提取frame processor到base
This commit is contained in:
195
biz/base_frame_processor.py
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195
biz/base_frame_processor.py
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# base_frame_processor.py
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# 通用帧处理工作线程基类
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# 统一异步POST、告警去重、抽帧控制等公共逻辑
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import cv2
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import base64
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import time
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import threading
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import queue
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import requests
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from typing import Dict, Any, Callable
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from concurrent.futures import ThreadPoolExecutor
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from common.contants import ALERT_PUSH_URL
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from utils.logger import get_logger
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logger = get_logger(__name__)
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# 告警推送频率限制（秒）
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ALERT_PUSH_INTERVAL = 5.0
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class BaseFrameProcessorWorker(threading.Thread):
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"""
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通用帧处理工作线程基类
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功能：
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- 统一异步POST（线程池）
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- 统一告警去重逻辑
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- 统一抽帧控制
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- 统一异常处理
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子类仅需提供：
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- DETECTOR_FACTORY: 检测器工厂函数
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- POST_TYPE: POST请求的type值
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- TARGET_FPS: 目标帧率
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"""
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# ========== 子类必须重写的类常量 ==========
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DETECTOR_FACTORY: Callable = None # 检测器工厂函数
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POST_TYPE: int = 2 # POST type
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TARGET_FPS: float = 10.0 # 目标帧率
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def __init__(self,
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raw_queue: queue.Queue,
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ws_queue: queue.Queue,
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stop_event: threading.Event,
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cameras=None,
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post_workers: int = 4):
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super().__init__(daemon=True)
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self.raw_queue = raw_queue
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self.ws_queue = ws_queue
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self.stop_event = stop_event
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# 将摄像头列表转换为字典，key为id，方便通过camera_id快速查找
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self.cameras = {cam.id: cam for cam in cameras} if cameras is not None else {}
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self.last_ts: Dict[int, float] = {}
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# 检测器实例缓存
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self.detectors: Dict[int, Any] = {}
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# 告警去重记录 {camera_id: {action: last_push_time}}
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self.last_alert_push_time: Dict[int, Dict[str, float]] = {}
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# 异步POST线程池
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self.post_executor = ThreadPoolExecutor(
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max_workers=post_workers,
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thread_name_prefix="alert_post"
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)
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def _encode_image_to_base64(self, img) -> str:
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"""图像编码为 Base64"""
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ok, buf = cv2.imencode(".jpg", img)
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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 _post_alert(self, msg: dict):
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"""异步发送告警 POST 请求（在线程池中执行）"""
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try:
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response = requests.post(ALERT_PUSH_URL, json=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: {msg.get('result_type')}")
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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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def _create_detector(self, params):
