对frame增加try以接住异常
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@@ -12,6 +12,8 @@ from algorithm.checkpoint.npu_yolo_onnx_person_car_phone import YOLOv8_ONNX
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from algorithm.checkpoint.npu_yolo_pose_onnx import YOLOv8_Pose_ONNX # Pose 专用模型
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from yolox.tracker.byte_tracker import BYTETracker
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from utils.logger import get_logger
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logger = get_logger(__name__)
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# ========================= 配置区 =========================
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# Kadian 模型路径与ROI（可根据实际情况修改）
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@@ -114,15 +116,15 @@ class KadianDetector:
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self.frame_buffer_limit_person = int(self.TIME_TOLERANCE_PERSON * self.fps)
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self.frame_buffer_limit_car = int(self.TIME_TOLERANCE_CAR * self.fps)
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print(f"\n超参数设置:")
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print(f" FPS: {self.fps:.2f}")
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print(f" 判定 'Only One' / 'Nobody' 需连续: {self.frame_thresh_one} 帧")
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print(f" 判定 'Trunk Checked' 需累计检测: {self.frame_thresh_trunk_valid} 帧")
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print(f" 判定 'Phone Detected' 需累计检测: {self.frame_thresh_phone} 帧")
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print(f" 手机丢失缓冲帧数: {self.frame_buffer_phone} 帧")
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print(f" 判定 'Uniform Invalid' 需连续检测: {self.frame_thresh_uniform} 帧")
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print(f" 制服合规恢复缓冲帧数: {self.frame_buffer_uniform} 帧")
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print(f" 判定 'Too Fast' (视为Nobody) 最小停留: {self.frame_thresh_car_min_duration} 帧")
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logger.info(f"\n超参数设置:")
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logger.info(f" FPS: {self.fps:.2f}")
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logger.info(f" 判定 'Only One' / 'Nobody' 需连续: {self.frame_thresh_one} 帧")
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logger.info(f" 判定 'Trunk Checked' 需累计检测: {self.frame_thresh_trunk_valid} 帧")
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logger.info(f" 判定 'Phone Detected' 需累计检测: {self.frame_thresh_phone} 帧")
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logger.info(f" 手机丢失缓冲帧数: {self.frame_buffer_phone} 帧")
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logger.info(f" 判定 'Uniform Invalid' 需连续检测: {self.frame_thresh_uniform} 帧")
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logger.info(f" 制服合规恢复缓冲帧数: {self.frame_buffer_uniform} 帧")
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logger.info(f" 判定 'Too Fast' (视为Nobody) 最小停留: {self.frame_thresh_car_min_duration} 帧")
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self.current_frame_idx = 0
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@@ -260,7 +262,7 @@ class KadianDetector:
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elif cls_id == 3:
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dets_roles.append("phone")
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# print(f'dets_roles: {dets_roles}')
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# logger.debug(f'dets_roles: {dets_roles}')
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dets = np.array(dets_for_tracker, dtype=np.float32) if len(dets_for_tracker) else np.empty((0, 5))
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@@ -269,7 +271,7 @@ class KadianDetector:
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[self.height, self.width],
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[self.height, self.width]
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)
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# print("tracks: {}".format(tracks))
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# logger.debug("tracks: {}".format(tracks))
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# 绘制骨骼
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frame = YOLOv8_Pose_ONNX.draw_keypoints(frame, pose_results)
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# ========= 绘制 ROI =========
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@@ -285,7 +287,7 @@ class KadianDetector:
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current_trunks = [] # (cx, cy)
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for t in tracks:
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# print("t: {}".format(t))
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# logger.debug("t: {}".format(t))
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tid = t.track_id
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# cls_id = -1
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@@ -319,7 +321,7 @@ class KadianDetector:
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cls_id = 2
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elif role == "phone":
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cls_id = 3
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# print("tid: {}, role: {}, cls: {}".format(tid, role,cls_id))
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# logger.debug("tid: {}, role: {}, cls: {}".format(tid, role,cls_id))
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x1, y1, x2, y2 = map(int, t.tlbr)
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@@ -498,12 +500,12 @@ class KadianDetector:
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# 情况1：通过时间太短 -> 归类为 Nobody (Too Fast)
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if duration_frames < self.frame_thresh_car_min_duration:
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print(f"ALARM: Car {car_id} passed too fast -> Regarded as Nobody Checked!")
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logger.warning(f"ALARM: Car {car_id} passed too fast -> Regarded as Nobody Checked!")
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self.fast_pass_alerts[car_id] = self.current_frame_idx + int(3.0 * self.fps)
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# 情况2：时间够长，但没检查后备箱 -> Unchecked Trunk
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elif not car_info['is_checked']:
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print(f"ALARM: Car {car_id} left without checking trunk!")
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logger.warning(f"ALARM: Car {car_id} left without checking trunk!")
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self.unchecked_trunk_alerts[car_id] = self.current_frame_idx + int(3.0 * self.fps)
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del self.roi_car_registry[car_id]
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@@ -698,6 +700,7 @@ class FrameProcessorWorker(threading.Thread):
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except queue.Empty:
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continue
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try:
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cam_id = item["camera_id"]
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ts = item["timestamp"]
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frame = item["frame"]
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@@ -718,7 +721,7 @@ class FrameProcessorWorker(threading.Thread):
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result_img = result["image"]
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result_type = result["alerts"]
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# print(f"alerts: {result_type}")
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# logger.debug(f"alerts: {result_type}")
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# ========= 核心修改：过滤5秒内重复的action =========
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# 初始化当前摄像头的推送时间记录
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@@ -741,7 +744,7 @@ class FrameProcessorWorker(threading.Thread):
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try:
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img_b64 = self._encode_base64(result_img)
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except Exception as e:
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print(f"[ERROR] Encode image failed: {e}")
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logger.error(f"[ERROR] Encode image failed: {e}")
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img_b64 = None
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if img_b64 is not None:
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@@ -761,6 +764,11 @@ class FrameProcessorWorker(threading.Thread):
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# if push_actions and len(push_actions) > 0:
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# self.ws_queue_2.put(msg, timeout=1.0)
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except queue.Full:
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print("[WARN] ws_send_queue full, drop frame message")
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logger.warning("[WARN] ws_send_queue full, drop frame message")
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except Exception as e:
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logger.error(f"[ERROR] Frame processing failed for camera {cam_id if 'cam_id' in locals() else 'unknown'}: {e}")
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logger.exception("Exception details:") # 打印完整的堆栈跟踪
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# 继续处理下一帧，不要退出循环
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finally:
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self.raw_queue.task_done()
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