引入指挥室和看守所
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rtsp_service_ws_Zhihuishi.py
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870
rtsp_service_ws_Zhihuishi.py
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# rtsp_service_kadian.py
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# 融合 Kadian_Detect_1221.py + rtsp_service_ws.py
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# 支持多路RTSP、抽帧、分段保存MP4、WebSocket推送图像与告警
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import cv2
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import numpy as np
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import os
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import time
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import threading
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import queue
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import yaml
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import json
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import base64
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import asyncio
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import websockets
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from dataclasses import dataclass
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from typing import Dict, Any, Tuple, List
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from datetime import datetime
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from test_cam import get_camera_preview_url
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# -------------------------- Kadian 检测相关导入 --------------------------
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from 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 yolox.tracker.byte_tracker import BYTETracker
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# ========================= 配置区 =========================
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Person_Phone_Model = 'YOLO_Weight/person_phone_model.onnx' # 人和手机的检测模型
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Smoke_Model = 'YOLO_Weight/smoke_model.onnx' # 抽烟检测模型
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person_phone_input_size = 1280 # 模型输入尺寸，与训练时的模型一致
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smoke_input_size = 1280 # 模型输入尺寸，与训练时的模型一致
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# RTSP 服务配置
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RTSP_TARGET_FPS = 5.0
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FRAMES_PER_SEGMENT = 300
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WS_HOST = "0.0.0.0"
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WS_PORT = 8771
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WS_PORT_2 = 8770 # 新增：第二个WebSocket端口
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# 新增：告警推送频率限制（秒）
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ALERT_PUSH_INTERVAL = 5.0 # 相同action 5秒内仅推送一次
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# WebSocket 客户端集合
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ws_clients = set()
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ws_clients_2 = set() # 新增：第二个WebSocket客户端集合
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# ========================= 数据结构 =========================
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@dataclass
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class CameraConfig:
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id: int
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name: str
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index: str
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rtsp_url: str
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class ZhihuishiDetector:
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def __init__(self):
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# 模型加载
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# 人和手机检测模型
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print(f"加载人和手机检测模型: {Person_Phone_Model}")
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self.person_phone_detector = YOLOv8_ONNX(Person_Phone_Model, conf_threshold=0.6, iou_threshold=0.45,
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input_size=person_phone_input_size)
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# 抽烟检测模型
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print(f"加载抽烟检测模型: {Smoke_Model}")
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self.smoke_detector = YOLOv8_ONNX(Smoke_Model, conf_threshold=0.4, iou_threshold=0.65,
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input_size=smoke_input_size)
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# ByteTracker
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class TrackerArgs:
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track_thresh = 0.25
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track_buffer = 30
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match_thresh = 0.8
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mot20 = False
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self.fps = RTSP_TARGET_FPS
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self.person_phone_tracker = BYTETracker(TrackerArgs(), frame_rate=self.fps)
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self.smoke_tracker = BYTETracker(TrackerArgs(), frame_rate=self.fps)
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self.person_phone_track_role = {}
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self.smoke_track_role = {}
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# ==========================================
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# 超参数设置 (Hyperparameters)
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# ==========================================
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# 1. 业务判定时间阈值
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self.TIME_THRESHOLD_NOBODY = 2.0 # 无人在场判定时长
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self.TIME_THRESHOLD_SMOKE = 1.0 # 抽烟判定时长
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self.TIME_TOLERANCE_SMOKE = 0.5 # 烟丢失缓冲时间（防抖动）
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self.TIME_THRESHOLD_PHONE = 1.0 # 玩手机判定时长
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self.TIME_TOLERANCE_PHONE = 0.5 # 手机丢失缓冲时间（防抖动）
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# 无人在场帧数阈值
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self.frame_thresh_nobody = int(self.TIME_THRESHOLD_NOBODY * self.fps)
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# 抽烟检测帧数阈值
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self.frame_thresh_smoke = int(self.TIME_THRESHOLD_SMOKE * self.fps)
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self.frame_buffer_smoke = int(self.TIME_TOLERANCE_SMOKE * self.fps)
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# 手机检测帧数阈值
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self.frame_thresh_phone = int(self.TIME_THRESHOLD_PHONE * self.fps)
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self.frame_buffer_phone = int(self.TIME_TOLERANCE_PHONE * 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 'Nobody' 需连续: {self.frame_thresh_nobody} 帧")
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print(f" 判定 'Smoke Detected' 需累计检测: {self.frame_thresh_smoke} 帧")
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print(f" 抽烟丢失缓冲帧数: {self.frame_buffer_smoke} 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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# ==========================================
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# 状态变量初始化
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# ==========================================
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self.current_frame_idx = 0
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# 无人在场检测状态变量
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self.cnt_frame_nobody = 0
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# 手机检测状态变量
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self.phone_detection_frames = 0 # 连续检测到手机的帧数
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self.phone_missing_frames = 0 # 连续未检测到手机的帧数
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self.phone_alert_active = False # 手机报警是否激活
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# 抽烟检测状态变量
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self.smoke_detection_frames = 0 # 连续检测到手机的帧数
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self.smoke_missing_frames = 0 # 连续未检测到手机的帧数
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self.smoke_alert_active = False # 手机报警是否激活
