629 lines
31 KiB
Java
629 lines
31 KiB
Java
package com.mixi.service;
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import cn.hutool.core.collection.CollectionUtil;
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import cn.hutool.core.exceptions.ExceptionUtil;
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import com.alibaba.fastjson.JSON;
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import com.alibaba.fastjson.JSONArray;
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import com.alibaba.fastjson.JSONObject;
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import com.baomidou.mybatisplus.core.conditions.query.QueryWrapper;
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import com.google.common.collect.Lists;
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import com.google.common.collect.Maps;
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import com.mixi.common.config.FileProperties;
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import com.mixi.common.config.exception.BusinessException;
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import com.mixi.common.utils.AccessLimitUtils;
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import com.mixi.mapper.TProductMapper;
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import com.mixi.mapper.entity.QeFilling;
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import com.mixi.mapper.entity.TProduct;
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import com.mixi.model.dto.AIRecommendDTO;
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import com.mixi.model.dto.GenerateCollocationDataBaseDTO;
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import com.mixi.model.dto.GenerateCollocationQueryDTO;
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import com.mixi.model.dto.GenerateCollocationQueryNewDTO;
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import com.mixi.model.vo.AppProductColorExtractVO;
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import com.mixi.model.vo.GenerateCollocationOutVO;
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import lombok.extern.slf4j.Slf4j;
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import okhttp3.*;
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import org.springframework.beans.factory.annotation.Value;
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import org.springframework.stereotype.Service;
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import javax.annotation.Resource;
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import java.io.IOException;
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import java.util.*;
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import java.util.concurrent.TimeUnit;
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import java.util.stream.Collectors;
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@Slf4j
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@Service
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public class PythonService {
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@Resource
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private FileProperties fileProperties;
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@Value("${access.python.ip:''}")
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private String accessPythonIp;
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/**
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* 识别对应的属性标签值
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*
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* @param pictureUrls
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* @param ids
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* @return
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*/
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public JSONObject attributeRecognition(List<String> pictureUrls,List<String> ids, List<String> category) {
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//限流校验
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AccessLimitUtils.validate("attributeRecognition", 20);
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OkHttpClient client = new OkHttpClient().newBuilder()
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.connectTimeout(30, TimeUnit.SECONDS)
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.pingInterval(5, TimeUnit.SECONDS)//websocket轮训间隔(单位:秒)
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.readTimeout(300, TimeUnit.SECONDS)//读取超时(单位:秒)
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.writeTimeout(300, TimeUnit.SECONDS)//写入超时(单位:秒)
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.build();
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MediaType mediaType = MediaType.parse("application/json");
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Map<String, List<String>> content = Maps.newHashMap();
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//识别图片路径数组
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content.put("upload_img_path", pictureUrls);
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//识别图片id数组
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content.put("upload_img_id", ids);