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"""创建检测器实例"""
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# 使用 type(self) 访问类属性，避免 lambda 被绑定 self 参数
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factory = type(self).DETECTOR_FACTORY
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if factory is None:
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raise NotImplementedError("子类必须提供 DETECTOR_FACTORY")
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return factory(params)
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def _filter_duplicate_alerts(self, cam_id: int, alerts: list, current_time: float) -> list:
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"""
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过滤5秒内重复的告警
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Args:
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cam_id: 摄像头ID
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alerts: 当前帧的告警列表
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current_time: 当前时间戳
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Returns:
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符合推送条件的action列表
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"""
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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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push_actions = []
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for alert in alerts:
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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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return push_actions
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def run(self):
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"""主循环 - 模板方法"""
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target_interval = 1.0 / self.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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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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# 抽帧控制
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if ts - self.last_ts.get(cam_id, 0) < target_interval:
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continue
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self.last_ts[cam_id] = ts
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# 获取或创建检测器实例
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if cam_id not in self.detectors:
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camera_config = self.cameras.get(cam_id)
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params = camera_config.params if camera_config else None
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self.detectors[cam_id] = self._create_detector(params)
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detector = self.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_alerts = result["alerts"]
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# 过滤重复告警
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push_actions = self._filter_duplicate_alerts(
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cam_id, result_alerts, time.time()
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)
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# 编码图像
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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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logger.error(f"[ERROR] Encode image failed: {e}")
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img_b64 = None
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# 推送结果
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if img_b64 is not None:
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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": 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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# 异步发送 POST 请求（提交到线程池）
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post_msg = msg.copy()
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post_msg['type'] = self.POST_TYPE
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self.post_executor.submit(self._post_alert, post_msg)
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except queue.Full:
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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(
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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:")
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finally:
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self.raw_queue.task_done()
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# 线程退出时关闭线程池
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self.post_executor.shutdown(wait=False)
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@@ -1,14 +1,11 @@
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import cv2
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import cv2
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import numpy as np
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import numpy as np
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import base64
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from typing import Dict, Any
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from typing import Dict, Any