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def compute_iou(self,boxA, boxB):
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# box = [x1, y1, x2, y2]
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xA = max(boxA[0], boxB[0])
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yA = max(boxA[1], boxB[1])
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xB = min(boxA[2], boxB[2])
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yB = min(boxA[3], boxB[3])
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interW = max(0, xB - xA)
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interH = max(0, yB - yA)
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interArea = interW * interH
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boxAArea = (boxA[2] - boxA[0]) * (boxA[3] - boxA[1])
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boxBArea = (boxB[2] - boxB[0]) * (boxB[3] - boxB[1])
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unionArea = boxAArea + boxBArea - interArea
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if unionArea == 0:
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return 0.0
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return interArea / unionArea
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def draw_alert(self, frame, text, color=(0, 0, 255), sub_text=None, offset_y=0):
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"""在右上角绘制警告文字 (支持垂直偏移，防止文字重叠)"""
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font_scale = 1.5
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thickness = 3
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font = cv2.FONT_HERSHEY_SIMPLEX
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(text_w, text_h), _ = cv2.getTextSize(text, font, font_scale, thickness)
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x = self.width - text_w - 20
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y = 50 + text_h + offset_y # 增加 Y 轴偏移
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cv2.rectangle(frame, (x - 10, y - text_h - 10), (x + text_w + 10, y + 10), (0, 0, 0), -1)
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cv2.putText(frame, text, (x, y), font, font_scale, color, thickness)
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if sub_text:
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cv2.putText(frame, sub_text, (x, y + 40), font, 0.7, (200, 200, 200), 2)
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def process_frame(self, frame, camera_id: int, timestamp: float) -> Dict[str, Any]:
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h, w = frame.shape[:2]
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self.width, self.height = w, h
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self.current_frame_idx += 1
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current_time_sec = timestamp
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# ========= 人和手机检测 =========
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person_phone_results = self.person_phone_detector(frame)
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# ========= 抽烟检测 =========
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smoke_results = self.smoke_detector(frame)
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person_phone_dets_xyxy = []
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person_phone_dets_roles = []
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person_phone_dets_for_tracker = []
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smoke_dets_xyxy = []
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smoke_dets_roles = []
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smoke_dets_for_tracker = []
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# ========= 当前帧所有警告列表（关键改动）==========
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current_frame_alerts = [] # 每帧清空，重新收集
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# 收集 人和手机的检测结果
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if person_phone_results:
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for det in person_phone_results:
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x1, y1, x2, y2, conf, cls_id = det # x1, y1, x2, y2为角点坐标，x1 y1为左上角，x2 y2为右下角
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person_phone_dets_xyxy.append([x1, y1, x2, y2])
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person_phone_dets_for_tracker.append([x1, y1, x2, y2, conf])
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if cls_id == 0:
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person_phone_dets_roles.append("phone")
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elif cls_id == 1:
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person_phone_dets_roles.append("police")
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person_phone_dets = np.array(person_phone_dets_for_tracker, dtype=np.float32) if len(
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person_phone_dets_for_tracker) else np.empty((0, 5))
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person_phone_tracks = self.person_phone_tracker.update(
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person_phone_dets,
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[self.height, self.width],
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[self.height, self.width]
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)
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# 收集 抽烟的检测结果
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if smoke_results:
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for det in smoke_results:
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x1, y1, x2, y2, conf, cls_id = det
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smoke_dets_xyxy.append([x1, y1, x2, y2])
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smoke_dets_for_tracker.append([x1, y1, x2, y2, conf])
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if cls_id == 0:
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smoke_dets_roles.append("smoke")
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smoke_dets = np.array(smoke_dets_for_tracker, dtype=np.float32) if len(
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smoke_dets_for_tracker) else np.empty((0, 5))
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smoke_tracks = self.smoke_tracker.update(
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smoke_dets,
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[self.height, self.width],
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[self.height, self.width]
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)
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# ========= 单帧统计变量 =========
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current_person_count = 0
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current_phone_count = 0
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current_smoke_count = 0
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# ========= 人和手机检测 =========
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for t in person_phone_tracks:
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# print("t: {}".format(t))
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tid = t.track_id
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# cls_id = -1
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# IoU 匹配角色
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# IoU匹配跟踪ID和类别
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REVALIDATE_FRAME_INTERVAL = 10
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if (self.current_frame_idx % REVALIDATE_FRAME_INTERVAL == 0) or (tid not in self.person_phone_track_role):
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#if tid not in self.person_phone_track_role:
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best_iou = 0
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best_role = "unknown"
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t_box = list(map(float, t.tlbr)) # [x1,y1,x2,y2]
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for i, box in enumerate(person_phone_dets_xyxy):
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iou_val = self.compute_iou(t_box, box)
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if iou_val > best_iou:
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best_iou = iou_val
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best_role = person_phone_dets_roles[i]
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if best_iou > 0.1:
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self.person_phone_track_role[tid] = best_role
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else:
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self.person_phone_track_role[tid] = "unknown"
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role = self.person_phone_track_role.get(tid, "unknown")
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cls_id = -1
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if role == "phone":
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cls_id = 0
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elif role == "police":
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cls_id = 1
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# print("tid: {}, role: {}, cls: {}".format(tid, role,cls_id))
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x1, y1, x2, y2 = map(int, t.tlbr)
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cx, cy = (x1 + x2) // 2, (y1 + y2) // 2
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color = None
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label = None
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if cls_id == 0: # Person
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current_phone_count += 1
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color = (255, 0, 255)
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label = "Phone"
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elif cls_id == 1: # Phone（主模型已支持）
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current_person_count += 1
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color = (0, 0, 139)
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label = "Person"
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else:
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color = (255, 255, 255)
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label = "Unknown"
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# label = f"ID:{tid} IN"
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cv2.rectangle(frame, (x1, y1), (x2, y2), color, 2)
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cv2.putText(frame, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2)
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# ========= 抽烟检测 =========
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for t in smoke_tracks:
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# print("t: {}".format(t))
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tid = t.track_id
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# cls_id = -1
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# IoU 匹配角色
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# IoU匹配跟踪ID和类别
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REVALIDATE_FRAME_INTERVAL = 10
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if (self.current_frame_idx % REVALIDATE_FRAME_INTERVAL == 0) or (tid not in self.smoke_track_role):
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#if tid not in self.smoke_track_role:
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best_iou = 0
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best_role = "unknown"
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t_box = list(map(float, t.tlbr)) # [x1,y1,x2,y2]
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for i, box in enumerate(smoke_dets_xyxy):
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iou_val = self.compute_iou(t_box, box)
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if iou_val > best_iou:
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best_iou = iou_val
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best_role = smoke_dets_roles[i]
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# self.smoke_track_role[tid] = best_role
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if best_iou > 0.1:
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self.smoke_track_role[tid] = best_role
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else:
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self.smoke_track_role[tid] = "unknown"
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role = self.smoke_track_role.get(tid, "unknown")
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cls_id = -1
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if role == "smoke":
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cls_id = 0
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x1, y1, x2, y2 = map(int, t.tlbr)
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cx, cy = (x1 + x2) // 2, (y1 + y2) // 2
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color = None
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label = None
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if cls_id == 0: # 抽烟
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current_smoke_count += 1
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color = (255, 255, 0)
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label = "Smoke"
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else:
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color = (255, 255, 255)
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label = "Unknown"
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# label = f"ID:{tid} IN"
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cv2.rectangle(frame, (x1, y1), (x2, y2), color, 2)
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cv2.putText(frame, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2)
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# ==========================================
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# 手机检测
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# ==========================================
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if current_phone_count > 0:
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# 检测到手机框
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self.phone_detection_frames += 1
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self.phone_missing_frames = 0 # 重置丢失计数器
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# 当检测累计达到阈值时，激活报警
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if self.phone_detection_frames >= self.frame_thresh_phone:
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self.phone_alert_active = True
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else:
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# 未检测到手机框
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self.phone_missing_frames += 1
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# 如果之前检测到手机，重置检测计数器
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if self.phone_detection_frames > 0:
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# 只有在连续丢失超过缓冲帧数时才重置
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if self.phone_missing_frames >= self.frame_buffer_phone:
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self.phone_detection_frames = 0
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self.phone_alert_active = False
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else:
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# 从未检测到手机，保持状态
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pass
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# ==========================================
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# 抽烟检测
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# ==========================================
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if current_smoke_count > 0:
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# 检测到抽烟框
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self.smoke_detection_frames += 1
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self.smoke_missing_frames = 0 # 重置丢失计数器
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# 当检测累计达到阈值时，激活报警
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if self.smoke_detection_frames >= self.frame_thresh_smoke:
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self.smoke_alert_active = True
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else:
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# 未检测到抽烟框
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self.smoke_missing_frames += 1
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# 如果之前检测到抽烟，重置检测计数器
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if self.smoke_detection_frames > 0:
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# 只有在连续丢失超过缓冲帧数时才重置
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if self.smoke_missing_frames >= self.frame_buffer_smoke:
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self.smoke_detection_frames = 0
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self.smoke_alert_active = False
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else:
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# 从未检测到抽烟，保持状态
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||||
pass
|
||||
|
||||
# ==========================================
|
||||
# 9. 业务逻辑判定 (Only One / Nobody)
|
||||
# ==========================================
|
||||
status_text = ""
|
||||
|
||||
if current_person_count == 0:
|
||||
self.cnt_frame_nobody += 1
|
||||
else:
|
||||
self.cnt_frame_nobody = 0
|
||||
|
||||
# ==========================================
|
||||
# 10. 收集并生成结构化警告（核心改动）
|
||||
# ==========================================
|
||||
|
||||
alert_offset = 0
|
||||
|
||||
# A. Playing Phone
|
||||
if self.phone_alert_active:
|
||||
duration_seconds = self.phone_detection_frames / self.fps
|
||||
current_frame_alerts.append(
|
||||
{
|
||||
'time': current_time_sec,
|
||||
'action': 'Playing Phone',
|
||||
'confidence': 1.0, # 固定为1.0（规则判定）
|
||||
'details': f"Detected for {duration_seconds:.1f}s"
|
||||
}
|
||||
)
|
||||
|
||||
# A. Playing Phone
|
||||
if self.smoke_alert_active:
|
||||
duration_seconds = self.smoke_detection_frames / self.fps
|
||||
current_frame_alerts.append(
|
||||
{
|
||||
'time': current_time_sec,
|
||||
'action': 'Smoke',
|
||||
'confidence': 1.0, # 固定为1.0（规则判定）
|
||||
'details': f"Detected for {duration_seconds:.1f}s"
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
# D. Nobody Checking
|
||||
elif self.cnt_frame_nobody >= self.frame_thresh_nobody:
|
||||
current_frame_alerts.append({
|
||||
'time': current_time_sec,
|
||||
'action': 'Nobody Checking',
|
||||
'confidence': 1.0,
|
||||
'details': 'No inspector present'
|
||||
})
|
||||
|
||||
# ==========================================
|
||||
# 11. 统一显示当前帧所有警告（可替换原分层显示）
|
||||
# ==========================================
|
||||
debug_info = f"Person: {current_person_count} | Phone: {current_phone_count} | Smoke: {current_smoke_count}"
|
||||
cv2.putText(frame, debug_info, (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)
|
||||
|
||||
# 统一警告显示区
|
||||
alert_y_start = 150
|
||||
for i, alert in enumerate(current_frame_alerts):
|
||||
action = alert['action']
|
||||
details = alert.get('details', '')
|
||||
color = (0, 0, 255) # 默认红色警告
|
||||
|
||||
if action == 'Nobody Checking':
|
||||
color = (255, 255, 255)
|
||||
elif action == 'Smoke':
|
||||
color = (0, 0, 255)
|
||||
elif action == 'Playing Phone':
|
||||
color = (255, 0, 0)
|
||||
|
||||
main_text = action
|
||||
if details:
|
||||
main_text += f" ({details})"
|
||||
|
||||
y_pos = alert_y_start + i * 50
|
||||
cv2.rectangle(frame, (20, y_pos - 40), (900, y_pos + 10), (0, 0, 0), -1)
|
||||
cv2.putText(frame, main_text, (30, y_pos), cv2.FONT_HERSHEY_SIMPLEX, 1.0, color, 2)
|
||||
|
||||
return {
|
||||
"image": frame,
|
||||
|
||||
"alerts":current_frame_alerts
|
||||
}
|
||||
|
||||
# ========================= WebSocket 服务线程 =========================
|
||||
class WebSocketSender(threading.Thread):
|
||||
def __init__(self, send_queue: queue.Queue, stop_event: threading.Event):
|
||||
super().__init__(daemon=True)
|
||||
self.send_queue = send_queue
|
||||
self.stop_event = stop_event
|
||||
|
||||
async def _ws_handler(self, websocket):
|
||||
ws_clients.add(websocket)
|
||||
try:
|
||||
async for _ in websocket:
|
||||
pass
|
||||
finally:
|
||||
ws_clients.discard(websocket)
|
||||
|
||||
async def _broadcaster(self):
|
||||
while not self.stop_event.is_set():
|
||||
try:
|
||||
msg = await asyncio.to_thread(self.send_queue.get, timeout=0.5)
|
||||
except queue.Empty:
|
||||
continue
|
||||
data = json.dumps(msg)
|
||||
dead = []
|
||||
for ws in list(ws_clients):
|
||||
try:
|
||||
await ws.send(data)
|
||||
except:
|
||||
dead.append(ws)
|
||||
for ws in dead:
|
||||
ws_clients.discard(ws)
|
||||
self.send_queue.task_done()
|
||||
|
||||
async def _run_async(self):
|
||||
async with websockets.serve(self._ws_handler, WS_HOST, WS_PORT):
|
||||
print(f"[INFO] WebSocket server started at ws://{WS_HOST}:{WS_PORT}")
|
||||
await self._broadcaster()
|
||||
|
||||
def run(self):
|
||||
asyncio.run(self._run_async())
|
||||
|
||||
|
||||
# ========================= WebSocket 服务线程2 =========================
|
||||
class WebSocketSender2(threading.Thread):
|
||||
def __init__(self, send_queue: queue.Queue, stop_event: threading.Event):
|
||||
super().__init__(daemon=True)
|
||||
self.send_queue = send_queue
|
||||
self.stop_event = stop_event
|
||||
|
||||
async def _ws_handler(self, websocket):
|
||||
ws_clients_2.add(websocket)
|
||||
try:
|
||||
async for _ in websocket:
|
||||
pass
|
||||
finally:
|
||||
ws_clients_2.discard(websocket)
|
||||
|
||||
async def _broadcaster(self):
|
||||
while not self.stop_event.is_set():
|
||||
try:
|
||||
msg = await asyncio.to_thread(self.send_queue.get, timeout=0.5)
|
||||
except queue.Empty:
|
||||
continue
|
||||
data = json.dumps(msg)
|
||||
dead = []
|
||||
for ws in list(ws_clients_2):
|
||||
try:
|
||||
await ws.send(data)
|
||||
except:
|
||||
dead.append(ws)
|
||||
for ws in dead:
|
||||
ws_clients_2.discard(ws)
|
||||
self.send_queue.task_done()
|
||||
|
||||
async def _run_async(self):
|
||||
async with websockets.serve(self._ws_handler, WS_HOST, WS_PORT_2):
|
||||
print(f"[INFO] WebSocket server 2 started at ws://{WS_HOST}:{WS_PORT_2}")
|
||||
await self._broadcaster()
|
||||
|
||||
def run(self):
|
||||
asyncio.run(self._run_async())
|
||||
|
||||
|
||||
# ========================= RTSP 抓流线程 =========================
|
||||
class RTSPCaptureWorker(threading.Thread):
|
||||
def __init__(self, camera_cfg: CameraConfig, raw_queue: queue.Queue, stop_event: threading.Event):
|
||||
super().__init__(daemon=True)
|
||||
self.camera_cfg = camera_cfg
|
||||
self.raw_queue = raw_queue
|
||||
self.stop_event = stop_event
|
||||
# 添加重连计数器
|
||||
self.reconnect_count = 0
|
||||
self.max_reconnects = 5
|
||||
self.rtsp_url = ""
|
||||
|
||||
def run(self):
|
||||
while not self.stop_event.is_set():
|
||||
try:
|
||||
|
||||
if self.reconnect_count >= self.max_reconnects:
|
||||
print(f"[WARN] RTSP: {self.camera_cfg.name} reach max reconnects, refresh url")
|
||||
self.reconnect_count = 0
|
||||
new_url = self.refresh_video_url()
|
||||
if new_url:
|
||||
self.rtsp_url = new_url
|
||||
else:
|
||||
print(f"[ERROR] refresh RTSP URL is empty, do nothing")
|
||||
|
||||
# 检查rtsp_url是否为空或None，如果是则重新获取
|
||||
if not self.rtsp_url:
|
||||
print(f"[WARN] RTSP URL is empty, refreshing...")
|
||||
new_url = self.refresh_video_url()
|
||||
if new_url:
|
||||
self.rtsp_url = new_url
|
||||
else:
|
||||
print(f"[ERROR] RTSP URL is still empty, retrying in 5 seconds")
|
||||
time.sleep(5)
|
||||
continue
|
||||
|
||||
# 方法1：使用TCP传输（更稳定）
|
||||
rtsp_url = self.rtsp_url
|
||||
if "?" not in rtsp_url:
|
||||
rtsp_url += "?transport=tcp" # 强制TCP传输
|
||||
else:
|
||||
rtsp_url += "&transport=tcp"
|
||||
|
||||
# 方法2：添加更多FFmpeg参数
|
||||
cap = cv2.VideoCapture(rtsp_url, cv2.CAP_FFMPEG)
|
||||
|
||||
# 方法3：设置缓冲区大小
|
||||
cap.set(cv2.CAP_PROP_BUFFERSIZE, 10) # 增加缓冲区
|
||||
|
||||
# 方法4：设置超时和重连参数
|
||||
os.environ["OPENCV_FFMPEG_CAPTURE_OPTIONS"] = \
|
||||
"rtsp_transport;tcp|buffer_size;1024000|max_delay;500000|stimeout;2000000"
|
||||
|
||||
# 方法5：设置解码器flags，忽略解码错误
|
||||
# cap.set(cv2.CAP_PROP_HW_ACCELERATION, cv2.VIDEO_ACCELERATION_ANY)
|
||||
|
||||
if not cap.isOpened():
|
||||
print(f"[ERROR] Cannot open RTSP: {self.rtsp_url}")
|
||||
time.sleep(2)
|
||||
self.reconnect_count += 1
|
||||
continue
|
||||
|
||||
print(f"[INFO] Successfully opened RTSP: {self.name}")
|
||||
self.reconnect_count = 0 # 重置重连计数
|
||||
|
||||
# # 设置帧率（可选）
|
||||
# cap.set(cv2.CAP_PROP_FPS, 25)
|
||||
|
||||
while not self.stop_event.is_set():
|
||||
ret, frame = cap.read()
|
||||
if not ret:
|
||||
# 检查流是否结束
|
||||
print(f"[WARN] Failed to read frame from {self.camera_cfg.name}")
|
||||
|
||||
# 检查是否还有数据
|
||||
time.sleep(0.1)
|
||||
# 尝试几次后重连
|
||||
break
|
||||
|
||||
item = {
|
||||
"camera_id": self.camera_cfg.id,
|
||||
"camera_name": self.camera_cfg.name,
|
||||
"timestamp": time.time(),
|
||||
"frame": frame,
|
||||
}
|
||||
|
||||
try:
|
||||
# 添加队列满时的处理
|
||||
if self.raw_queue.full():
|
||||
# 丢弃最旧的一帧
|
||||
try:
|
||||
self.raw_queue.get_nowait()
|
||||
self.raw_queue.task_done()
|
||||
except queue.Empty:
|
||||
pass
|
||||
|
||||
self.raw_queue.put(item, timeout=0.5)
|
||||
except queue.Full:
|
||||
print(f"[WARN] Queue full, dropping frame from {self.camera_cfg.name}")
|
||||
continue
|
||||
|
||||
# 控制读取速度，避免过快
|
||||
time.sleep(0.02) # 约50ms间隔
|
||||
|
||||
cap.release()
|
||||
|
||||
except Exception as e:
|
||||
print(f"[ERROR] Error in RTSP capture for {self.camera_cfg.name}: {e}")
|
||||
time.sleep(2)
|
||||
self.reconnect_count += 1
|
||||
|
||||
if self.reconnect_count >= self.max_reconnects:
|
||||
print(f"[ERROR] Max reconnects reached for {self.camera_cfg.name}, stopping.")
