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feat(face): 引入人脸识别指标记录与搜索结果合并功能
- 新增 FaceMetricsRecorder 类用于记录人脸识别、自定义匹配及低阈值检测次数 - 新增 SearchResultMerger 类用于合并多个人脸搜索结果，支持并集与交集模式- 在 FaceServiceImpl 中引入 metricsRecorder 和 resultMerger 辅助类 - 替换原有的 Redis 操作代码为 FaceMetricsRecorder 的方法调用- 将搜索结果合并逻辑从 FaceServiceImpl 提取至 SearchResultMerger- 新增策略模式相关类：RematchContext、RematchModeStrategy 接口及四种实现 - 使用策略工厂 Rematch
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package com.ycwl.basic.service.pc.helper;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.data.redis.core.RedisTemplate;
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import org.springframework.stereotype.Component;
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import java.util.concurrent.TimeUnit;
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import static com.ycwl.basic.constant.FaceConstant.*;
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/**
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* 人脸识别指标记录器
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* 负责记录人脸识别相关的计数指标到Redis
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*
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* @author longbinbin
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* @date 2025-01-31
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*/
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@Slf4j
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@Component
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public class FaceMetricsRecorder {
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@Autowired
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private RedisTemplate<String, String> redisTemplate;
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/**
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* 记录人脸识别次数到Redis
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* 设置2天过期时间
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*
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* @param faceId 人脸ID
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*/
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public void recordRecognitionCount(Long faceId) {
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if (faceId == null) {
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return;
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}
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try {
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String redisKey = FACE_RECOGNITION_COUNT_PFX + faceId;
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// 使用Redis原子操作INCR增加计数
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Long count = redisTemplate.opsForValue().increment(redisKey);
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// 设置2天过期时间(48小时)
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redisTemplate.expire(redisKey, 2, TimeUnit.DAYS);
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log.debug("人脸识别计数更新:faceId={}, count={}", faceId, count);
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} catch (Exception e) {
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// 计数失败不应影响主要业务逻辑,只记录错误日志
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log.error("记录人脸识别次数失败:faceId={}", faceId, e);
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}
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}
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/**
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* 记录自定义人脸匹配次数到Redis
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* 设置2天过期时间
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*
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* @param faceId 人脸ID
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*/
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public void recordCustomMatchCount(Long faceId) {
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if (faceId == null) {
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return;
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}
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try {
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String redisKey = FACE_CUSTOM_MATCH_COUNT_PFX + faceId;
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Long count = redisTemplate.opsForValue().increment(redisKey);
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redisTemplate.expire(redisKey, 2, TimeUnit.DAYS);
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log.debug("自定义人脸匹配计数更新:faceId={}, count={}", faceId, count);
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} catch (Exception e) {
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log.error("记录自定义人脸匹配次数失败:faceId={}", faceId, e);
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}
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}
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/**
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* 记录低阈值检测的人脸ID到Redis
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* 设置2天过期时间
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*
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* @param faceId 人脸ID
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*/
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public void recordLowThreshold(Long faceId) {
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if (faceId == null) {
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return;
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}
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try {
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String redisKey = FACE_LOW_THRESHOLD_PFX + faceId;
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// 设置标记,表示该人脸ID触发了低阈值检测
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redisTemplate.opsForValue().set(redisKey, "1", 2, TimeUnit.DAYS);
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log.debug("记录低阈值检测人脸:faceId={}", faceId);
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} catch (Exception e) {
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// 记录失败不应影响主要业务逻辑,只记录错误日志
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log.error("记录低阈值检测人脸失败:faceId={}", faceId, e);
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}
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}
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/**
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* 获取人脸识别次数
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*
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* @param faceId 人脸ID
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* @return 识别次数
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*/
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public long getRecognitionCount(Long faceId) {
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if (faceId == null) {
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return 0L;
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}
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try {
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String countKey = FACE_RECOGNITION_COUNT_PFX + faceId;
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String countStr = redisTemplate.opsForValue().get(countKey);
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if (countStr != null) {
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return Long.parseLong(countStr);
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}
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} catch (Exception e) {
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log.warn("获取识别次数失败:faceId={}", faceId, e);
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}
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return 0L;
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}
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/**
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* 获取自定义匹配次数
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*
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* @param faceId 人脸ID
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* @return 自定义匹配次数
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*/
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public long getCustomMatchCount(Long faceId) {
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if (faceId == null) {
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return 0L;
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}
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try {
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String customMatchKey = FACE_CUSTOM_MATCH_COUNT_PFX + faceId;
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String customMatchCountStr = redisTemplate.opsForValue().get(customMatchKey);
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if (customMatchCountStr != null) {
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return Long.parseLong(customMatchCountStr);
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}
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} catch (Exception e) {
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log.warn("获取自定义匹配次数失败:faceId={}", faceId, e);
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}
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return 0L;
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}
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/**
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* 检查是否触发过低阈值检测
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*
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* @param faceId 人脸ID
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* @return 是否触发过低阈值检测
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*/
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public boolean hasLowThreshold(Long faceId) {
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if (faceId == null) {
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return false;
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}
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try {
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String lowThresholdKey = FACE_LOW_THRESHOLD_PFX + faceId;
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return Boolean.TRUE.equals(redisTemplate.hasKey(lowThresholdKey));
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} catch (Exception e) {
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log.warn("检查低阈值状态失败:faceId={}", faceId, e);
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return false;
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}