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import threading
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import threading
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import time
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import queue
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import queue
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import requests
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from concurrent.futures import ThreadPoolExecutor
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from biz.base_frame_processor import BaseFrameProcessorWorker
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from common.contants import ALERT_PUSH_URL
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# -------------------------- Kadian 检测相关导入 --------------------------
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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 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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@@ -813,135 +810,10 @@ class KadianDetector:
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# ========================= 帧处理线程 =========================
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# ========================= 帧处理线程 =========================
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class FrameProcessorWorker(threading.Thread):
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class FrameProcessorWorker(BaseFrameProcessorWorker):
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def __init__(self, raw_queue: queue.Queue, ws_queue: queue.Queue, stop_event: threading.Event, cameras=None, post_workers: int = 4):
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"""卡点检测帧处理线程"""
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super().__init__(daemon=True)
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self.raw_queue = raw_queue
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self.ws_queue = ws_queue
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self.stop_event = stop_event
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# 将摄像头列表转换为字典，key为id，方便通过camera_id快速查找
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self.cameras = {cam.id: cam for cam in cameras} if cameras is not None else {}
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self.last_ts: Dict[int, float] = {}
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# 子类配置
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DETECTOR_FACTORY = lambda params: KadianDetector(params)
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# 每个摄像头一个独立的 Kadian 检测器实例
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POST_TYPE = 1
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self.kadian_detectors: Dict[int, KadianDetector] = {}
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TARGET_FPS = RTSP_TARGET_FPS
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self.last_alert_push_time: Dict[int, Dict[str, float]] = {}
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# 线程池用于异步发送 POST 请求
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self.post_executor = ThreadPoolExecutor(max_workers=post_workers, thread_name_prefix="alert_post")
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def _post_alert(self, msg: dict):
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"""异步发送告警 POST 请求（在线程池中执行）"""
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try:
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response = requests.post(ALERT_PUSH_URL, json=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: {msg.get('result_type')}")
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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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def _encode_base64(self, img):
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_, buf = cv2.imencode(".jpg", img)
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return base64.b64encode(buf).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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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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# 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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camera_config = self.cameras.get(cam_id)
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params = camera_config.params if camera_config else None
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self.kadian_detectors[cam_id] = KadianDetector(params)
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detector = self.kadian_detectors[cam_id]
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# 执行检测
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# detect_start = time.time()
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result = detector.process_frame(frame.copy(), cam_id, ts)
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# detect_time = (time.time() - detect_start) * 1000
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result_img = result["image"]
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result_type = result["alerts"]