|
||||
|
||||
def refresh_video_url(self):
|
||||
"""
|
||||
重新通过视频ID获取视频URL，调用test_cam.py中的get_camera_preview_url方法
|
||||
|
||||
返回:
|
||||
str: 新的视频URL，如果获取失败则返回None
|
||||
"""
|
||||
try:
|
||||
|
||||
# 获取视频ID（camera_cfg.index）
|
||||
video_id = self.camera_cfg.index
|
||||
|
||||
# 调用test_cam.py中的函数
|
||||
result = get_camera_preview_url(video_id)
|
||||
|
||||
# 解析结果（与test_cam.py相同）
|
||||
if 'data' in result and 'url' in result['data']:
|
||||
new_url = result['data']['url']
|
||||
print(f"[INFO] get rtsp url success, URL: {new_url}")
|
||||
return new_url
|
||||
else:
|
||||
print(f"[ERROR] get rtsp url failed: {result}")
|
||||
return None
|
||||
|
||||
except Exception as e:
|
||||
print(f"[ERROR] get rtsp url error: {str(e)}")
|
||||
return None
|
||||
|
||||
|
||||
# ========================= 帧处理线程 =========================
|
||||
class FrameProcessorWorker(threading.Thread):
|
||||
def __init__(self,
|
||||
raw_frame_queue: "queue.Queue[Dict[str, Any]]",
|
||||
ws_send_queue: "queue.Queue[Dict[str, Any]]",
|
||||
ws_send_queue_2: "queue.Queue[Dict[str, Any]]",
|
||||
stop_event: threading.Event):
|
||||
super().__init__(daemon=True)
|
||||
self.raw_queue = raw_frame_queue
|
||||
self.ws_queue = ws_send_queue
|
||||
self.ws_queue_2 = ws_send_queue_2 # 新增：第二个WebSocket队列
|
||||
self.stop_event = stop_event
|
||||
|
||||
self.last_ts: Dict[int, float] = {}
|
||||
|
||||
# 每个摄像头一个独立的 Kadian 检测器实例
|
||||
self.kadian_detectors: Dict[int, ZhihuishiDetector] = {}
|
||||
|
||||
# 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
|
||||
|
||||
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:
|
||||
self.kadian_detectors[cam_id] = ZhihuishiDetector()
|
||||
detector = self.kadian_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
|
||||
|
||||
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": 1,
|
||||
"timestamp": ts,
|
||||
#"result_type": action_names,
|
||||
"result_type": push_actions,
|
||||
"image_base64": img_b64,
|
||||
}
|
||||
try:
|
||||
self.ws_queue.put(msg, timeout=1.0)
|
||||
#if action_names and len(action_names) > 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")
|
||||
|
||||
self.raw_queue.task_done()
|
||||
|
||||
|
||||
# ========================= 服务主类 =========================
|
||||
class RTSPService:
|
||||
def __init__(self, config_path: str = "config.yaml"):
|
||||
with open(config_path, "r", encoding="utf-8") as f:
|
||||
cfg = yaml.safe_load(f)
|
||||
self.cameras = [CameraConfig(id=c["id"], name=c.get("name", f"cam_{c['id']}"), index = c["index"], rtsp_url=c["rtsp_url"])
|
||||
for c in cfg.get("cameras", [])]
|
||||
|
||||
self.stop_event = threading.Event()
|
||||
self.raw_queue = queue.Queue(maxsize=500)
|
||||
self.ws_queue = queue.Queue(maxsize=1000)
|
||||
self.ws_queue_2 = queue.Queue(maxsize=1000) # 新增：第二个WebSocket队列
|
||||
|
||||
self.capture_workers = []
|
||||
self.processor = FrameProcessorWorker(self.raw_queue, self.ws_queue, self.ws_queue_2, self.stop_event)
|
||||
self.ws_sender = WebSocketSender(self.ws_queue, self.stop_event)
|
||||
self.ws_sender_2 = WebSocketSender2(self.ws_queue_2, self.stop_event) # 新增：第二个WebSocket发送器
|
||||
|
||||
def start(self):
|
||||
self.ws_sender.start()
|
||||
self.ws_sender_2.start() # 新增：启动第二个WebSocket服务
|
||||
self.processor.start()
|
||||
for cam in self.cameras:
|
||||
w = RTSPCaptureWorker(cam, self.raw_queue, self.stop_event)
|
||||
w.start()
|
||||
self.capture_workers.append(w)
|
||||
print("[INFO] Zhihuishi RTSP Service started")
|
||||
|
||||
def stop(self):
|
||||
self.stop_event.set()
|
||||
self.raw_queue.join()
|
||||
self.ws_queue.join()
|
||||
self.ws_queue_2.join() # 新增：等待第二个WebSocket队列
|
||||
for w in self.capture_workers:
|
||||
w.join(timeout=2.0)
|
||||
self.processor.join(timeout=2.0)
|
||||
self.ws_sender.join(timeout=2.0)
|
||||
self.ws_sender_2.join(timeout=2.0) # 新增：等待第二个WebSocket发送器
|
||||
print("[INFO] Service stopped")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
service = RTSPService("config.yaml")
|
||||
service.start()
|
||||
try:
|
||||
while True:
|
||||
time.sleep(1)
|
||||
except KeyboardInterrupt:
|
||||
service.stop()
|
||||
538
rtsp_service_ws_kanshousuo.py
Normal file
538
rtsp_service_ws_kanshousuo.py
Normal file
@@ -0,0 +1,538 @@
|
||||
# rtsp_service_kadian.py
|
||||
# 融合 Kadian_Detect_1221.py + rtsp_service_ws.py
|
||||
# 支持多路RTSP、抽帧、分段保存MP4、WebSocket推送图像与告警
|
||||
|
||||
import cv2
|
||||
import numpy as np
|
||||
import os
|
||||
import time
|
||||
import threading
|
||||
import queue
|
||||
import yaml
|
||||
import json
|
||||
import base64
|
||||
import asyncio
|
||||
import websockets
|
||||
from dataclasses import dataclass
|
||||
from typing import Dict, Any, Tuple, List
|
||||
from datetime import datetime
|
||||
|
||||
# -------------------------- Kadian 检测相关导入 --------------------------
|
||||
from npu_yolo_onnx_person_car_phone import YOLOv8_ONNX # 主检测模型（人/车/后备箱/手机）
|
||||
|
||||
from yolox.tracker.byte_tracker import BYTETracker
|
||||
|
||||
|
||||
# ========================= 配置区 =========================
|
||||
# Kadian 模型路径与ROI（可根据实际情况修改）
|
||||
detector_model_path = 'YOLO_Weight/bag_model.onnx'