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content.put("upload_img_category", category);
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RequestBody body = RequestBody.create(mediaType, JSON.toJSONString(content));
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Request request = new Request.Builder()
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.url(accessPythonIp + ":9993/api/attribute")
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.method("POST", body)
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.addHeader("Authorization", "Basic YWlkbGFiOjEyMw==")
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.addHeader("Content-Type", "application/json")
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.build();
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Response response = null;
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String bodyStr = null;
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try {
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log.info("识别python对应的属性标签值请求入参content###{}", JSON.toJSONString(content));
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response = client.newCall(request).execute();
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bodyStr = response.body().string();
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} catch (IOException ioException) {
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log.error("PythonService###attributeRecognition异常##{}", ExceptionUtil.getThrowableList(ioException));
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}
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log.info("识别python对应的属性标签值结果###{}",bodyStr.trim());
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//去除限流
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AccessLimitUtils.validateOut("attributeRecognition");
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if (Objects.isNull(response)) {
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log.error("PythonService##attributeRecognition异常###{}", "response or body is empty!");
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throw new BusinessException("attribute recognition exception!");
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}
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JSONObject jsonObject = JSON.parseObject(JSON.toJSONString(response));
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Boolean result = jsonObject.getBoolean("successful");
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if (result) {
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JSONObject attributeJSONObject = JSON.parseObject(bodyStr.trim());
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return attributeJSONObject;
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}
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log.info("识别python对应的属性标签值异常###{}", jsonObject);
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//生成失败
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throw new BusinessException("Atribute recognition exception!");
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}
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/**
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* 商品推荐搭配
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*
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* @param query
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* @param dataBaseMap
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* @return
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*/
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public List<GenerateCollocationOutVO> generateCollocation(
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List<GenerateCollocationQueryDTO> query, Map<String, GenerateCollocationDataBaseDTO> dataBaseMap) {
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//限流校验
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AccessLimitUtils.validate("generateCollocation", 20);
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OkHttpClient client = new OkHttpClient().newBuilder()
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.connectTimeout(30, TimeUnit.SECONDS)
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.pingInterval(5, TimeUnit.SECONDS)//websocket轮训间隔(单位:秒)
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.readTimeout(300, TimeUnit.SECONDS)//读取超时(单位:秒)
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.writeTimeout(300, TimeUnit.SECONDS)//写入超时(单位:秒)
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.build();
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MediaType mediaType = MediaType.parse("application/json");
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Map<String, Object> content = Maps.newHashMap();
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//范围，范围越大，速度越慢。现在调试阶段可以设为10，也就是从10套中选最好的5套。
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content.put("max_outfits", 5);
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content.put("is_best", Boolean.TRUE);
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//输出得分最高的时装的套数（topk < range
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content.put("topk", 1);
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//需要搭配的衣服,数组
