feat: 添加摄像头配置与状态同步功能

api/sync.py

@@ -0,0 +1,116 @@
+from fastapi import APIRouter, Depends
+from sqlalchemy.orm import Session
+from typing import List, Optional
+
+from db.models import get_db
+from services.sync_service import get_sync_service
+
+router = APIRouter(prefix="/api/sync", tags=["同步"])
+
+
+@router.get("/status")
+def get_sync_status(db: Session = Depends(get_db)):
+    """获取同步服务状态"""
+    from sqlalchemy import text
+
+    service = get_sync_service()
+    status = service.get_status()
+
+    pending_cameras = db.execute(
+        text("SELECT COUNT(*) FROM cameras WHERE pending_sync = 1")
+    ).scalar() or 0
+
+    pending_rois = db.execute(
+        text("SELECT COUNT(*) FROM rois WHERE pending_sync = 1")
+    ).scalar() or 0
+
+    pending_alarms = db.execute(
+        text("SELECT COUNT(*) FROM alarms WHERE upload_status = 'pending' OR upload_status = 'retry'")
+    ).scalar() or 0
+
+    return {
+        "running": status["running"],
+        "cloud_enabled": status["cloud_enabled"],
+        "network_status": status["network_status"],
+        "device_id": status["device_id"],
+        "pending_sync": pending_cameras + pending_rois,
+        "pending_alarms": pending_alarms,
+        "details": {
+            "pending_cameras": pending_cameras,
+            "pending_rois": pending_rois,
+            "pending_alarms": pending_alarms
+        }
+    }
+
+
+@router.get("/pending")
+def get_pending_syncs(db: Session = Depends(get_db)):
+    """获取待同步项列表"""
+    from sqlalchemy import text
+    from db.models import Camera, ROI, Alarm
+
+    pending_cameras = db.query(Camera).filter(Camera.pending_sync == True).all()
+    pending_rois = db.query(ROI).filter(ROI.pending_sync == True).all()
+
+    from db.session import SessionLocal
+    temp_db = SessionLocal()
+    try:
+        pending_alarms = temp_db.query(Alarm).filter(
+            Alarm.upload_status.in_(['pending', 'retry'])
+        ).limit(100).all()
+    finally:
+        temp_db.close()
+
+    return {
+        "cameras": [{"id": c.id, "name": c.name} for c in pending_cameras],
+        "rois": [{"id": r.id, "name": r.name, "camera_id": r.camera_id} for r in pending_rois],
+        "alarms": [{"id": a.id, "camera_id": a.camera_id, "type": a.event_type} for a in pending_alarms]
+    }
+
+
+@router.post("/trigger")
+def trigger_sync():
+    """手动触发同步"""
+    service = get_sync_service()
+    from db.session import SessionLocal
+    from db.crud import get_all_cameras, get_all_rois
+    from db.models import Camera, ROI
+
+    db = SessionLocal()
+    try:
+        cameras = get_all_cameras(db)
+        for camera in cameras:
+            service.queue_camera_sync(camera.id, 'update', {
+                'name': camera.name,
+                'rtsp_url': camera.rtsp_url,
+                'enabled': camera.enabled
+            })
+            db.query(Camera).filter(Camera.id == camera.id).update({'pending_sync': False})
+            db.commit()
+
+        rois = get_all_rois(db)
+        for roi in rois:
+            service.queue_roi_sync(roi.id, 'update', {
+                'name': roi.name,
+                'roi_type': roi.roi_type,
+                'points': roi.points,
+                'enabled': roi.enabled
+            })
+            db.query(ROI).filter(ROI.id == roi.id).update({'pending_sync': False})
+            db.commit()
+
+        return {"message": "同步任务已加入队列", "count": len(cameras) + len(rois)}
+    finally:
+        db.close()
+
+
+@router.post("/clear-failed")
+def clear_failed_syncs(db: Session = Depends(get_db)):
+    """清除失败的同步标记"""
+    from sqlalchemy import text
+
+    db.execute(text("UPDATE cameras SET pending_sync = 0, sync_failed_at = NULL, sync_retry_count = 0"))
+    db.execute(text("UPDATE rois SET pending_sync = 0, sync_failed_at = NULL, sync_retry_count = 0"))
+    db.commit()
+
+    return {"message": "已清除所有失败的同步标记"}

