feat: 支持按算法独立配置置信度阈值

通过 ALGO_CONF_{ALGO_CODE} 环境变量为每个算法设置独立的 conf_threshold，
未配置的算法回退到全局 CONF_THRESHOLD。推理过程零改动，仅后处理过滤阶段
按 bind.algo_code 使用对应阈值。

当前配置：离岗=0.4（降低漏检），入侵=0.5（减少误报）。

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

config/settings.py

@@ -5,7 +5,7 @@
 
 import os
 from dataclasses import dataclass, field
-from typing import List, Optional
+from typing import Dict, List, Optional
 
 
 @dataclass
@@ -117,10 +117,17 @@ class InferenceConfig:
     input_width: int = 480
     input_height: int = 480
     batch_size: int = 1
-    conf_threshold: float = 0.4
-    nms_threshold: float = 0.45
+    conf_threshold: float = 0.45
+    nms_threshold: float = 0.5
     device_id: int = 0
     fp16_mode: bool = True
+    # 按算法类型覆盖置信度阈值，key=algo_code, value=threshold
+    # 未命中时回退到 conf_threshold
+    algo_conf_thresholds: Dict[str, float] = field(default_factory=dict)
+
+    def get_conf_threshold(self, algo_code: str) -> float:
+        """获取指定算法的置信度阈值，未配置则回退全局值"""
+        return self.algo_conf_thresholds.get(algo_code, self.conf_threshold)
 
 
 # ===================== Debug / Local Sync =====================
@@ -273,8 +280,9 @@ class Settings:
             input_width=int(os.getenv("INPUT_WIDTH", "480")),
             input_height=int(os.getenv("INPUT_HEIGHT", "480")),
             batch_size=int(os.getenv("BATCH_SIZE", "4")),
-            conf_threshold=float(os.getenv("CONF_THRESHOLD", "0.4")),
-            nms_threshold=float(os.getenv("NMS_THRESHOLD", "0.45")),
+            conf_threshold=float(os.getenv("CONF_THRESHOLD", "0.45")),
+            nms_threshold=float(os.getenv("NMS_THRESHOLD", "0.5")),
+            algo_conf_thresholds=self._parse_algo_conf_thresholds(),
         )
 
         self.config_sync_mode = os.getenv("CONFIG_SYNC_MODE", "LOCAL").upper()
@@ -297,6 +305,25 @@ class Settings:
         # 使用 COCO 类别名称
         self.class_names = COCO_CLASS_NAMES
     
+    @staticmethod
+    def _parse_algo_conf_thresholds() -> Dict[str, float]:
+        """解析 ALGO_CONF_* 环境变量，返回 {algo_code: threshold} 字典
+
+        环境变量命名规则: ALGO_CONF_{ALGO_CODE}，如:
+            ALGO_CONF_LEAVE_POST=0.35
+            ALGO_CONF_INTRUSION=0.55
+        """
+        prefix = "ALGO_CONF_"
+        result = {}
+        for key, value in os.environ.items():
+            if key.startswith(prefix) and value:
+                algo_code = key[len(prefix):].lower()
+                try:
+                    result[algo_code] = float(value)
+                except ValueError:
+                    pass
+        return result
+
     def _parse_working_hours(self) -> List[dict]:
         """解析工作时间配置"""
         working_hours_str = os.getenv("WORKING_HOURS", "")