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//去重
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List<GenerateCollocationQueryDTO> queryAfter = CollectionUtil.emptyIfNull(query).stream().collect(Collectors.collectingAndThen(
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Collectors.toCollection(()->new TreeSet<>(Comparator.comparing(GenerateCollocationQueryDTO::getItem_id))),ArrayList::new));
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content.put("query", queryAfter);
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//java数据库中存在的商品
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content.put("database", dataBaseMap);
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RequestBody body = RequestBody.create(mediaType, JSON.toJSONString(content));
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Request request = new Request.Builder()
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.url(accessPythonIp + ":10201/mixi/api/v1.0/generate")
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.method("POST", body)
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.addHeader("Authorization", "Basic YWlkbGFiOjEyMw==")
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.addHeader("Content-Type", "application/json")
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.build();
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Response response = null;
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String bodyStr = null;
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try {
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log.info("获取python推荐搭配请求入参content###{}", JSON.toJSONString(content));
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response = client.newCall(request).execute();
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bodyStr = response.body().string();
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} catch (IOException ioException) {
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log.error("PythonService##attributeRecognition异常###{}", ExceptionUtil.getThrowableList(ioException));
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}
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log.info("识获取python推荐搭配请求结果###{}", bodyStr.trim());
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//去除限流
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AccessLimitUtils.validateOut("generateCollocation");
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if (Objects.isNull(response)) {
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log.error("PythonService##generateCollocation异常###{}", "response or body is empty!");
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throw new BusinessException("Generate Collocation exception!");
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}
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JSONObject jsonObject = JSON.parseObject(JSON.toJSONString(response));
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Boolean result = jsonObject.getBoolean("successful");
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if (result) {
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List<GenerateCollocationOutVO> collocationOutList = JSON.parseArray(bodyStr.trim(),GenerateCollocationOutVO.class);
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return collocationOutList;
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}
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log.info("获取python推荐搭配请求异常###{}", jsonObject);
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//生成失败
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throw new BusinessException("Generate Collocation exception!");
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}
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public List<GenerateCollocationOutVO> generateCollocationNew(
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List<GenerateCollocationQueryNewDTO> query, List<GenerateCollocationQueryNewDTO> dataBaseMap) {
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//限流校验
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AccessLimitUtils.validate("generateCollocation", 20);
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OkHttpClient client = new OkHttpClient().newBuilder()
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.connectTimeout(30, TimeUnit.SECONDS)
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.pingInterval(5, TimeUnit.SECONDS)//websocket轮训间隔(单位:秒)
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.readTimeout(300, TimeUnit.SECONDS)//读取超时(单位:秒)
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.writeTimeout(300, TimeUnit.SECONDS)//写入超时(单位:秒)
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.build();
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MediaType mediaType = MediaType.parse("application/json");
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Map<String, Object> content = Maps.newHashMap();
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//范围，范围越大，速度越慢。现在调试阶段可以设为10，也就是从10套中选最好的5套。
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content.put("max_outfits", 10);
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content.put("is_best", Boolean.TRUE);
