完成走廊迁移
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@@ -7,6 +7,8 @@ import time
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import queue
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import requests
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from biz.base_frame_processor import BaseFrameProcessorWorker
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# -------------------------- Kadian 检测相关导入 --------------------------
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from algorithm.common.npu_yolo_onnx_person_car_phone import YOLOv8_ONNX # 主检测模型（人/车/后备箱/手机）
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from common.constants import ALERT_PUSH_URL
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@@ -19,7 +21,7 @@ from yolox.tracker.byte_tracker import BYTETracker
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detector_model_path = 'YOLO_Weight/prisoner_model.onnx'
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# 输入尺寸
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input_size = 1280
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input_size = 640
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RTSP_TARGET_FPS = 10.0
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@@ -28,9 +30,11 @@ ALERT_PUSH_INTERVAL = 5.0 # 相同action 5秒内仅推送一次
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class ZoulangDetector:
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def __init__(self):
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# 模型加载
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def __init__(self, params=None):
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# 摄像头额外参数
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self.params = params if params is not None else {}
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# 模型加载
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self.police_prisoner_detector = YOLOv8_ONNX(detector_model_path, conf_threshold=0.5, iou_threshold=0.45,
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input_size=input_size)
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@@ -41,8 +45,6 @@ class ZoulangDetector:
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match_thresh = 0.8
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mot20 = False
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self.police_prisoner_track_role = {}
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self.fps = RTSP_TARGET_FPS
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@@ -334,114 +336,11 @@ class ZoulangDetector:
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}
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# ========================= 帧处理线程 =========================
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class FrameProcessorWorker(threading.Thread):
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def __init__(self,
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raw_frame_queue: "queue.Queue[Dict[str, Any]]",
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ws_send_queue: "queue.Queue[Dict[str, Any]]",
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stop_event: threading.Event):
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super().__init__(daemon=True)
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self.raw_queue = raw_frame_queue
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self.ws_queue = ws_send_queue
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self.stop_event = stop_event
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class FrameProcessorWorker(BaseFrameProcessorWorker):
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"""轨迹检测帧处理线程"""
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self.last_ts: Dict[int, float] = {}
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# 每个摄像头一个独立的 Kadian 检测器实例
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self.kadian_detectors: Dict[int, ZoulangDetector] = {}
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# 新增：维护每个摄像头每个action的最后推送时间 {camera_id: {action: last_push_time}}
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self.last_alert_push_time: Dict[int, Dict[str, float]] = {}
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def _encode_image_to_base64(self, image) -> str:
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ok, buf = cv2.imencode(".jpg", image)
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if not ok:
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raise RuntimeError("Failed to encode image to JPEG")
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return base64.b64encode(buf.tobytes()).decode("ascii")
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def run(self):
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target_interval = 1.0 / RTSP_TARGET_FPS
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while not self.stop_event.is_set():
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try:
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item = self.raw_queue.get(timeout=0.5)
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except queue.Empty:
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continue
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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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# 抽帧控制
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if ts - self.last_ts.get(cam_id, 0) < target_interval:
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self.raw_queue.task_done()
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continue
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self.last_ts[cam_id] = ts
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# 获取检测器实例
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if cam_id not in self.kadian_detectors:
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self.kadian_detectors[cam_id] = ZoulangDetector()
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detector = self.kadian_detectors[cam_id]
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# 执行检测
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result = detector.process_frame(frame.copy(), cam_id, ts)
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result_img = result["image"]
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result_type = result["alerts"]
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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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if cam_id not in self.last_alert_push_time:
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self.last_alert_push_time[cam_id] = {}
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# 筛选出符合推送条件的action（5秒内未推送过）
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push_actions = []
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current_time = time.time()
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for alert in result_type:
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action = alert['action']
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last_push = self.last_alert_push_time[cam_id].get(action, 0)
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# 检查是否超过推送间隔
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if current_time - last_push >= ALERT_PUSH_INTERVAL:
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push_actions.append(action)
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# 更新该action的最后推送时间
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self.last_alert_push_time[cam_id][action] = current_time
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# 通过 WebSocket 发送帧结果
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try:
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img_b64 = self._encode_image_to_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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img_b64 = None
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if img_b64 is not None:
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# 将abnormal_actions对象数组转换为字符串数组
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#action_names = [action_info['action'] for action_info in push_actions]
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msg = {
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"msg_type": "frame",
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"camera_id": item["camera_index"],
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"timestamp": ts,
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#"result_type": action_names,
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"result_type": push_actions,
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"image_base64": img_b64,
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}
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try:
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self.ws_queue.put(msg, timeout=1.0)
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if push_actions and len(push_actions) > 0:
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# 发送POST请求
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post_msg = msg.copy()
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post_msg['type'] = 2
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try:
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response = requests.post(ALERT_PUSH_URL, json=post_msg, timeout=5.0)
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if response.status_code == 200:
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print(f"[INFO] POST alert sent successfully for actions: {push_actions}")
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else:
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print(f"[WARN] POST alert failed with status: {response.status_code}")
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except Exception as e:
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print(f"[ERROR] POST alert request failed: {e}")
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except queue.Full:
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print("[WARN] ws_send_queue full, drop frame message")
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self.raw_queue.task_done()
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# 子类配置
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DETECTOR_FACTORY = lambda params: ZoulangDetector(params)
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POST_TYPE = 2
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TARGET_FPS = RTSP_TARGET_FPS
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@@ -2,6 +2,7 @@ from biz.checkpoint.checkpoint_biz import FrameProcessorWorker as CheckpointWork
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from biz.prison.trajectory02_biz import FrameProcessorWorker as TrajectoryWorker
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from biz.prison.supervision_room_biz import FrameProcessorWorker as SupervisionWorker
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from biz.prison.ab_biz import FrameProcessorWorker as AbWorker
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from biz.prison.prison_biz import FrameProcessorWorker as CorridorWorker
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# ... 其他导入
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@@ -9,7 +10,8 @@ PROCESSOR_MAP = {
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"checkpoint": CheckpointWorker,
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"trajectory": TrajectoryWorker,
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"supervision_room": SupervisionWorker,
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"ab": AbWorker
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"ab": AbWorker,
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"corridor": CorridorWorker
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}
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def get_processor(processor_type: str):
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