 10px;cursor: pointer;display: inline-block;}.result:hover {background: rgb(240, 240, 240);}.result p {width: 110px;overflow: hidden;white-space: nowrap;text-overflow: ellipsis;}.result img {width: 160px;height: 160px;}.result .prob {color: rgb(37, 147, 60)}/stylescript srcjs/jquery-3.6.0.js/script
/head
body
divdiv classuploaddiv classcover请选择图片img idimage src//divinput idfile typefile/divdiv classresult-blockh1请选择图片/h1/div
/divul idbox/ul
scriptvar file $(#file)file.change(function () {let f this.files[0]let index f.name.lastIndexOf(.)let fileText f.name.substring(index,f.name.length)let ext fileText.toLowerCase() //文件类型console.log(ext)if(ext ! .png ext ! .jpg ext ! .jpeg){alert(系统仅支持 JPG、PNG、JPEG 格式的图片请您调整格式后重新上传)return}$(.result-block).empty().append($(h1正在识别中.../h1))$(#image).attr(src,getObjectURL(f));let formData new FormData()formData.append(file,f)$.ajax({url: http://localhost:8080/search,method: post,data: formData,processData: false,contentType: false,success: res {console.log(shibie, res)$(.result-block).empty()for (let item of res) {console.log(item)let html div classresultimg srcfile:///${item.url}/div styledisplay: inline-block;vertical-align: topp classprob得分${item.score.toFixed(4)}/p/div/div$(.result-block).append($(html))}}})});$(#button).click(function(e) {var file $(#file)[0].files[0] //单个console.log(file)})function getObjectURL(file) {var url null;if (window.createObjcectURL ! undefined) {url window.createOjcectURL(file);} else if (window.URL ! undefined) {url window.URL.createObjectURL(file);} else if (window.webkitURL ! undefined) {url window.webkitURL.createObjectURL(file);}return url;}function detect() {}
/script
/body
/html
