7aa71c5f83
本次提交实现了完整的人员行为分析系统，包括： 1. 新增基于位置和跟踪ID的两种行为检测算法 2. 新增徘徊检测服务与行为处理器模块 3. 前后端集成算法配置界面与告警展示 4. 支持图片和视频流场景下的行为分析 5. 新增算法配置接口与文档说明 具体改动： - 新增loitering_detection模型目录与算法实现 - 新增AlgorithmConfig组件实现可视化配置 - 扩展图片/视频检测接口支持算法参数传递 - 新增行为告警推送与前端展示页面 - 优化检测服务，集成行为分析逻辑 - 移除冗余日志输出，完善代码注释
252 lines
8.2 KiB
Python
252 lines
8.2 KiB
Python
"""
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基于跟踪ID的徘徊检测算法
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依赖跟踪ID，适用于跟踪稳定的场景
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"""
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import time
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from typing import Dict, List, Tuple, Optional
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from dataclasses import dataclass, field
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from collections import defaultdict
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@dataclass
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class PersonTrack:
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"""人员跟踪记录"""
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person_id: int
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first_seen: float
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last_seen: float
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positions: List[Tuple[int, int]] = field(default_factory=list)
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last_position: Optional[Tuple[int, int]] = None
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stationary_start: Optional[float] = None
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total_duration: float = 0.0
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stationary_duration: float = 0.0
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class LoiteringDetector:
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"""
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徘徊检测器（基于跟踪ID）
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特点：
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- 依赖跟踪 ID，需要稳定的跟踪器
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- 可以检测长时间停留（徘徊）
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- 可以检测静止不动（静止）
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"""
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def __init__(
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self,
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loitering_threshold: float = 300.0, # 徘徊阈值（秒），默认5分钟
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stationary_threshold: float = 2.0, # 静止阈值（秒）
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movement_threshold: float = 5.0, # 移动阈值（像素）
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cleanup_interval: float = 10.0 # 清理间隔（秒）
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):
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self.loitering_threshold = loitering_threshold
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self.stationary_threshold = stationary_threshold
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self.movement_threshold = movement_threshold
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self.cleanup_interval = cleanup_interval
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# 跟踪记录: {person_id: PersonTrack}
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self._tracks: Dict[int, PersonTrack] = {}
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self._last_cleanup = time.time()
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def _cleanup_old_tracks(self, max_age: float = 60.0) -> int:
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"""清理长时间未更新的跟踪记录"""
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current_time = time.time()
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to_remove = [
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pid for pid, track in self._tracks.items()
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if current_time - track.last_seen > max_age
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]
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for pid in to_remove:
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del self._tracks[pid]
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return len(to_remove)
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def update(
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self,
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person_id: int,
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position: Tuple[int, int]
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) -> Tuple[bool, float, bool, float]:
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"""
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更新人员位置
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Args:
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person_id: 人员ID
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position: (x, y) 中心点坐标
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Returns:
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is_loitering: 是否徘徊超过阈值
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loitering_duration: 徘徊时长（秒）
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is_stationary: 是否静止超过阈值
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stationary_duration: 静止时长（秒）
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"""
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current_time = time.time()
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# 定期清理
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if current_time - self._last_cleanup > self.cleanup_interval:
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self._cleanup_old_tracks()
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self._last_cleanup = current_time
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# 获取或创建跟踪记录
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if person_id not in self._tracks:
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self._tracks[person_id] = PersonTrack(
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person_id=person_id,
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first_seen=current_time,
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last_seen=current_time,
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last_position=position
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)
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return False, 0.0, False, 0.0
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track = self._tracks[person_id]
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track.last_seen = current_time
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track.positions.append(position)
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# 计算总停留时长
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track.total_duration = current_time - track.first_seen
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# 检查是否移动
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is_moving = False
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if track.last_position is not None:
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distance = ((position[0] - track.last_position[0]) ** 2 +
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(position[1] - track.last_position[1]) ** 2) ** 0.5
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is_moving = distance > self.movement_threshold
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track.last_position = position
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# 更新静止状态
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if is_moving:
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# 如果移动了，重置静止计时
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track.stationary_start = None
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track.stationary_duration = 0.0
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else:
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# 如果没移动，更新静止时长
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if track.stationary_start is None:
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track.stationary_start = current_time
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track.stationary_duration = current_time - track.stationary_start
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# 判断是否徘徊/静止
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is_loitering = track.total_duration > self.loitering_threshold
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is_stationary = track.stationary_duration > self.stationary_threshold
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return (
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is_loitering,
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track.total_duration,
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is_stationary,
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track.stationary_duration
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)
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def detect(
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self,
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detections: List[Dict],
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id_key: str = 'track_id'
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) -> List[Dict]:
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"""
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批量检测徘徊状态
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Args:
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detections: 检测结果列表，每项包含 'bbox' 和 track_id
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id_key: 跟踪ID的字段名
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Returns:
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添加 'loitering_info' 字段的检测结果
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"""
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results = []
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for det in detections:
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person_id = det.get(id_key)
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if person_id is None:
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results.append(det)
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continue
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x1, y1, x2, y2 = det['bbox']
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center = ((x1 + x2) // 2, (y1 + y2) // 2)
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is_loitering, loitering_duration, is_stationary, stationary_duration = \
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self.update(person_id, center)
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det_copy = det.copy()
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det_copy['loitering_info'] = {
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'person_id': person_id,
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'is_loitering': is_loitering,
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'loitering_duration': round(loitering_duration, 2),
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'is_stationary': is_stationary,
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'stationary_duration': round(stationary_duration, 2),
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'loitering_threshold': self.loitering_threshold,
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'stationary_threshold': self.stationary_threshold
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}
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results.append(det_copy)
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return results
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def get_all_loitering(
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self,
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threshold: Optional[float] = None
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) -> List[Dict]:
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"""
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获取所有徘徊超过阈值的人员
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Args:
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threshold: 徘徊阈值（秒），默认使用初始化时的阈值
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Returns:
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list: [{person_id, duration, positions}, ...]
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"""
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threshold = threshold or self.loitering_threshold
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result = []
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for person_id, track in self._tracks.items():
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if track.total_duration > threshold:
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result.append({
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'person_id': person_id,
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'duration': track.total_duration,
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'positions': track.positions.copy(),
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'is_stationary': track.stationary_duration > self.stationary_threshold,
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'stationary_duration': track.stationary_duration
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})
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# 按时长排序
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result.sort(key=lambda x: x['duration'], reverse=True)
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return result
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def get_all_stationary(
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self,
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threshold: Optional[float] = None
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) -> List[Dict]:
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"""
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获取所有静止超过阈值的人员
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Args:
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threshold: 静止阈值（秒），默认使用初始化时的阈值
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Returns:
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list: [{person_id, duration, position}, ...]
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"""
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threshold = threshold or self.stationary_threshold
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result = []
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for person_id, track in self._tracks.items():
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if track.stationary_duration > threshold:
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result.append({
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'person_id': person_id,
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'duration': track.stationary_duration,
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'position': track.last_position,
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'total_duration': track.total_duration
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})
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result.sort(key=lambda x: x['duration'], reverse=True)
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return result
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def reset(self):
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"""重置所有跟踪数据"""
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self._tracks.clear()
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self._last_cleanup = time.time()
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def get_stats(self) -> Dict:
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"""获取统计信息"""
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return {
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'total_tracks': len(self._tracks),
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'loitering_count': len(self.get_all_loitering()),
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'stationary_count': len(self.get_all_stationary()),
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'loitering_threshold': self.loitering_threshold,
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'stationary_threshold': self.stationary_threshold
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}
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