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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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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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# encode_start = time.time()
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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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logger.error(f"[ERROR] Encode image failed: {e}")
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img_b64 = None
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# encode_time = (time.time() - encode_start) * 1000
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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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# 异步发送 POST 请求（提交到线程池）
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post_msg = msg.copy()
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post_msg['type'] = 1
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self.post_executor.submit(self._post_alert, post_msg)
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except queue.Full:
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logger.warning("[WARN] ws_send_queue full, drop frame message")
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# # 打印关键操作的耗时
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# total_time = detect_time + encode_time
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# logger.info(f"[PERF] Camera {cam_id} - Total: {total_time:.1f}ms | "
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# f"Detect: {detect_time:.1f}ms | "
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# f"Encode: {encode_time:.1f}ms | ")
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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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|
||||||
# 线程退出时关闭线程池
|
|
||||||
self.post_executor.shutdown(wait=False)
|
|
||||||
|
|||||||
@@ -5,17 +5,14 @@
|
|||||||
import cv2
|
import cv2
|
||||||
import numpy as np
|
import numpy as np
|
||||||
import os
|
import os
|
||||||
import time
|
|
||||||
import threading
|
import threading
|
||||||
import queue
|
import queue
|
||||||
import yaml
|
import yaml
|
||||||
import json
|
import json
|
||||||
import base64
|
|
||||||
|
|
||||||
from typing import Dict, Any, Tuple, List
|
from typing import Dict, Any, Tuple, List
|
||||||
|
|
||||||
from common.contants import ALERT_PUSH_URL
|
from biz.base_frame_processor import BaseFrameProcessorWorker
|
||||||
import requests
|
|
||||||
|
|
||||||
# -------------------------- Kadian 检测相关导入 --------------------------
|
# -------------------------- Kadian 检测相关导入 --------------------------
|
||||||
from algorithm.common.npu_yolo_onnx_person_car_phone import YOLOv8_ONNX # 主检测模型（人/车/后备箱/手机）
|
from algorithm.common.npu_yolo_onnx_person_car_phone import YOLOv8_ONNX # 主检测模型（人/车/后备箱/手机）
|
||||||
@@ -496,126 +493,11 @@ class ZhihuishiDetector:
|
|||||||
|
|
||||||
|
|
||||||
# ========================= 帧处理线程 =========================
|
# ========================= 帧处理线程 =========================
|
||||||
class FrameProcessorWorker(threading.Thread):
|
class FrameProcessorWorker(BaseFrameProcessorWorker):
|
||||||
def __init__(self, raw_queue: queue.Queue, ws_queue: queue.Queue, stop_event: threading.Event, cameras=None):
|
"""监控室检测帧处理线程"""
|
||||||
super().__init__(daemon=True)
|
|
||||||
self.raw_queue = raw_queue
|
|
||||||
self.ws_queue = ws_queue
|
|
||||||
self.stop_event = stop_event
|
|
||||||
self.cameras = {cam.id: cam for cam in cameras} if cameras is not None else {}
|
|
||||||
|
|
||||||
self.last_ts: Dict[int, float] = {}
|
# 子类配置
|
||||||
|
DETECTOR_FACTORY = lambda params: ZhihuishiDetector(params)
|
||||||
# 每个摄像头一个独立的 Kadian 检测器实例
|
POST_TYPE = 2
|
||||||
self.kadian_detectors: Dict[int, ZhihuishiDetector] = {}
|
TARGET_FPS = RTSP_TARGET_FPS
|
||||||
|
|
||||||
self.last_alert_push_time: Dict[int, Dict[str, float]] = {}
|
|
||||||
|
|
||||||
def _encode_base64(self, img):
|
|
||||||
_, buf = cv2.imencode(".jpg", img)
|
|
||||||
return base64.b64encode(buf).decode("ascii")
|
|
||||||
|
|
||||||
def run(self):
|
|
||||||
target_interval = 1.0 / RTSP_TARGET_FPS
|
|
||||||
while not self.stop_event.is_set():
|
|
||||||
try:
|
|
||||||
item = self.raw_queue.get(timeout=0.5)
|
|
||||||
except queue.Empty:
|
|
||||||
continue
|
|
||||||
|
|
||||||
try:
|
|
||||||
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.kadian_detectors:
|
|
||||||
camera_config = self.cameras.get(cam_id)
|
|
||||||
params = camera_config.params if camera_config else None
|
|
||||||
self.kadian_detectors[cam_id] = ZhihuishiDetector(params)
|
|
||||||
detector = self.kadian_detectors[cam_id]
|
|
||||||
|
|
||||||
# 执行检测
|
|
||||||
# detect_start = time.time()
|
|
||||||
result = detector.process_frame(frame.copy(), cam_id, ts)
|
|
||||||
# detect_time = (time.time() - detect_start) * 1000
|
|
||||||
|
|
||||||
result_img = result["image"]
|
|
||||||
result_type = result["alerts"]
|
|
||||||
# logger.debug(f"alerts: {result_type}")
|
|
||||||
|
|
||||||
# ========= 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
|
|
||||||
# encode_start = time.time()
|
|
||||||
try:
|
|
||||||
img_b64 = self._encode_base64(result_img)
|
|
||||||
except Exception as e:
|
|
||||||
logger.error(f"[ERROR] Encode image failed: {e}")
|
|
||||||
img_b64 = None
|
|
||||||
# encode_time = (time.time() - encode_start) * 1000
|
