583 lines
22 KiB
Python
583 lines
22 KiB
Python
# 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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# 修改为单一区域监控：犯人离开指定区域即报警
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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 common.contants import ALERT_PUSH_URL
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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 rtsp_service_ws_0108 import WS_PORT
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from yolox.tracker.byte_tracker import BYTETracker
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from utils.logger import get_logger
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logger = get_logger(__name__)
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# ========================= 配置区 =========================
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# Kadian 模型路径与ROI（可根据实际情况修改）
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detector_model_path = 'YOLO_Weight/prisoner_model.onnx'
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# 输入尺寸
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input_size = 640
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# RTSP 服务配置
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RTSP_TARGET_FPS = 10.0
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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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# 默认 ROI 相对坐标（区域多边形）
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DEFAULT_ROI_RELATIVE = [(0.47, 0.35), (0.5, 0.35), (0.7, 1.0), (0.3, 1.0)]
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class TrajectoryDetector:
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def __init__(self, params=None):
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# 摄像头额外参数
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self.params = params if params is not None else {}
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# 模型加载
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self.police_prisoner_detector = YOLOv8_ONNX(detector_model_path, conf_threshold=0.5, iou_threshold=0.45,
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input_size=input_size)
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# 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.police_prisoner_track_role = {}
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self.fps = RTSP_TARGET_FPS
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self.tracker = BYTETracker(TrackerArgs(), frame_rate=self.fps)
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# ==========================================
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# 超参数设置 (Hyperparameters)
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# ==========================================
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self.TIME_THRESHOLD_POLICE = 1.0 # 警察判定时长
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self.TIME_TOLERANCE_POLICE = 0.5 # 警察失缓冲时间（防抖动）
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self.TIME_THRESHOLD_PRISONER = 1.0 # 犯人判定时长
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self.TIME_TOLERANCE_PRISONER = 1.0 # 犯人丢失缓冲时间（防抖动）
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# 警察检测帧数阈值
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self.frame_thresh_police = int(self.TIME_THRESHOLD_POLICE * self.fps)
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self.frame_buffer_police = int(self.TIME_TOLERANCE_POLICE * self.fps)
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# 犯人检测帧数阈值
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self.frame_thresh_prisoner = int(self.TIME_THRESHOLD_PRISONER * self.fps)
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self.frame_buffer_prisoner = int(self.TIME_TOLERANCE_PRISONER * self.fps)
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logger.debug(f"\n超参数设置:")
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logger.debug(f" FPS: {self.fps:.2f}")
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logger.debug(f" 判定 'police Detected' 需累计检测: {self.frame_thresh_police} 帧")
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logger.debug(f" 警察丢失缓冲帧数: {self.frame_buffer_police} 帧")
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logger.debug(f" 判定 'prisoner Detected' 需累计检测: {self.frame_thresh_prisoner} 帧")
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logger.debug(f" 犯人丢失缓冲帧数: {self.frame_buffer_prisoner} 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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# 警察检测状态变量
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self.police_detection_frames = 0 # 连续检测到警察的帧数
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self.police_missing_frames = 0 # 连续未检测到警察的帧数
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self.police_alert_active = False # 警察报警是否激活
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# 犯人检测状态变量
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self.prisoner_detection_frames = 0 # 连续检测到犯人的帧数
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self.prisoner_missing_frames = 0 # 连续未检测到犯人的帧数
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self.prisoner_alert_active = False # 犯人报警是否激活
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# =========================
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# 区域 ROI + 状态机初始化（修改为单一区域）
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# =========================
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# ⚠️ 改为相对坐标（0-1区间），按 [x, y] 格式，x/y 范围 0~1
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# 示例：原 (50,100) 在 960x480 分辨率下 → x=50/960≈0.052, y=100/480≈0.208
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# ROI 处理：优先从 params 获取，否则使用默认值 DEFAULT_ROI_RELATIVE
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roi_points = self.params.get('roi_points', DEFAULT_ROI_RELATIVE)
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self.route_rois = [
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{
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"name": "zone", # 单一区域，犯人离开即报警
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"polygon_rel": roi_points # 相对坐标，从params获取或使用默认值
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}
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]
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# 帧尺寸（动态更新）
