diff --git a/biz/prison/trajectory02_biz.py b/biz/prison/trajectory02_biz.py index 150b937..0ba05a3 100644 --- a/biz/prison/trajectory02_biz.py +++ b/biz/prison/trajectory02_biz.py @@ -25,6 +25,9 @@ from algorithm.common.npu_yolo_onnx_person_car_phone import YOLOv8_ONNX # 主 from yolox.tracker.byte_tracker import BYTETracker +from utils.logger import get_logger +logger = get_logger(__name__) + # ========================= 配置区 ========================= # Kadian 模型路径与ROI（可根据实际情况修改） detector_model_path = 'YOLO_Weight/prisoner_model.onnx' @@ -38,9 +41,15 @@ RTSP_TARGET_FPS = 10.0 # 新增：告警推送频率限制（秒） ALERT_PUSH_INTERVAL = 5.0 # 相同action 5秒内仅推送一次 +# 默认 ROI 相对坐标（区域多边形） +DEFAULT_ROI_RELATIVE = [(0.47, 0.35), (0.5, 0.35), (0.7, 1.0), (0.3, 1.0)] + class TrajectoryDetector: - def __init__(self): + def __init__(self, params=None): + # 摄像头额外参数 + self.params = params if params is not None else {} + # 模型加载 self.police_prisoner_detector = YOLOv8_ONNX(detector_model_path, conf_threshold=0.5, iou_threshold=0.45, input_size=input_size) @@ -75,12 +84,12 @@ class TrajectoryDetector: self.frame_thresh_prisoner = int(self.TIME_THRESHOLD_PRISONER * self.fps) self.frame_buffer_prisoner = int(self.TIME_TOLERANCE_PRISONER * self.fps) - print(f"\n超参数设置:") - print(f" FPS: {self.fps:.2f}") - print(f" 判定 'police Detected' 需累计检测: {self.frame_thresh_police} 帧") - print(f" 警察丢失缓冲帧数: {self.frame_buffer_police} 帧") - print(f" 判定 'prisoner Detected' 需累计检测: {self.frame_thresh_prisoner} 帧") - print(f" 犯人丢失缓冲帧数: {self.frame_buffer_prisoner} 帧") + logger.debug(f"\n超参数设置:") + logger.debug(f" FPS: {self.fps:.2f}") + logger.debug(f" 判定 'police Detected' 需累计检测: {self.frame_thresh_police} 帧") + logger.debug(f" 警察丢失缓冲帧数: {self.frame_buffer_police} 帧") + logger.debug(f" 判定 'prisoner Detected' 需累计检测: {self.frame_thresh_prisoner} 帧") + logger.debug(f" 犯人丢失缓冲帧数: {self.frame_buffer_prisoner} 帧") # ========================================== # 状态变量初始化 @@ -102,10 +111,13 @@ class TrajectoryDetector: # ========================= # ⚠️ 改为相对坐标（0-1区间），按 [x, y] 格式，x/y 范围 0~1 # 示例：原 (50,100) 在 960x480 分辨率下 → x=50/960≈0.052, y=100/480≈0.208 + # ROI 处理：优先从 params 获取，否则使用默认值 DEFAULT_ROI_RELATIVE + roi_points = self.params.get('roi_points', DEFAULT_ROI_RELATIVE) + self.route_rois = [ { "name": "zone", # 单一区域，犯人离开即报警 - "polygon_rel": [(0.47, 0.35), (0.5, 0.35), (0.7, 1.0), (0.3, 1.0)] # 相对坐标，可自定义 + "polygon_rel": roi_points # 相对坐标，从params获取或使用默认值 } ] @@ -113,7 +125,7 @@ class TrajectoryDetector: self.width = 0 self.height = 0 - print(f"相对坐标 ROI: {self.route_rois}") + logger.debug(f"相对坐标 ROI: {self.route_rois}") # 每个犯人（track_id）一套状态 self.prisoner_route_state = {} @@ -498,64 +510,73 @@ class FrameProcessorWorker(threading.Thread): except queue.Empty: continue - cam_id = item["camera_id"] - ts = item["timestamp"] - frame = item["frame"] - - # 抽帧控制 - if ts - self.last_ts.get(cam_id, 0) < target_interval: - self.raw_queue.task_done() - continue - self.last_ts[cam_id] = ts - - # 获取检测器实例 - if cam_id not in self.trajectory_detectors: - self.trajectory_detectors[cam_id] = TrajectoryDetector() - detector = self.trajectory_detectors[cam_id] - - # 执行检测 - result = detector.process_frame(frame.copy(), cam_id, ts) - - result_img = result["image"] - result_type = result["alerts"] - - # ========= 核心修改：过滤5秒内重复的action ========= - # 初始化当前摄像头的推送时间记录 - if cam_id not in self.last_alert_push_time: - self.last_alert_push_time[cam_id] = {} - - # 筛选出符合推送条件的action（5秒内未推送过） - push_actions = [] - current_time = time.time() - for alert in result_type: - action = alert['action'] - last_push = self.last_alert_push_time[cam_id].get(action, 0) - # 检查是否超过推送间隔 - if current_time - last_push >= ALERT_PUSH_INTERVAL: - push_actions.append(action) - # 更新该action的最后推送时间 - self.last_alert_push_time[cam_id][action] = current_time - - # 通过 WebSocket 发送帧结果 try: - img_b64 = self._encode_image_to_base64(result_img) - except Exception as e: - print(f"[ERROR] Encode image failed: {e}") - img_b64 = None + cam_id = item["camera_id"] + ts = item["timestamp"] + frame = item["frame"] - if img_b64 is not None: - msg = { - "msg_type": "frame", - "camera_id": 1, - "timestamp": ts, - "result_type": push_actions, - "image_base64": img_b64, - } + # 抽帧控制 + if ts - self.last_ts.get(cam_id, 0) < target_interval: + # self.raw_queue.task_done() + continue + self.last_ts[cam_id] = ts + + # 获取检测器实例 + if cam_id not in self.trajectory_detectors: + camera_config = self.cameras.get(cam_id) + params = camera_config.params if camera_config else None + self.trajectory_detectors[cam_id] = TrajectoryDetector(params) + detector = self.trajectory_detectors[cam_id] + + # 执行检测 + result = detector.process_frame(frame.copy(), cam_id, ts) + + result_img = result["image"] + result_type = result["alerts"] + + # ========= 核心修改：过滤5秒内重复的action ========= + # 初始化当前摄像头的推送时间记录 + if cam_id not in self.last_alert_push_time: + self.last_alert_push_time[cam_id] = {} + + # 筛选出符合推送条件的action（5秒内未推送过） + push_actions = [] + current_time = time.time() + for alert in result_type: + action = alert['action'] + last_push = self.last_alert_push_time[cam_id].get(action, 0) + # 检查是否超过推送间隔 + if current_time - last_push >= ALERT_PUSH_INTERVAL: + push_actions.append(action) + # 更新该action的最后推送时间 + self.last_alert_push_time[cam_id][action] = current_time + + # 通过 WebSocket 发送帧结果 try: - self.ws_queue.put(msg, timeout=1.0) - # if push_actions and len(push_actions) > 0: - # self.ws_queue_2.put(msg, timeout=1.0) - except queue.Full: - print("[WARN] ws_send_queue full, drop frame message") + img_b64 = self._encode_image_to_base64(result_img) + except Exception as e: + logger.error(f"[ERROR] Encode image failed: {e}") + img_b64 = None - self.raw_queue.task_done() \ No newline at end of file + if img_b64 is not None: + msg = { + "msg_type": "frame", + "camera_id": 1, + "timestamp": ts, + "result_type": push_actions, + "image_base64": img_b64, + } + try: + self.ws_queue.put(msg, timeout=1.0) + # if push_actions and len(push_actions) > 0: + # self.ws_queue_2.put(msg, timeout=1.0) + except queue.Full: + logger.warning("[WARN] ws_send_queue full, drop frame message") + + except Exception as e: + logger.error( + f"[ERROR] Frame processing failed for camera {cam_id if 'cam_id' in locals() else 'unknown'}: {e}") + logger.exception("Exception details:") # 打印完整的堆栈跟踪 + # 继续处理下一帧，不要退出循环 + finally: + self.raw_queue.task_done()