|
||||||
|
|
||||||
if img_b64 is not None:
|
|
||||||
# 将abnormal_actions对象数组转换为字符串数组
|
|
||||||
# action_names = [action_info['action'] for action_info in push_actions]
|
|
||||||
|
|
||||||
msg = {
|
|
||||||
"msg_type": "frame",
|
|
||||||
"camera_id": item["camera_index"],
|
|
||||||
"timestamp": ts,
|
|
||||||
# "result_type": action_names,
|
|
||||||
"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:
|
|
||||||
# 发送POST请求
|
|
||||||
post_msg = msg.copy()
|
|
||||||
post_msg['type'] = 2
|
|
||||||
try:
|
|
||||||
response = requests.post(ALERT_PUSH_URL, json=post_msg, timeout=5.0)
|
|
||||||
if response.status_code == 200:
|
|
||||||
print(f"[INFO] POST alert sent successfully for actions: {push_actions}")
|
|
||||||
else:
|
|
||||||
print(f"[WARN] POST alert failed with status: {response.status_code}")
|
|
||||||
except Exception as e:
|
|
||||||
print(f"[ERROR] POST alert request failed: {e}")
|
|
||||||
except queue.Full:
|
|
||||||
logger.warning("[WARN] ws_send_queue full, drop frame message")
|
|
||||||
|
|
||||||
# # 打印关键操作的耗时
|
|
||||||
# total_time = detect_time + encode_time
|
|
||||||
# logger.info(f"[PERF] Camera {cam_id} - Total: {total_time:.1f}ms | "
|
|
||||||
# f"Detect: {detect_time:.1f}ms | "
|
|
||||||
# f"Encode: {encode_time:.1f}ms | ")
|
|
||||||
|
|
||||||
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()
|
|
||||||
|
|
||||||
|
|||||||
@@ -6,19 +6,17 @@
|
|||||||
import cv2
|
import cv2
|
||||||
import numpy as np
|
import numpy as np
|
||||||
import os
|
import os
|
||||||
import time
|
|
||||||
import threading
|
import threading
|
||||||
import queue
|
import queue
|
||||||
import yaml
|
import yaml
|
||||||
import json
|
import json
|
||||||
import base64
|
|
||||||
import asyncio
|
import asyncio
|
||||||
import websockets
|
import websockets
|
||||||
from dataclasses import dataclass
|
from dataclasses import dataclass
|
||||||
from typing import Dict, Any, Tuple, List
|
from typing import Dict, Any, Tuple, List
|
||||||
from datetime import datetime
|
from datetime import datetime
|
||||||
from common.contants import ALERT_PUSH_URL
|
|
||||||
import requests
|
from biz.base_frame_processor import BaseFrameProcessorWorker
|
||||||
|
|
||||||
|
|
||||||
# -------------------------- Kadian 检测相关导入 --------------------------
|
# -------------------------- Kadian 检测相关导入 --------------------------
|
||||||
@@ -480,118 +478,10 @@ class TrajectoryDetector:
|
|||||||
|
|
||||||
|
|
||||||
# ========================= 帧处理线程 =========================
|
# ========================= 帧处理线程 =========================
|
||||||
class FrameProcessorWorker(threading.Thread):
|
class FrameProcessorWorker(BaseFrameProcessorWorker):
|
||||||
def __init__(self,
|
"""轨迹检测帧处理线程"""
|
||||||
raw_frame_queue: "queue.Queue[Dict[str, Any]]",
|
|
||||||
ws_send_queue: "queue.Queue[Dict[str, Any]]",
|
|
||||||
stop_event: threading.Event,
|
|
||||||
cameras=None):
|
|
||||||
super().__init__(daemon=True)
|
|
||||||
self.raw_queue = raw_frame_queue
|
|
||||||
self.ws_queue = ws_send_queue
|
|
||||||
self.stop_event = stop_event
|
|
||||||
# 将摄像头列表转换为字典，key为id，方便通过camera_id快速查找
|
|
||||||
self.cameras = {cam.id: cam for cam in cameras} if cameras is not None else {}
|
|
||||||
|
|
||||||
self.last_ts: Dict[int, float] = {}
|
# 子类配置
|
||||||
|
DETECTOR_FACTORY = lambda params: TrajectoryDetector(params)
|
||||||
# 每个摄像头一个独立的 Kadian 检测器实例
|
POST_TYPE = 2
|
||||||
self.trajectory_detectors: Dict[int, TrajectoryDetector] = {}
|
TARGET_FPS = RTSP_TARGET_FPS
|
||||||
|
|
||||||
# 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}}
|
|
||||||
self.last_alert_push_time: Dict[int, Dict[str, float]] = {}
|
|
||||||
|
|
||||||
def _encode_image_to_base64(self, image) -> str:
|
|
||||||
ok, buf = cv2.imencode(".jpg", image)
|
|
||||||
if not ok:
|
|
||||||
raise RuntimeError("Failed to encode image to JPEG")
|
|
||||||
return base64.b64encode(buf.tobytes()).decode("ascii")
|
|
||||||
|
|
||||||
def run(self):
|
|
||||||
target_interval = 1.0 / RTSP_TARGET_FPS
|
|
||||||
while not self.stop_event.is_set():
|
|
||||||
try:
|
|
||||||
item = self.raw_queue.get(timeout=0.5)
|
|
||||||
except queue.Empty:
|
|
||||||
continue
|
|
||||||
|
|
||||||
try:
|
|
||||||
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:
|
|
||||||
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:
|
|
||||||
img_b64 = self._encode_image_to_base64(result_img)
|
|
||||||
except Exception as e:
|
|
||||||
logger.error(f"[ERROR] Encode image failed: {e}")
|
|
||||||
img_b64 = None
|
|
||||||
|
|
||||||
if img_b64 is not None:
|
|
||||||
msg = {
|
|
||||||
"msg_type": "frame",
|
|
||||||
"camera_id": item["camera_index"],
|
|
||||||
"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:
|
|
||||||
# 发送POST请求
|
|
||||||
post_msg = msg.copy()
|
|
||||||
post_msg['type'] = 2
|
|
||||||
try:
|
|
||||||
response = requests.post(ALERT_PUSH_URL, json=post_msg, timeout=5.0)
|
|
||||||
if response.status_code == 200:
|
|
||||||
print(f"[INFO] POST alert sent successfully for actions: {push_actions}")
|
|
||||||
else:
|
|
||||||
print(f"[WARN] POST alert failed with status: {response.status_code}")
|
|
||||||
except Exception as e:
|
|
||||||
print(f"[ERROR] POST alert request failed: {e}")
|
|
||||||
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()
|
|
||||||
|
|||||||
Reference in New Issue
Block a user