|
||||
|
||||
|
||||
|
||||
# 输入尺寸
|
||||
input_size = 640
|
||||
|
||||
# RTSP 服务配置
|
||||
RTSP_TARGET_FPS = 5.0
|
||||
WS_HOST = "0.0.0.0"
|
||||
WS_PORT = 8767
|
||||
WS_PORT_2 = 8766 # 新增：第二个WebSocket端口
|
||||
|
||||
ALERT_PUSH_INTERVAL=5.0
|
||||
|
||||
# WebSocket 客户端集合
|
||||
ws_clients = set()
|
||||
ws_clients_2 = set() # 新增：第二个WebSocket客户端集合
|
||||
|
||||
|
||||
# ========================= 数据结构 =========================
|
||||
@dataclass
|
||||
class CameraConfig:
|
||||
id: int
|
||||
name: str
|
||||
rtsp_url: str
|
||||
|
||||
|
||||
# ========================= Kadian TrafficMonitor（精简版，专为服务设计） =========================
|
||||
class KadianDetector:
|
||||
def __init__(self):
|
||||
# 模型加载
|
||||
|
||||
self.detector = YOLOv8_ONNX(detector_model_path, conf_threshold=0.5, iou_threshold=0.45,
|
||||
input_size=input_size)
|
||||
|
||||
# ByteTracker
|
||||
class TrackerArgs:
|
||||
track_thresh = 0.25
|
||||
track_buffer = 30
|
||||
match_thresh = 0.8
|
||||
mot20 = False
|
||||
|
||||
|
||||
|
||||
self.track_role = {}
|
||||
|
||||
self.fps = RTSP_TARGET_FPS
|
||||
|
||||
self.tracker = BYTETracker(TrackerArgs(), frame_rate=self.fps)
|
||||
|
||||
# ==========================================
|
||||
# 超参数设置
|
||||
# ==========================================
|
||||
self.TIME_THRESHOLD_BLACKBAG = 1.0 # 黑包判定时长（秒）
|
||||
self.TIME_TOLERANCE_BLACKBAG = 0.5 # 黑包丢失缓冲时间
|
||||
|
||||
# 转换为帧数阈值
|
||||
self.frame_thresh_blackbag = int(self.TIME_THRESHOLD_BLACKBAG * self.fps)
|
||||
self.frame_buffer_blackbag = int(self.TIME_TOLERANCE_BLACKBAG * self.fps)
|
||||
|
||||
print(f"\n超参数设置:")
|
||||
print(f" FPS: {self.fps:.2f}")
|
||||
print(f" 判定 'BlackBag Detected' 需累计检测: {self.frame_thresh_blackbag} 帧")
|
||||
print(f" 黑包丢失缓冲帧数: {self.frame_buffer_blackbag} 帧")
|
||||
|
||||
# ==========================================
|
||||
# 状态变量初始化
|
||||
# ==========================================
|
||||
self.current_frame_idx = 0
|
||||
|
||||
# 黑包检测状态
|
||||
self.blackbag_detection_frames = 0
|
||||
self.blackbag_missing_frames = 0
|
||||
self.blackbag_alert_active = False
|
||||
|
||||
# 人员统计变量
|
||||
self.current_person_count = 0
|
||||
|
||||
|
||||
def compute_iou(self,boxA, boxB):
|
||||
# box = [x1, y1, x2, y2]
|
||||
xA = max(boxA[0], boxB[0])
|
||||
yA = max(boxA[1], boxB[1])
|
||||
xB = min(boxA[2], boxB[2])
|
||||
yB = min(boxA[3], boxB[3])
|
||||
|
||||
interW = max(0, xB - xA)
|
||||
interH = max(0, yB - yA)
|
||||
interArea = interW * interH
|
||||
|
||||
boxAArea = (boxA[2] - boxA[0]) * (boxA[3] - boxA[1])
|
||||
boxBArea = (boxB[2] - boxB[0]) * (boxB[3] - boxB[1])
|
||||
|
||||
unionArea = boxAArea + boxBArea - interArea
|
||||
if unionArea == 0:
|
||||
return 0.0
|
||||
|
||||
return interArea / unionArea
|
||||
|
||||
def draw_alert(self, frame, text, color=(0, 0, 255), sub_text=None, offset_y=0):
|
||||
"""在右上角绘制警告文字 (支持垂直偏移，防止文字重叠)"""
|
||||
font_scale = 1.5
|
||||
thickness = 3
|
||||
font = cv2.FONT_HERSHEY_SIMPLEX
|
||||
|
||||
(text_w, text_h), _ = cv2.getTextSize(text, font, font_scale, thickness)
|
||||
x = self.width - text_w - 20
|
||||
y = 50 + text_h + offset_y # 增加 Y 轴偏移
|
||||
|
||||
cv2.rectangle(frame, (x - 10, y - text_h - 10), (x + text_w + 10, y + 10), (0, 0, 0), -1)
|
||||
cv2.putText(frame, text, (x, y), font, font_scale, color, thickness)
|
||||
|
||||
if sub_text:
|
||||
cv2.putText(frame, sub_text, (x, y + 40), font, 0.7, (200, 200, 200), 2)
|
||||
|
||||
def process_frame(self, frame, camera_id: int, timestamp: float) -> Dict[str, Any]:
|
||||
h, w = frame.shape[:2]
|
||||
self.width, self.height = w, h
|
||||
|
||||
self.current_frame_idx += 1
|
||||
|
||||
current_time_sec = timestamp
|
||||
|
||||
# ========= 检测推理（黑包+人）=========
|
||||
detect_results = self.detector(frame)
|
||||
|
||||
# 初始化检测结果存储
|
||||
dets_xyxy = []
|
||||
dets_roles = []
|
||||
dets_for_tracker = []
|
||||
current_frame_alerts = []
|
||||
|
||||
# 解析检测结果（黑包cls_id=0，人员cls_id=1）
|
||||
if detect_results:
|
||||
for det in detect_results:
|
||||
x1, y1, x2, y2, conf, cls_id = det
|
||||
dets_xyxy.append([x1, y1, x2, y2])
|
||||
dets_for_tracker.append([x1, y1, x2, y2, conf])
|
||||
if cls_id == 0:
|
||||
dets_roles.append("black_bag")
|
||||
elif cls_id == 1:
|
||||
dets_roles.append("person")
|
||||
|
||||
# 跟踪器更新
|
||||
dets = np.array(dets_for_tracker, dtype=np.float32) if len(dets_for_tracker) else np.empty((0, 5))
|
||||
tracks = self.tracker.update(
|
||||
dets,
|
||||
[self.height, self.width],
|
||||
[self.height, self.width]
|
||||
)
|
||||
|
||||
# ========= 单帧统计初始化 =========
|
||||
self.current_person_count = 0
|
||||
current_blackbag_count = 0
|
||||
|
||||
# ========= 跟踪结果绘制与统计 =========
|
||||
for t in tracks:
|
||||
tid = t.track_id
|
||||
|
||||
# IoU匹配跟踪ID和类别
|
||||
REVALIDATE_FRAME_INTERVAL = 10
|
||||
|
||||
|
||||
#if tid not in self.track_role:
|
||||
if (self.current_frame_idx % REVALIDATE_FRAME_INTERVAL == 0) or (tid not in self.track_role):
|
||||
best_iou = 0
|
||||
best_role = "unknown"
|
||||
t_box = list(map(float, t.tlbr))
|
||||
for i, box in enumerate(dets_xyxy):
|
||||
iou_val = self.compute_iou(t_box, box)