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//输出得分最高的时装的套数（topk < range
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content.put("topk", 5);
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//需要搭配的衣服,数组
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//去重
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// List<GenerateCollocationQueryDTO> queryAfter = CollectionUtil.emptyIfNull(query).stream().collect(Collectors.collectingAndThen(
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// Collectors.toCollection(()->new TreeSet<>(Comparator.comparing(GenerateCollocationQueryDTO::getItem_id))),ArrayList::new));
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content.put("query", query);
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//java数据库中存在的商品
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content.put("database", dataBaseMap);
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RequestBody body = RequestBody.create(mediaType, JSON.toJSONString(content));
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Request request = new Request.Builder()
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.url(accessPythonIp + ":9993/api/outfit_matcheroutfit_matcher")
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.method("POST", body)
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.addHeader("Authorization", "Basic YWlkbGFiOjEyMw==")
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.addHeader("Content-Type", "application/json")
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.build();
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Response response = null;
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String bodyStr = null;
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try {
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log.info("获取python推荐搭配请求入参content###{}", JSON.toJSONString(content));
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response = client.newCall(request).execute();
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bodyStr = response.body().string();
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} catch (IOException ioException) {
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log.error("PythonService##attributeRecognition异常###{}", ExceptionUtil.getThrowableList(ioException));
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}
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log.info("识获取python推荐搭配请求结果###{}", bodyStr.trim());
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//去除限流
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AccessLimitUtils.validateOut("generateCollocation");
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if (Objects.isNull(response)) {
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log.error("PythonService##generateCollocation异常###{}", "response or body is empty!");
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throw new BusinessException("Generate Collocation exception!");
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}
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JSONObject jsonObject = JSON.parseObject(JSON.toJSONString(response));
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Boolean result = jsonObject.getBoolean("successful");
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if (result) {
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System.out.println(bodyStr.trim());
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// JSONObject jsonObject1 = JSONObject.parseObject(bodyStr.trim());
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List<GenerateCollocationOutVO> collocationOutList = processJson(bodyStr.trim());
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return collocationOutList;
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}
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log.info("获取python推荐搭配请求异常###{}", jsonObject);
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//生成失败
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throw new BusinessException("Generate Collocation exception!");
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}
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public static List<GenerateCollocationOutVO> processJson(String json) {
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List<GenerateCollocationOutVO> resultList = new ArrayList<>();
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JSONObject jsonObject = JSON.parseObject(json);
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if (jsonObject.containsKey("data")) {
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JSONArray dataArray = jsonObject.getJSONArray("data");
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for (int i = 0; i < dataArray.size(); i++) {
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JSONObject dataObject = dataArray.getJSONObject(i);
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if (dataObject.containsKey("outfits") && dataObject.containsKey("scores")) {
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JSONArray outfitsArray = dataObject.getJSONArray("outfits");
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JSONArray scoresArray = dataObject.getJSONArray("scores");
