fix: 修复10个关键bug提升系统稳定性和性能

1. YOLO11输出解析错误: 移除不存在的objectness行，正确使用class_scores.max()
2. CPU NMS逻辑错误: keep_mask同时标记保留和抑制框导致NMS失效，改用独立suppressed集合
3. 坐标映射缺失: _build_tracks中scale_info未使用，添加revert_boxes还原到ROI裁剪空间
4. batch=1限制: 恢复真正的动态batch推理(1~8)，BatchPreprocessor支持多图stack
5. 帧率控制缺失: _read_frame添加time.monotonic()间隔控制，按target_fps跳帧
6. 拉流推理耦合: 新增独立推理线程(InferenceWorker)，生产者-消费者模式解耦
7. 攒批形同虚设: 添加50ms攒批窗口+max_batch阈值，替代>=1立即处理
8. LeavePost双重等待: LEAVING确认后直接触发告警，不再进入OFF_DUTY二次等待
9. register_algorithm每帧调用: 添加_registered_keys缓存，O(1)快速路径跳过
10. GPU context线程安全: TensorRT infer()内部加锁，防止多线程CUDA context竞争

附带修复:
- reset_algorithm中未定义algorithm_type变量(NameError)
- update_roi_params中循环变量key覆盖外层key
- AlertInfo缺少bind_id字段(TypeError)
- _logger.log_alert在标准logger上不存在(AttributeError)
- AlarmStateMachine死锁(Lock改为RLock)
- ROICropper.create_mask坐标解析错误
- 更新测试用例适配新API

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

tests/test_preprocessor.py

@@ -130,41 +130,36 @@ class TestLetterboxPreprocessor(unittest.TestCase):
 
 class TestBatchPreprocessor(unittest.TestCase):
     """测试Batch预处理器"""
-    
+
     def test_preprocess_batch(self):
         """测试批次预处理"""
         from core.preprocessor import BatchPreprocessor
-        
+
         preprocessor = BatchPreprocessor(
             target_size=(480, 480),
-            max_batch_size=4,
             fp16_mode=True
         )
-        
+
         images = [
             np.zeros((640, 640, 3), dtype=np.uint8)
             for _ in range(2)
         ]
-        
+
         result, scale_info_list = preprocessor.preprocess_batch(images)
-        
+
         self.assertEqual(result.shape[0], 2)
         self.assertEqual(len(scale_info_list), 2)
-    
-    def test_memory_allocation(self):
-        """测试内存分配"""
+
+    def test_max_batch_size(self):
+        """测试最大batch大小"""
         from core.preprocessor import BatchPreprocessor
-        
+
         preprocessor = BatchPreprocessor(
             target_size=(480, 480),
-            max_batch_size=4,
             fp16_mode=True
         )
-        
-        mem = preprocessor.allocate_batch_memory(2)
-        
-        self.assertEqual(mem.shape[0], 2)
-        self.assertEqual(mem.dtype, np.float16)
+
+        self.assertEqual(preprocessor.max_batch_size, 8)
 
 
 class TestImagePreprocessor(unittest.TestCase):
@@ -200,12 +195,12 @@ class TestImagePreprocessor(unittest.TestCase):
     def test_get_statistics(self):
         """测试获取统计"""
         from core.preprocessor import ImagePreprocessor
-        
+
         preprocessor = ImagePreprocessor()
         stats = preprocessor.get_statistics()
-        
+
         self.assertIn("config", stats)
-        self.assertIn("memory", stats)
+        self.assertIn("batch_size", stats["config"])
 
 
 if __name__ == "__main__":