|
||||
if iou_val > best_iou:
|
||||
best_iou = iou_val
|
||||
best_role = dets_roles[i]
|
||||
self.track_role[tid] = best_role if best_iou > 0.1 else "unknown"
|
||||
|
||||
role = self.track_role.get(tid, "unknown")
|
||||
x1, y1, x2, y2 = map(int, t.tlbr)
|
||||
color = (255, 255, 255)
|
||||
label = "Unknown"
|
||||
|
||||
# 人员检测（cls_id=1）
|
||||
if role == "person":
|
||||
self.current_person_count += 1
|
||||
color = (255, 0, 255) # 紫色框
|
||||
label = "Person"
|
||||
# 黑包检测（cls_id=0）
|
||||
elif role == "black_bag":
|
||||
current_blackbag_count += 1
|
||||
color = (0, 128, 0) # 绿色框
|
||||
label = "Black Bag"
|
||||
|
||||
# 绘制检测框和标签
|
||||
cv2.rectangle(frame, (x1, y1), (x2, y2), color, 2)
|
||||
cv2.putText(frame, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.6, color, 2)
|
||||
|
||||
# ==========================================
|
||||
# 黑包状态更新
|
||||
# ==========================================
|
||||
if current_blackbag_count > 0:
|
||||
self.blackbag_detection_frames += 1
|
||||
self.blackbag_missing_frames = 0
|
||||
if self.blackbag_detection_frames >= self.frame_thresh_blackbag:
|
||||
self.blackbag_alert_active = True
|
||||
else:
|
||||
self.blackbag_missing_frames += 1
|
||||
if self.blackbag_missing_frames >= self.frame_buffer_blackbag:
|
||||
self.blackbag_detection_frames = 0
|
||||
self.blackbag_alert_active = False
|
||||
|
||||
# ==========================================
|
||||
# 警告信息收集
|
||||
# ==========================================
|
||||
if self.blackbag_alert_active:
|
||||
duration_seconds = self.blackbag_detection_frames / self.fps
|
||||
current_frame_alerts.append(
|
||||
{
|
||||
'time': current_time_sec,
|
||||
'action': 'Black Bag',
|
||||
'details': f"Detected for {duration_seconds:.1f}s"
|
||||
}
|
||||
)
|
||||
self.draw_alert(frame, "Black Bag Alert", (0, 0, 255), sub_text=f"Detected for {duration_seconds:.1f}s")
|
||||
|
||||
# ==========================================
|
||||
# 绘制信息
|
||||
# ==========================================
|
||||
# 实时统计
|
||||
debug_info = f"Person: {self.current_person_count} | BlackBag: {current_blackbag_count}"
|
||||
cv2.putText(frame, debug_info, (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2)
|
||||
|
||||
# 警告信息
|
||||
alert_y_start = 150
|
||||
for i, alert in enumerate(current_frame_alerts):
|
||||
action = alert['action']
|
||||
details = alert.get('details', '')
|
||||
color = (0, 0, 255) # 红色警告
|
||||
main_text = f"{action} ({details})"
|
||||
y_pos = alert_y_start + i * 50
|
||||
cv2.rectangle(frame, (20, y_pos - 40), (900, y_pos + 10), (0, 0, 0), -1)
|
||||
cv2.putText(frame, main_text, (30, y_pos), cv2.FONT_HERSHEY_SIMPLEX, 1.0, color, 2)
|
||||
|
||||
return {
|
||||
"image": frame,
|
||||
|
||||
"alerts":current_frame_alerts
|
||||
}
|
||||
|
||||
# ========================= WebSocket 服务线程 =========================
|
||||
class WebSocketSender(threading.Thread):
|
||||
def __init__(self, send_queue: queue.Queue, stop_event: threading.Event):
|
||||
super().__init__(daemon=True)
|
||||
self.send_queue = send_queue
|
||||
self.stop_event = stop_event
|
||||
|
||||
async def _ws_handler(self, websocket):
|
||||
ws_clients.add(websocket)
|
||||
try:
|
||||
async for _ in websocket:
|
||||
pass
|
||||
finally:
|
||||
ws_clients.discard(websocket)
|
||||
|
||||
async def _broadcaster(self):
|
||||
while not self.stop_event.is_set():
|
||||
try:
|
||||
msg = await asyncio.to_thread(self.send_queue.get, timeout=0.5)
|
||||
except queue.Empty:
|
||||
continue
|
||||
data = json.dumps(msg)
|
||||
dead = []
|
||||
for ws in list(ws_clients):
|
||||
try:
|
||||
await ws.send(data)
|
||||
except:
|
||||
dead.append(ws)
|
||||
for ws in dead:
|
||||
ws_clients.discard(ws)
|
||||
self.send_queue.task_done()
|
||||
|
||||
async def _run_async(self):
|
||||
async with websockets.serve(self._ws_handler, WS_HOST, WS_PORT):
|
||||
print(f"[INFO] WebSocket server started at ws://{WS_HOST}:{WS_PORT}")
|
||||
await self._broadcaster()
|
||||
|
||||
def run(self):
|
||||
asyncio.run(self._run_async())
|
||||
|
||||
|
||||
# ========================= WebSocket 服务线程2 =========================
|
||||
class WebSocketSender2(threading.Thread):
|
||||
def __init__(self, send_queue: queue.Queue, stop_event: threading.Event):
|
||||
super().__init__(daemon=True)
|
||||
self.send_queue = send_queue
|
||||
self.stop_event = stop_event
|
||||
|
||||
async def _ws_handler(self, websocket):
|
||||
ws_clients_2.add(websocket)
|
||||
try:
|
||||
async for _ in websocket:
|
||||
pass
|
||||
finally:
|
||||
ws_clients_2.discard(websocket)
|
||||
|
||||
async def _broadcaster(self):
|
||||
while not self.stop_event.is_set():
|
||||
try:
|
||||
msg = await asyncio.to_thread(self.send_queue.get, timeout=0.5)
|
||||
except queue.Empty:
|
||||
continue
|
||||
data = json.dumps(msg)
|
||||
dead = []
|
||||
for ws in list(ws_clients_2):
|
||||
try:
|
||||
await ws.send(data)
|
||||
except:
|
||||
dead.append(ws)
|
||||
for ws in dead:
|
||||
ws_clients_2.discard(ws)
|
||||
self.send_queue.task_done()
|
||||
|
||||
async def _run_async(self):
|
||||
async with websockets.serve(self._ws_handler, WS_HOST, WS_PORT_2):