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List<List<GenerateCollocationQueryNewDTO>> outfitsList = new ArrayList<>();
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for (int j = 0; j < outfitsArray.size(); j++) {
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JSONArray innerArray = outfitsArray.getJSONArray(j);
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List<GenerateCollocationQueryNewDTO> innerList = new ArrayList<>();
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for (int k = 0; k < innerArray.size(); k++) {
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JSONObject itemObject = innerArray.getJSONObject(k);
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GenerateCollocationQueryNewDTO item = new GenerateCollocationQueryNewDTO();
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item.setItem_name(itemObject.getString("item_name"));
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item.setSemantic_category(itemObject.getString("semantic_category"));
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item.setImage_path(itemObject.getString("image_path"));
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innerList.add(item);
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}
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outfitsList.add(innerList);
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}
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List<Double> scoresList = new ArrayList<>();
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for (int j = 0; j < scoresArray.size(); j++) {
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scoresList.add(scoresArray.getDouble(j));
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}
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GenerateCollocationOutVO vo = new GenerateCollocationOutVO();
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vo.setOutfits(outfitsList);
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vo.setScores(scoresList);
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resultList.add(vo);
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}
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}
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}
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return resultList;
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}
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/**
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* 颜色或者相似度搭配,或者主色提取(同一个接口)
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*
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* @param query
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* @param dataBaseMap
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* @return
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*/
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public Map<String,List<String>> similarityRecognition(String mode, List<GenerateCollocationQueryDTO> query
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, Map<String, GenerateCollocationDataBaseDTO> dataBaseMap,List<AppProductColorExtractVO> productRgbList) {
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//限流校验
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AccessLimitUtils.validate("similarityRecognition", 20);
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OkHttpClient client = new OkHttpClient().newBuilder()
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.connectTimeout(30, TimeUnit.SECONDS)
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.pingInterval(5, TimeUnit.SECONDS)//websocket轮训间隔(单位:秒)
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||
.readTimeout(300, TimeUnit.SECONDS)//读取超时(单位:秒)
|
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.writeTimeout(300, TimeUnit.SECONDS)//写入超时(单位:秒)
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.build();
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MediaType mediaType = MediaType.parse("application/json");
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Map<String, Object> content = Maps.newHashMap();
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//color_feature和hash_feature。分别表示进行颜色匹配和相似度匹配。
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content.put("mode", mode);
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//颜色识别
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if("color_feature".equals(mode)){
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List<List<Integer>> rgbList = productRgbList.stream()
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.map(rgb-> Arrays.asList(Integer.valueOf(rgb.getR()),
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Integer.valueOf(rgb.getG()),Integer.valueOf(rgb.getB()))).collect(Collectors.toList());
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List<Map<String,List<List<Integer>>>> rgbArgList = Lists.newArrayList();
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Map<String,List<List<Integer>>> map = Maps.newHashMap();
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map.put("RGB",rgbList);
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rgbArgList.add(map);
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//相似度识别
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content.put("query", rgbArgList);
