feat(face): 添加人脸识别重试功能并优化得分筛选逻辑

- 在FaceSampleController中新增retryFaceRecognition接口用于手动重试失败的人脸识别任务- 集成人脸识别Kafka服务，支持异步处理重试请求- 在FaceServiceImpl中增加从景区配置读取人脸得分阈值的功能
- 根据配置的得分阈值对人脸识别结果进行筛选，过滤低分样本
- 添加详细的日志记录和异常处理机制- 优化线程池使用，确保重试任务能够正确提交和执行

src/main/java/com/ycwl/basic/controller/pc/FaceSampleController.java

@@ -1,4 +1,5 @@
 package com.ycwl.basic.controller.pc;
+import com.ycwl.basic.integration.kafka.service.FaceProcessingKafkaService;
 
 import com.github.pagehelper.PageInfo;
 import com.ycwl.basic.model.pc.faceSample.entity.FaceSampleEntity;
@@ -15,13 +16,14 @@ import java.util.List;
  * @Author：longbinbin
  * @Date：2024/12/2 16:33
  */
-@Deprecated
 @RestController
 @RequestMapping("/api/faceSample/v1")
 // 人脸样本管理
 public class FaceSampleController {
     @Autowired
     private FaceSampleService FaceSampleService;
+    @Autowired(required = false)
+    private FaceProcessingKafkaService faceProcessingKafkaService;
 
     // 分页查询人脸样本
     @PostMapping("/page")
@@ -39,4 +41,25 @@ public class FaceSampleController {
         return FaceSampleService.getById(id);
     }
 
+    /**
+     * 重试失败的人脸识别
+     * 用于手动重试状态为-1的人脸样本
+     *
+     * @param id 人脸样本ID
+     * @return 重试结果
+     */
+    @PostMapping("/retry/{id}")
+    public ApiResponse<String> retryFaceRecognition(@PathVariable("id") Long id) {
+        if (faceProcessingKafkaService == null) {
+            return ApiResponse.fail("Kafka服务未启用,无法重试人脸识别");
+        }
+        
+        boolean success = faceProcessingKafkaService.retryFaceRecognition(id);
+        if (success) {
+            return ApiResponse.success("人脸识别重试任务已提交");
+        } else {
+            return ApiResponse.fail("提交重试任务失败,请检查人脸样本状态");
+        }
+    }
+
 }

src/main/java/com/ycwl/basic/integration/kafka/service/FaceProcessingKafkaService.java

@@ -191,4 +191,53 @@ public class FaceProcessingKafkaService {
             log.error("更新人脸样本状态失败, faceSampleId: {}", faceSampleId, e);
         }
     }
+
+    /**
+     * 重试失败的人脸识别
+     * 用于手动重试状态为-1的人脸样本
+     *
+     * @param faceSampleId 人脸样本ID
+     * @return 是否成功提交重试任务
+     */
+    public boolean retryFaceRecognition(Long faceSampleId) {
+        try {
+            // 查询人脸样本信息
+            FaceSampleEntity faceSample = faceSampleMapper.getEntity(faceSampleId);
+            if (faceSample == null) {
+                log.error("人脸样本不存在, faceSampleId: {}", faceSampleId);
+                return false;
+            }
+
+            // 检查状态是否为失败状态(-1)
+            if (faceSample.getStatus() != -1) {
+                log.warn("人脸样本状态不是失败状态, 无需重试, faceSampleId: {}, status: {}",
+                        faceSampleId, faceSample.getStatus());
+                return false;
+            }
+
+            // 构造人脸处理消息
+            FaceProcessingMessage message = FaceProcessingMessage.builder()
+                    .faceSampleId(faceSample.getId())
+                    .scenicId(faceSample.getScenicId())
+                    .deviceId(faceSample.getDeviceId())
+                    .faceUrl(faceSample.getFaceUrl())
+                    .shotTime(faceSample.getCreateAt())
+                    .createTime(new Date())
+                    .source("retry-manual")
+                    .build();
+
+            // 提交到线程池进行异步处理
+            faceRecognitionExecutor.execute(() -> processFaceRecognitionAsync(message));
+
+            log.info("人脸识别重试任务已提交, faceSampleId: {}, 活跃线程: {}, 队列大小: {}",
+                    faceSampleId, faceRecognitionExecutor.getActiveCount(),
+                    faceRecognitionExecutor.getQueue().size());
+
+            return true;
+
+        } catch (Exception e) {
+            log.error("提交人脸识别重试任务失败, faceSampleId: {}", faceSampleId, e);
+            return false;
+        }
+    }
 }

src/main/java/com/ycwl/basic/service/pc/impl/FaceServiceImpl.java

@@ -1341,12 +1341,32 @@ public class FaceServiceImpl implements FaceService {
             resultItems = Collections.emptyList();
         }
 
+        // 获取景区配置的得分阈值
+        Float scoreThreshold = null;
+        try {
+            ScenicConfigManager scenicConfig = scenicRepository.getScenicConfigManager(face.getScenicId());
+            if (scenicConfig != null) {
+                BigDecimal thresholdConfig = scenicConfig.getBigDecimal("face_select_score_threshold");
+                if (thresholdConfig != null) {
+                    // 配置值是0~100的小数，需要转换为0~1的阈值
+                    scoreThreshold = thresholdConfig.floatValue() / 100.0f;
+                }
+            }
+        } catch (Exception e) {
+            log.warn("获取景区人脸得分阈值配置失败, scenicId: {}, 将不进行得分筛选", face.getScenicId(), e);
+        }
+
         List<Long> persistedAcceptedIds = parseMatchSampleIds(face.getMatchSampleIds());
         LinkedHashSet<Long> sampleUniverse = new LinkedHashSet<>();
         Map<Long, SearchFaceResultItem> itemBySampleId = new LinkedHashMap<>();
         for (SearchFaceResultItem item : resultItems) {
             Long sampleId = parseLongSilently(item.getExtData());
             if (sampleId != null) {
+                // 根据得分阈值筛选样本
+                if (scoreThreshold != null && item.getScore() != null && item.getScore() < scoreThreshold) {
+                    // 得分低于阈值，跳过此样本
+                    continue;
+                }
                 sampleUniverse.add(sampleId);
                 itemBySampleId.putIfAbsent(sampleId, item);
             }