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self.width = 0
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self.height = 0
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logger.debug(f"相对坐标 ROI: {self.route_rois}")
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# 每个犯人（track_id）一套状态
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self.prisoner_route_state = {}
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# 新增：记录所有曾经出现过的犯人track_id及其状态
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self.all_prisoner_tracks = {}
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# 新增：记录已触发违规的track_id，避免重复告警
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self.violated_tracks = set()
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def _get_abs_polygon(self, rel_polygon):
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"""将相对坐标(0-1)转换为绝对像素坐标"""
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return [
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(int(x * self.width), int(y * self.height))
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for x, y in rel_polygon
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]
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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(boxB[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 _point_in_polygon(self, point, polygon):
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"""
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判断点是否在多边形内
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polygon: 绝对像素坐标的多边形
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"""
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return cv2.pointPolygonTest(
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np.array(polygon, dtype=np.int32),
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point,
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False
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) >= 0
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def _draw_route_rois(self, frame):
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"""
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在画面中绘制路线 ROI（动态转换为绝对坐标）
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"""
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for idx, roi in enumerate(self.route_rois):
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# 相对坐标转绝对坐标
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abs_polygon = self._get_abs_polygon(roi["polygon_rel"])
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pts = np.array(abs_polygon, np.int32).reshape((-1, 1, 2))
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# ROI 边框
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cv2.polylines(
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frame,
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[pts],
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isClosed=True,
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color=(0, 255, 255),
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thickness=2
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)
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# 标注名称
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text_pos = abs_polygon[0]
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cv2.putText(
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frame,
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f"{idx + 1}:{roi['name']}",
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(text_pos[0], text_pos[1] - 5),
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cv2.FONT_HERSHEY_SIMPLEX,
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0.7,
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(0, 255, 255),
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2
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)
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def _update_prisoner_route(self, tid, point, timestamp):
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"""
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区域监控状态机（修改为单一区域）：
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只监控一个区域，如果犯人进入过该区域，后来离开（连续多帧不在区域内或消失），则触发违规。
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"""
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# 初始化状态
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if tid not in self.prisoner_route_state:
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self.prisoner_route_state[tid] = {
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"entered_zone": False, # 是否曾进入区域
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"in_zone": False, # 当前是否在区域内
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"out_frames": 0, # 连续不在区域内的帧数
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"violation": False, # 是否已触发离开违规
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"last_seen": timestamp # 最后出现时间
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}
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# 记录所有犯人track
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self.all_prisoner_tracks[tid] = self.prisoner_route_state[tid]
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state = self.prisoner_route_state[tid]
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state["last_seen"] = timestamp
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# 如果已经触发违规，不再处理（可保留但不重复触发）
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if state["violation"]:
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return
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# 获取当前唯一区域的多边形（绝对坐标）
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current_roi_rel = self.route_rois[0]["polygon_rel"]
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current_roi_abs = self._get_abs_polygon(current_roi_rel)
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# 判断点是否在区域内
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in_zone = self._point_in_polygon(point, current_roi_abs)
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if in_zone:
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# 在区域内
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state["in_zone"] = True
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state["out_frames"] = 0
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if not state["entered_zone"]:
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state["entered_zone"] = True
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else:
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# 不在区域内
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if state["entered_zone"]:
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# 曾进入过区域，开始计数离开帧数
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state["out_frames"] += 1
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# 如果离开帧数超过阈值，触发违规
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# 使用 frame_buffer_prisoner 作为离开判定缓冲（可自定义）
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if state["out_frames"] >= self.frame_buffer_prisoner:
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state["violation"] = True
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state["in_zone"] = False
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# 如果还未进入区域，忽略
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def _check_prisoner_violation(self, current_time):
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"""
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检查消失的犯人是否违规（离开区域）：
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1. 曾进入过区域
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2. 未触发过违规
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3. 已经消失（超过track buffer时间）
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"""
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violations = []
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# 遍历所有曾经出现过的犯人track
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for tid, state in list(self.all_prisoner_tracks.items()):
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# 跳过已违规或未进入区域的track
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if state["violation"] or not state["entered_zone"]:
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continue
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# 检查是否已消失（超过track buffer时间，这里用2秒作为消失判定）
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if current_time - state["last_seen"] > 2.0 and tid not in self.violated_tracks:
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state["violation"] = True
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self.violated_tracks.add(tid)
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violations.append({
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'time': current_time,
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'action': 'violation',
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'confidence': 1.0,
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'details': "Prisoner left zone (disappeared)"
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})
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return violations
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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 # 更新帧尺寸
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self.current_frame_idx += 1
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current_time_sec = timestamp
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# ========= 警察和犯人检测 =========
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police_prisoner_results = self.police_prisoner_detector(frame)
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police_prisoner_dets_xyxy = []
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police_prisoner_dets_roles = []
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police_prisoner_dets_for_tracker = []
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# ========= 当前帧所有警告列表 ==========
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current_frame_alerts = [] # 每帧清空，重新收集
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if police_prisoner_results:
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for det in police_prisoner_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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police_prisoner_dets_xyxy.append([x1, y1, x2, y2])
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police_prisoner_dets_for_tracker.append([x1, y1, x2, y2, conf])
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if cls_id == 0:
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police_prisoner_dets_roles.append("police")
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elif cls_id == 1:
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police_prisoner_dets_roles.append("prisoner")
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ppolice_prisoner_dets = np.array(police_prisoner_dets_for_tracker, dtype=np.float32) if len(
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police_prisoner_dets_for_tracker) else np.empty((0, 5))
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police_prisoner_dets_tracks = self.tracker.update(
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ppolice_prisoner_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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# 重置当前帧的犯人track标记
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current_frame_prisoner_tids = set()
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# ========= 单帧统计变量 =========
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current_police_count = 0
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current_prisoner_count = 0
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# ========= 警察和犯人检测 =========
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for t in police_prisoner_dets_tracks:
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tid = t.track_id
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# IoU 匹配角色
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REVALIDATE_FRAME_INTERVAL = 10
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if (self.current_frame_idx % REVALIDATE_FRAME_INTERVAL == 0) or (
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tid not in self.police_prisoner_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(police_prisoner_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 = police_prisoner_dets_roles[i]
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if best_iou > 0.1:
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self.police_prisoner_track_role[tid] = best_role
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else:
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self.police_prisoner_track_role[tid] = "unknown"
