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/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);
             }