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}
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}
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@@ -0,0 +1,154 @@
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package com.ycwl.basic.service.pc.helper;
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import com.ycwl.basic.model.task.resp.SearchFaceRespVo;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.stereotype.Component;
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import java.util.*;
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import java.util.stream.Collectors;
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/**
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* 搜索结果合并器
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* 负责合并多个人脸搜索结果
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*
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* @author longbinbin
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* @date 2025-01-31
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*/
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@Slf4j
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@Component
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public class SearchResultMerger {
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/**
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* 合并多个搜索结果(默认使用并集模式)
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*
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* @param searchResults 搜索结果列表
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* @return 合并后的结果
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*/
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public SearchFaceRespVo merge(List<SearchFaceRespVo> searchResults) {
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return merge(searchResults, 0);
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}
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/**
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* 合并多个搜索结果
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*
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* @param searchResults 搜索结果列表
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* @param mergeMode 合并模式:0-并集,1-交集
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* @return 合并后的结果
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*/
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public SearchFaceRespVo merge(List<SearchFaceRespVo> searchResults, Integer mergeMode) {
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SearchFaceRespVo mergedResult = new SearchFaceRespVo();
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if (searchResults == null || searchResults.isEmpty()) {
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return mergedResult;
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}
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List<String> allSearchJsons = new ArrayList<>();
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float maxScore = 0f;
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float maxFirstMatchRate = 0f;
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boolean hasLowThreshold = false;
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// 收集基础信息
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for (SearchFaceRespVo result : searchResults) {
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if (result.getSearchResultJson() != null) {
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allSearchJsons.add(result.getSearchResultJson());
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}
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if (result.getScore() > maxScore) {
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maxScore = result.getScore();
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}
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if (result.getFirstMatchRate() > maxFirstMatchRate) {
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maxFirstMatchRate = result.getFirstMatchRate();
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}
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if (result.isLowThreshold()) {
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hasLowThreshold = true;
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}
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}
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// 根据合并模式处理样本ID
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List<Long> finalSampleIds;
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if (Integer.valueOf(1).equals(mergeMode)) {
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// 模式1:交集 - 只保留所有搜索结果中都出现的样本ID
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finalSampleIds = computeIntersection(searchResults);
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log.debug("使用交集模式合并搜索结果,交集样本数: {}", finalSampleIds.size());
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} else {
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// 模式0:并集(默认) - 收集所有样本ID并去重
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Set<Long> allSampleIds = new LinkedHashSet<>();
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for (SearchFaceRespVo result : searchResults) {
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if (result.getSampleListIds() != null) {
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allSampleIds.addAll(result.getSampleListIds());
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}
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}
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finalSampleIds = new ArrayList<>(allSampleIds);
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log.debug("使用并集模式合并搜索结果,并集样本数: {}", finalSampleIds.size());
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}
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mergedResult.setSampleListIds(finalSampleIds);
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mergedResult.setSearchResultJson(String.join("|", allSearchJsons));
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mergedResult.setScore(maxScore);
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mergedResult.setFirstMatchRate(maxFirstMatchRate);
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mergedResult.setLowThreshold(hasLowThreshold);
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log.debug("合并搜索结果完成,模式={}, 最终样本数: {}", mergeMode, finalSampleIds.size());
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return mergedResult;
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}
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/**
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* 计算多个搜索结果的交集
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* 返回在所有搜索结果中都出现的样本ID
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*
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* @param searchResults 搜索结果列表
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* @return 交集样本ID列表
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*/
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public List<Long> computeIntersection(List<SearchFaceRespVo> searchResults) {
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if (searchResults == null || searchResults.isEmpty()) {
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return new ArrayList<>();
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}
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// 过滤掉空结果
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List<List<Long>> validSampleLists = searchResults.stream()
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.filter(result -> result.getSampleListIds() != null && !result.getSampleListIds().isEmpty())
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.map(SearchFaceRespVo::getSampleListIds)
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.toList();
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if (validSampleLists.isEmpty()) {
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return new ArrayList<>();
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}
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// 如果只有一个有效结果,直接返回
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if (validSampleLists.size() == 1) {
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return new ArrayList<>(validSampleLists.getFirst());
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}
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// 计算交集:从第一个列表开始,保留在所有其他列表中都出现的ID
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Set<Long> intersection = new LinkedHashSet<>(validSampleLists.getFirst());
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for (int i = 1; i < validSampleLists.size(); i++) {
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intersection.retainAll(validSampleLists.get(i));
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}
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return new ArrayList<>(intersection);
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}
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/**
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* 创建直接结果(模式2:不搜索,直接使用用户选择的faceSampleIds)
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*
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* @param faceSampleIds 用户选择的人脸样本ID列表
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* @return 搜索结果对象
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*/
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public SearchFaceRespVo createDirectResult(List<Long> faceSampleIds) {
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SearchFaceRespVo result = new SearchFaceRespVo();
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// 直接使用用户选择的faceSampleIds作为结果
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result.setSampleListIds(new ArrayList<>(faceSampleIds));
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// 设置默认值
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result.setScore(1.0f);
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result.setFirstMatchRate(1.0f);
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result.setLowThreshold(false);
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result.setSearchResultJson("");
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log.debug("创建直接结果,样本数: {}", faceSampleIds.size());
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return result;
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}
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}
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