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role = self.police_prisoner_track_role.get(tid, "unknown")
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cls_id = -1
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if role == "police":
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cls_id = 0
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elif role == "prisoner":
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cls_id = 1
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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: # police
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current_police_count += 1
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color = (255, 0, 255)
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label = "police"
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elif cls_id == 1: # prisoner
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current_prisoner_count += 1
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color = (0, 0, 139)
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label = "prisoner"
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current_frame_prisoner_tids.add(tid)
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# ===== 区域状态机更新 =====
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self._update_prisoner_route(
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tid=tid,
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point=(cx, cy),
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timestamp=current_time_sec
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)
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else:
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color = (255, 255, 255)
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label = "Unknown"
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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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# 检查犯人违规（进入区域后离开）
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# ==========================================
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violation_alerts = self._check_prisoner_violation(current_time_sec)
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# 遍历所有状态，收集刚刚触发的 violation（那些在更新中被标记但尚未加入 violated_tracks 的）
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for tid, state in self.prisoner_route_state.items():
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if state["violation"] and tid not in self.violated_tracks:
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self.violated_tracks.add(tid)
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violation_alerts.append({
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'time': current_time_sec,
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'action': 'violation',
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'confidence': 1.0,
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'details': "Prisoner left zone"
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})
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current_frame_alerts.extend(violation_alerts)
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# ==========================================
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# 犯人检测
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# ==========================================
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if current_prisoner_count > 0:
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self.prisoner_detection_frames += 1
|
||
self.prisoner_missing_frames = 0
|
||
if self.prisoner_detection_frames >= self.frame_thresh_prisoner:
|
||
self.prisoner_alert_active = True
|
||
else:
|
||
self.prisoner_missing_frames += 1
|
||
if self.prisoner_detection_frames > 0:
|
||
if self.prisoner_missing_frames >= self.frame_buffer_prisoner:
|
||
self.prisoner_detection_frames = 0
|
||
self.prisoner_alert_active = False
|
||
|
||
# ==========================================
|
||
# 警察检测
|
||
# ==========================================
|
||
if current_police_count > 0:
|
||
self.police_detection_frames += 1
|
||
self.police_missing_frames = 0
|
||
if self.police_detection_frames >= self.frame_thresh_police:
|
||
self.police_alert_active = True
|
||
else:
|
||
self.police_missing_frames += 1
|
||
if self.police_detection_frames > 0:
|
||
if self.police_missing_frames >= self.frame_buffer_police:
|
||
self.police_detection_frames = 0
|
||
self.police_alert_active = False
|
||
|
||
alert_offset = 0
|
||
|
||
# A. 有犯人
|
||
if self.prisoner_alert_active:
|
||
duration_seconds = self.prisoner_detection_frames / self.fps
|
||
current_frame_alerts.append(
|
||
{
|
||
'time': current_time_sec,
|
||
'action': 'prisoner',
|
||
'confidence': 1.0,
|
||
'details': f"Detected for {duration_seconds:.1f}s"
|
||
}
|
||
)
|
||
self.draw_alert(frame, "prisoner", (0, 0, 255), offset_y=alert_offset)
|
||
alert_offset += 100
|
||
|
||
# C. 区域违规告警（离开区域）
|
||
for violation in violation_alerts:
|
||
self.draw_alert(frame, "ZONE VIOLATION!", (0, 0, 255),
|
||
sub_text=violation['details'], offset_y=alert_offset)
|
||
alert_offset += 100
|
||
|
||
# =========================
|
||
# 绘制区域 ROI（始终显示）
|
||
# =========================
|
||
self._draw_route_rois(frame)
|
||
|
||
return {
|
||
"image": frame,
|
||
"alerts": current_frame_alerts
|
||
}
|
||
|
||
|
||
# ========================= 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]]",
|
||
stop_event: threading.Event):
|
||
super().__init__(daemon=True)
|
||
self.raw_queue = raw_frame_queue
|
||
self.ws_queue = ws_send_queue
|
||
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.trajectory_detectors: Dict[int, TrajectoryDetector] = {}
|
||
|
||
# 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": 1,
|
||
"timestamp": ts,
|
||
"result_type": push_actions,
|
||
"image_base64": img_b64,
|
||
}
|
||
try:
|
||
self.ws_queue.put(msg, timeout=1.0)
|
||
# if push_actions and len(push_actions) > 0:
|
||
# self.ws_queue_2.put(msg, timeout=1.0)
|
||
except queue.Full:
|
||
logger.warning("[WARN] ws_send_queue full, drop frame message")
|
||
|
||
except Exception as e:
|
||
logger.error(
|
||
f"[ERROR] Frame processing failed for camera {cam_id if 'cam_id' in locals() else 'unknown'}: {e}")
|
||
logger.exception("Exception details:") # 打印完整的堆栈跟踪
|
||
# 继续处理下一帧，不要退出循环
|
||
finally:
|
||
self.raw_queue.task_done()
|