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}else{
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//去重需要搭配的衣服,数组
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List<GenerateCollocationQueryDTO> queryAfter = CollectionUtil.emptyIfNull(query).stream().collect(Collectors.collectingAndThen(
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Collectors.toCollection(()->new TreeSet<>(Comparator.comparing(GenerateCollocationQueryDTO::getItem_id))),ArrayList::new));
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content.put("query", queryAfter);
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}
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//输出匹配得分最高的图片（topk < database）,暂定5
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content.put("topk", 5);
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//java数据库中存在的商品
|
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content.put("database", dataBaseMap);
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RequestBody body = RequestBody.create(mediaType, JSON.toJSONString(content));
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Request request = new Request.Builder()
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.url(accessPythonIp + ":10202/mixi/api/v1.0/retrieval")
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.method("POST", body)
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.addHeader("Authorization", "Basic YWlkbGFiOjEyMw==")
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.addHeader("Content-Type", "application/json")
|
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.build();
|
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Response response = null;
|
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String bodyStr = null;
|
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try {
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log.info("获取python颜色或者相似度搭配请求入参content###{}", JSON.toJSONString(content));
|
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response = client.newCall(request).execute();
|
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bodyStr = response.body().string();
|
||
} catch (IOException ioException) {
|
||
log.error("PythonService##similarityRecognition异常###{}", ExceptionUtil.getThrowableList(ioException));
|
||
}
|
||
log.info("识获取python颜色或者相似度搭配请求结果###{}", bodyStr.trim());
|
||
//去除限流
|
||
AccessLimitUtils.validateOut("similarityRecognition");
|
||
if (Objects.isNull(response)) {
|
||
log.error("PythonService##similarityRecognition异常###{}", "response or body is empty!");
|
||
throw new BusinessException("Generate Collocation exception!");
|
||
}
|
||
JSONObject jsonObject = JSON.parseObject(JSON.toJSONString(response));
|
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Boolean result = jsonObject.getBoolean("successful");
|
||
if (result) {
|
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JSONArray jsonArray = JSON.parseArray(bodyStr.trim());
|
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return resolveMap(jsonArray,mode);
|
||
}
|
||
log.info("获取python颜色或者相似度搭配请求异常###{}", jsonObject);
|
||
//生成失败
|
||
throw new BusinessException("Similarity Recognition Exception!");
|
||
}
|
||
private static Map<String,List<String>> resolveMap(JSONArray jsonArray,String mode ){
|
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Map<String,List<String>> returnMap = Maps.newHashMap();
|
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for (int i = 0; i < jsonArray.size(); i++) {
|
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JSONObject jsonObject = jsonArray.getJSONObject(i);
|
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String queryId ="RGB";
|
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if("hash_feature".equals(mode)){
|
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queryId = jsonObject.getJSONObject("query").getString("item_id");
|
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}
|
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String retrievalJSONString = jsonObject.getJSONObject("retrieval").toJSONString();
|
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Map<String,Map<String,Object>> resultValue = JSON.parseObject(retrievalJSONString,Map.class);
|
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List<String> collationProductIdList = Lists.newArrayList(resultValue.keySet());
|
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returnMap.put(queryId,collationProductIdList);
|
||
}
|
||
return returnMap;
|
||
}
|
||
/**
|
||
* 主色提取(同一个接口)
|
||
*
|
||
* @param mode
|
||
* @param path
|
||
* @param isHsv 1返回hsv值 0返回rgb值
|
||
* @return
|
||
*/
|
||
public List<List<String>> colorExtract(String mode,String path,Integer isHsv) {
|
||
//限流校验
|
||
AccessLimitUtils.validate("colorExtract", 20);
|
||
OkHttpClient client = new OkHttpClient().newBuilder()
|
||
.connectTimeout(30, TimeUnit.SECONDS)
|
||
.pingInterval(5, TimeUnit.SECONDS)//websocket轮训间隔(单位:秒)
|
||
.readTimeout(300, TimeUnit.SECONDS)//读取超时(单位:秒)
|
||
.writeTimeout(300, TimeUnit.SECONDS)//写入超时(单位:秒)
|
||
.build();
|
||
MediaType mediaType = MediaType.parse("application/json");
|
||
Map<String, Object> content = Maps.newHashMap();
|
||
//color_feature和hash_feature。分别表示进行颜色匹配和相似度匹配。