|
||||
print(f"[INFO] WebSocket server 2 started at ws://{WS_HOST}:{WS_PORT_2}")
|
||||
await self._broadcaster()
|
||||
|
||||
def run(self):
|
||||
asyncio.run(self._run_async())
|
||||
|
||||
|
||||
# ========================= RTSP 抓流线程 =========================
|
||||
class RTSPCaptureWorker(threading.Thread):
|
||||
def __init__(self, camera_cfg: CameraConfig, raw_queue: queue.Queue, stop_event: threading.Event):
|
||||
super().__init__(daemon=True)
|
||||
self.camera_cfg = camera_cfg
|
||||
self.raw_queue = raw_queue
|
||||
self.stop_event = stop_event
|
||||
|
||||
def run(self):
|
||||
cap = cv2.VideoCapture(self.camera_cfg.rtsp_url, cv2.CAP_FFMPEG)
|
||||
if not cap.isOpened():
|
||||
print(f"[ERROR] Cannot open RTSP: {self.camera_cfg.rtsp_url}")
|
||||
return
|
||||
print(f"[INFO] Capturing {self.camera_cfg.name} (ID:{self.camera_cfg.id})")
|
||||
while not self.stop_event.is_set():
|
||||
ret, frame = cap.read()
|
||||
if not ret:
|
||||
time.sleep(0.2)
|
||||
continue
|
||||
item = {
|
||||
"camera_id": self.camera_cfg.id,
|
||||
"camera_name": self.camera_cfg.name,
|
||||
"timestamp": time.time(),
|
||||
"frame": frame,
|
||||
}
|
||||
try:
|
||||
self.raw_queue.put(item, timeout=1.0)
|
||||
except queue.Full:
|
||||
pass
|
||||
cap.release()
|
||||
|
||||
|
||||
# ========================= 帧处理线程 =========================
|
||||
class FrameProcessorWorker(threading.Thread):
|
||||
def __init__(self,
|
||||
raw_frame_queue: "queue.Queue[Dict[str, Any]]",
|
||||
ws_send_queue: "queue.Queue[Dict[str, Any]]",
|
||||
ws_send_queue_2: "queue.Queue[Dict[str, Any]]",
|
||||
stop_event: threading.Event):
|
||||
super().__init__(daemon=True)
|
||||
self.raw_queue = raw_frame_queue
|
||||
self.ws_queue = ws_send_queue
|
||||
self.ws_queue_2 = ws_send_queue_2 # 新增：第二个WebSocket队列
|
||||
self.stop_event = stop_event
|
||||
|
||||
self.last_ts: Dict[int, float] = {}
|
||||
|
||||
# 每个摄像头一个独立的 Kadian 检测器实例
|
||||
self.kadian_detectors: Dict[int, KadianDetector] = {}
|
||||
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
|
||||
|
||||
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:
|
||||
self.kadian_detectors[cam_id] = KadianDetector()
|
||||
detector = self.kadian_detectors[cam_id]
|
||||
|
||||
# 执行检测
|
||||
result = detector.process_frame(frame.copy(), cam_id, ts)
|
||||
|
||||
result_img = result["image"]
|
||||
result_type = result["alerts"]
|
||||
|
||||
if cam_id not in self.last_alert_push_time:
|
||||
self.last_alert_push_time[cam_id]={}
|
||||
|
||||
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)
|
||||
|
||||
if current_time-last_push>=ALERT_PUSH_INTERVAL:
|
||||
push_actions.append(action)
|
||||
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
|
||||
|
||||
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": 1,
|
||||
"timestamp": ts,
|
||||
#"result_type": action_names,
|
||||
"result_type": push_actions,
|
||||
"image_base64": img_b64,
|
||||
}
|
||||
try:
|
||||
self.ws_queue.put(msg, timeout=1.0)
|
||||
#if action_names and len(action_names) > 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")
|
||||
|
||||
self.raw_queue.task_done()
|
||||
|
||||
|
||||
# ========================= 服务主类 =========================
|
||||
class RTSPService:
|
||||
def __init__(self, config_path: str = "config.yaml"):
|
||||
with open(config_path, "r", encoding="utf-8") as f:
|
||||
cfg = yaml.safe_load(f)
|
||||
self.cameras = [CameraConfig(id=c["id"], name=c.get("name", f"cam_{c['id']}"), rtsp_url=c["rtsp_url"])
|
||||
for c in cfg.get("cameras", [])]
|
||||
|
||||
self.stop_event = threading.Event()
|
||||
self.raw_queue = queue.Queue(maxsize=500)
|
||||
self.ws_queue = queue.Queue(maxsize=1000)
|
||||
self.ws_queue_2 = queue.Queue(maxsize=1000) # 新增：第二个WebSocket队列
|
||||
|
||||
self.capture_workers = []
|
||||
self.processor = FrameProcessorWorker(self.raw_queue, self.ws_queue, self.ws_queue_2, self.stop_event)
|
||||
self.ws_sender = WebSocketSender(self.ws_queue, self.stop_event)
|
||||
self.ws_sender_2 = WebSocketSender2(self.ws_queue_2, self.stop_event) # 新增：第二个WebSocket发送器
|
||||
|
||||
def start(self):
|
||||
self.ws_sender.start()
|
||||
self.ws_sender_2.start() # 新增：启动第二个WebSocket服务
|
||||
self.processor.start()
|
||||
for cam in self.cameras:
|
||||
w = RTSPCaptureWorker(cam, self.raw_queue, self.stop_event)
|
||||
w.start()
|
||||
self.capture_workers.append(w)
|
||||
print("[INFO] Kadian RTSP Service started")
|
||||
|
||||
def stop(self):
|
||||
self.stop_event.set()
|
||||
self.raw_queue.join()
|
||||
self.ws_queue.join()
|
||||
self.ws_queue_2.join() # 新增：等待第二个WebSocket队列
|
||||
for w in self.capture_workers:
|
||||
w.join(timeout=2.0)
|
||||
self.processor.join(timeout=2.0)
|
||||
self.ws_sender.join(timeout=2.0)
|
||||
self.ws_sender_2.join(timeout=2.0) # 新增：等待第二个WebSocket发送器
|
||||
print("[INFO] Service stopped")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
service = RTSPService("config.yaml")
|
||||
service.start()
|
||||
try:
|
||||
while True:
|
||||
time.sleep(1)
|
||||
except KeyboardInterrupt:
|
||||
service.stop()
|
||||
Reference in New Issue
Block a user