|
||
content.put("mode", mode);
|
||
//表示提取主色的数量（最小2，最大10）暂定5
|
||
content.put("color_num", 5);
|
||
content.put("return_hsv", isHsv);
|
||
//衣服的绝对路径或url（http开头）
|
||
content.put("path",path);
|
||
RequestBody body = RequestBody.create(mediaType, JSON.toJSONString(content));
|
||
Request request = new Request.Builder()
|
||
.url(accessPythonIp + ":10202/mixi/api/v1.0/retrieval")
|
||
.method("POST", body)
|
||
.addHeader("Authorization", "Basic YWlkbGFiOjEyMw==")
|
||
.addHeader("Content-Type", "application/json")
|
||
.build();
|
||
Response response = null;
|
||
String bodyStr = null;
|
||
try {
|
||
log.info("获取python主色提取请求入参content###{}", JSON.toJSONString(content));
|
||
response = client.newCall(request).execute();
|
||
bodyStr = response.body().string();
|
||
} catch (IOException ioException) {
|
||
log.error("PythonService##colorExtract异常###{}", ExceptionUtil.getThrowableList(ioException));
|
||
}
|
||
log.info("识获取python主色提取请求结果###{}", bodyStr.trim());
|
||
//去除限流
|
||
AccessLimitUtils.validateOut("colorExtract");
|
||
if (Objects.isNull(response)) {
|
||
log.error("PythonService##colorExtract异常###{}", "response or body is empty!");
|
||
throw new BusinessException("Color Extract exception!");
|
||
}
|
||
JSONObject jsonObject = JSON.parseObject(JSON.toJSONString(response));
|
||
Boolean result = jsonObject.getBoolean("successful");
|
||
if (result) {
|
||
JSONArray jsonArray = JSON.parseArray(bodyStr.trim());
|
||
return resolveColorExtractList(jsonArray);
|
||
}
|
||
log.info("获取python主色提取请求异常###{}", jsonObject);
|
||
//生成失败
|
||
throw new BusinessException("Color Extract Exception!");
|
||
}
|
||
private static List<List<String> > resolveColorExtractList(JSONArray jsonArray ){
|
||
List<List<String>> returnList = Lists.newArrayList();
|
||
List<String> innerList= Lists.newArrayList();
|
||
for (int i = 0; i < jsonArray.size(); i++) {
|
||
String rgb = jsonArray.getString(i);
|
||
innerList.add(rgb);
|
||
}
|
||
returnList.add(innerList);
|
||
return returnList;
|
||
}
|
||
/**
|
||
*
|
||
* rgb转hsv
|
||
*
|
||
* @param r
|
||
* @param g
|
||
* @param b
|
||
* @return
|
||
*/
|
||
public List<Integer> rgb2hsv(Integer r ,Integer g,Integer b) {
|
||
//限流校验
|
||
OkHttpClient client = new OkHttpClient().newBuilder()
|
||
.connectTimeout(30, TimeUnit.SECONDS)
|
||
.pingInterval(5, TimeUnit.SECONDS)//websocket轮训间隔(单位:秒)
|
||
.readTimeout(300, TimeUnit.SECONDS)//读取超时(单位:秒)
|
||
.writeTimeout(300, TimeUnit.SECONDS)//写入超时(单位:秒)
|
||
.build();
|
||
MediaType mediaType = MediaType.parse("application/json");
|
||
Map<String, Object> content = Maps.newHashMap();
|
||
//color_feature和hash_feature。分别表示进行颜色匹配和相似度匹配。
|
||
content.put("mode", "rgb2hsv");
|
||
//表示提取主色的数量（最小2，最大10）暂定5
|
||
content.put("rgb", Arrays.asList(r,g,b));
|
||
RequestBody body = RequestBody.create(mediaType, JSON.toJSONString(content));
|
||
Request request = new Request.Builder()
|
||
.url(accessPythonIp + ":10202/mixi/api/v1.0/retrieval")
|
||
.method("POST", body)
|
||
.addHeader("Authorization", "Basic YWlkbGFiOjEyMw==")
|
||
.addHeader("Content-Type", "application/json")
|
||
.build();
|
||
Response response = null;
|
||
String bodyStr = null;
|
||
try {
|
||
log.info("获取python rgb转hsv请求入参content###{}", JSON.toJSONString(content));
|
||
response = client.newCall(request).execute();
|
||
bodyStr = response.body().string();
|
||
} catch (IOException ioException) {
|
||
log.error("PythonService##rgb2hsv###{}", ExceptionUtil.getThrowableList(ioException));
|
||
}
|
||
log.info("识获取python主色 rgb转hsv请求结果###{}", bodyStr.trim());
|
||
if (Objects.isNull(response)) {
|
||
log.error("PythonService##rgb2hsv异常###{}", "response or body is empty!");
|
||
throw new BusinessException("rgb2hsv exception!");
|
||
}
|
||
JSONObject jsonObject = JSON.parseObject(JSON.toJSONString(response));
|
||
Boolean result = jsonObject.getBoolean("successful");
|
||
if (result) {
|
||
List<Integer> hsvList = JSON.parseArray(bodyStr.trim(),Integer.class);
|
||
return hsvList;
|
||
}
|
||
log.info("获取python rgb转hsv请求异常###{}", jsonObject);
|
||
//生成失败
|
||
throw new BusinessException("rgb2hsv Exception!");
|
||
}
|
||
|
||
public static void main(String[] args) {
|
||
// String res = "{\"1\":{\"Item\":\"top\",\"Top_length\":[\"Regular\"],\"Top_type\":[\"Sweater\"]},\"2\":{\"Item\":\"top\",\"Top_length\":[\"Regular\"],\"Top_type\":[\"Sweater\"]}}";
|
||
// Map<String,Map<String,Object>> resultValue = JSON.parseObject(res,Map.class);
|
||
// System.out.println(resultValue);
|
||
|
||
// String bodyStr = "{\n" +
|
||
// " \"mode\": \"color_extract\",\n" +
|
||
// " \"color_num\": 5,\n" +
|
||
// " \"path\": \"http://18.167.251.121:5568/download/202303/userFile/product/3/61b20df8-dabe-4eca-90a1-8dc804b1eddbrendering_113581965_source_99619122.jpg\"\n" +
|
||
// "}";
|
||
//
|
||
// List<GenerateCollocationOutVO> collocationOutList = JSON.parseArray(bodyStr.trim(),GenerateCollocationOutVO.class);
|
||
// System.out.println(collocationOutList);
|
||
//
|
||
// JSONArray jsonArray = JSON.parseArray(bodyStr.trim());
|
||
// System.out.println(resolveColorExtractList(jsonArray));
|
||
|
||
|
||
}
|
||
|
||
public List<TProduct> similarityMatch(String pictureUrl) {
|
||
//限流校验
|
||
AccessLimitUtils.validate("similarityMatch", 20);
|
||
OkHttpClient client = new OkHttpClient().newBuilder()
|
||
.connectTimeout(30, TimeUnit.SECONDS)
|
||
.pingInterval(5, TimeUnit.SECONDS)//websocket轮训间隔(单位:秒)
|
||
.readTimeout(300, TimeUnit.SECONDS)//读取超时(单位:秒)
|
||
.writeTimeout(300, TimeUnit.SECONDS)//写入超时(单位:秒)
|
||
.build();
|
||
MediaType mediaType = MediaType.parse("application/json");
|
||
Map<String, Object> content = Maps.newHashMap();
|
||
content.put("image_path", pictureUrl);
|
||
content.put("result_number", 5);
|
||
RequestBody body = RequestBody.create(mediaType, JSON.toJSONString(content));
|
||
Request request = new Request.Builder()
|
||
.url(accessPythonIp + ":9993/api/similar_matchsimilar_match")
|
||
.method("POST", body)
|
||
.addHeader("Authorization", "Basic YWlkbGFiOjEyMw==")
|
||
.addHeader("Content-Type", "application/json")
|
||
.build();
|
||
Response response = null;
|
||
String bodyStr = null;
|
||
try {
|
||
log.info("获取python获取相似商品请求入参content###{}", JSON.toJSONString(content));
|
||
response = client.newCall(request).execute();
|
||
bodyStr = response.body().string();
|
||
} catch (IOException ioException) {
|
||
log.error("PythonService##similarityMatch异常###{}", ExceptionUtil.getThrowableList(ioException));
|
||
}
|
||
log.info("识获取python获取相似商品请求结果###{}", bodyStr.trim());
|
||
//去除限流
|
||
AccessLimitUtils.validateOut("similarityMatch");
|
||
if (Objects.isNull(response)) {
|
||
log.error("PythonService##similarityMatch异常###{}", "response or body is empty!");
|
||
throw new BusinessException("SimilarityMatch exception.");
|
||
}
|
||
JSONObject jsonObject = JSON.parseObject(JSON.toJSONString(response));
|
||
Boolean result = jsonObject.getBoolean("successful");
|
||
if (result) {
|
||
JSONObject parseObject = JSON.parseObject(bodyStr.trim());
|
||
return similarityMatchToList(parseObject);
|
||
}
|
||
log.info("获取python获取相似商品请求异常###{}", jsonObject);
|
||
//生成失败
|
||
throw new BusinessException("SimilarityMatch exception.");
|
||
}
|
||
|
||
@Resource
|
||
private TProductMapper tProductMapper;
|
||
|
||
private List<TProduct> similarityMatchToList(JSONObject parseObject) {
|
||
List<TProduct> productList = new ArrayList<>();
|
||
JSONArray data = parseObject.getJSONArray("data");
|
||
for (int i = 0; i < data.size(); i++) {
|
||
JSONObject jsonObject = data.getJSONObject(i);
|
||
String imagePath = jsonObject.getString("image_path");
|
||
String itemName = jsonObject.getString("item_name");
|
||
QueryWrapper<TProduct> qw = new QueryWrapper<>();
|
||
qw.lambda().eq(TProduct::getPictureUrl, imagePath);
|
||
qw.lambda().eq(TProduct::getPictureName, itemName);
|
||
List<TProduct> productList1 = tProductMapper.selectList(qw);
|
||
if (CollectionUtil.isNotEmpty(productList1)) {
|
||
productList.add(productList1.get(0));
|
||
}
|
||
}
|
||
return productList;
|
||
}
|
||
|
||
public JSONArray getAIRecommend(QeFilling qeFilling) {
|
||
//限流校验
|
||
// AccessLimitUtils.validate("similarityMatch", 20);
|
||
OkHttpClient client = new OkHttpClient().newBuilder()
|
||
.connectTimeout(300, TimeUnit.SECONDS)
|
||
.pingInterval(5, TimeUnit.SECONDS)//websocket轮训间隔(单位:秒)
|
||
.readTimeout(300, TimeUnit.SECONDS)//读取超时(单位:秒)
|
||
.writeTimeout(300, TimeUnit.SECONDS)//写入超时(单位:秒)
|
||
.build();
|
||
MediaType mediaType = MediaType.parse("application/json");
|
||
Map<String, Object> content = Maps.newHashMap();
|
||
content.put("user_id", qeFilling.getPhoneNum());
|
||
// content.put("type", qeFilling.getType());
|
||
// content.put("q1", qeFilling.getQ1());
|
||
// content.put("q2", qeFilling.getQ2());
|
||
// content.put("q3", qeFilling.getQ3());
|
||
// content.put("q4", qeFilling.getQ4());
|
||
// content.put("q5", qeFilling.getQ5());
|
||
// content.put("q6", qeFilling.getQ6());
|
||
// content.put("q7", qeFilling.getQ7());
|
||
// content.put("q8", qeFilling.getQ8());
|
||
|
||
RequestBody body = RequestBody.create(mediaType, JSON.toJSONString(content));
|
||
Request request = new Request.Builder()
|
||
// .url(accessPythonIp + ":9993/api/similar_matchsimilar_match")
|
||
.url("http://127.0.0.1:5001/chat")
|
||
.method("POST", body)
|
||
// .addHeader("Authorization", "Basic YWlkbGFiOjEyMw==")
|
||
.addHeader("Content-Type", "application/json")
|
||
.build();
|
||
Response response = null;
|
||
String bodyStr = null;
|
||
try {
|
||
log.info("获取python获取AI推荐请求入参content###{}", JSON.toJSONString(content));
|
||
response = client.newCall(request).execute();
|
||
bodyStr = response.body().string();
|
||
} catch (IOException ioException) {
|
||
log.error("PythonService##similarityMatch异常###{}", ExceptionUtil.getThrowableList(ioException));
|
||
}
|
||
log.info("识获取python获取AI推荐请求结果###{}", bodyStr.trim());
|
||
//去除限流
|
||
AccessLimitUtils.validateOut("similarityMatch");
|
||
if (Objects.isNull(response)) {
|
||
log.error("PythonService##similarityMatch异常###{}", "response or body is empty!");
|
||
throw new BusinessException("SimilarityMatch exception.");
|
||
}
|
||
JSONObject jsonObject = JSON.parseObject(JSON.toJSONString(response));
|
||
Boolean result = jsonObject.getBoolean("successful");
|
||
if (result) {
|
||
JSONArray parseArray = JSON.parseArray(bodyStr.trim());
|
||
return parseArray;
|
||
}
|
||
log.info("获取python获取AI推荐请求异常###{}", jsonObject);
|
||
//生成失败
|
||
throw new BusinessException("AI recommendation exception.");
|
||
}
|
||
}
|