services/sync_service.py

@@ -0,0 +1,461 @@
+"""
+云端同步服务
+
+实现"云端为主、本地为辅"的双层数据存储架构：
+- 配置双向同步
+- 报警单向上报
+- 设备状态上报
+- 断网容错机制
+"""
+
+import os
+import sys
+import time
+import threading
+import logging
+from datetime import datetime
+from typing import Optional, List, Dict, Any
+from queue import Queue, Empty
+from dataclasses import dataclass
+from enum import Enum
+
+import requests
+from sqlalchemy.orm import Session
+
+# 添加项目根目录到路径
+project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+sys.path.insert(0, project_root)
+
+from config import get_config
+
+logger = logging.getLogger(__name__)
+
+
+class SyncStatus(Enum):
+    """同步状态"""
+    PENDING = "pending"
+    SYNCING = "syncing"
+    SUCCESS = "success"
+    FAILED = "failed"
+    RETRY = "retry"
+
+
+class EntityType(Enum):
+    """实体类型"""
+    CAMERA = "camera"
+    ROI = "roi"
+    ALARM = "alarm"
+    STATUS = "status"
+
+
+@dataclass
+class SyncTask:
+    """同步任务"""
+    entity_type: EntityType
+    entity_id: int
+    operation: str  # create, update, delete
+    data: Optional[Dict[str, Any]] = None
+    status: SyncStatus = SyncStatus.PENDING
+    retry_count: int = 0
+    error_message: Optional[str] = None
+    created_at: datetime = None
+
+    def __post_init__(self):
+        if self.created_at is None:
+            self.created_at = datetime.utcnow()
+
+
+class CloudAPIClient:
+    """云端 API 客户端"""
+
+    def __init__(self, base_url: str, api_key: str, device_id: str):
+        self.base_url = base_url.rstrip('/')
+        self.api_key = api_key
+        self.device_id = device_id
+        self.session = requests.Session()
+        self.session.headers.update({
+            'Authorization': f'Bearer {api_key}',
+            'Content-Type': 'application/json',
+            'X-Device-ID': device_id
+        })
+
+    def request(self, method: str, path: str, **kwargs) -> requests.Response:
+        """发送 API 请求"""
+        url = f"{self.base_url}{path}"
+        response = self.session.request(method, url, **kwargs)
+        response.raise_for_status()
+        return response
+
+    def get(self, path: str, **kwargs):
+        return self.request('GET', path, **kwargs)
+
+    def post(self, path: str, **kwargs):
+        return self.request('POST', path, **kwargs)
+
+    def put(self, path: str, **kwargs):
+        return self.request('PUT', path, **kwargs)
+
+    def delete(self, path: str, **kwargs):
+        return self.request('DELETE', path, **kwargs)
+
+
+class SyncService:
+    """云端同步服务"""
+
+    def __init__(self):
+        config = get_config()
+        self.config = config
+
+        # 云端配置
+        self.cloud_enabled = config.cloud.enabled
+        self.cloud_url = config.cloud.api_url
+        self.api_key = config.cloud.api_key
+        self.device_id = config.cloud.device_id
+
+        # 同步配置
+        self.sync_interval = config.cloud.sync_interval
+        self.alarm_retry_interval = config.cloud.alarm_retry_interval
+        self.status_report_interval = config.cloud.status_report_interval
+        self.max_retries = config.cloud.max_retries
+
+        # 客户端
+        self.client: Optional[CloudAPIClient] = None
+        if self.cloud_enabled:
+            self.client = CloudAPIClient(
+                self.cloud_url,
+                self.api_key,
+                self.device_id
+            )
+
+        # 任务队列
+        self.sync_queue: Queue = Queue()
+        self.alarm_queue: Queue = Queue()
+
+        # 状态
+        self.running = False
+        self.threads: List[threading.Thread] = []
+        self.network_status = "disconnected"
+
+        # 重试配置
+        self.retry_delays = [60, 300, 900, 3600]  # 1分钟, 5分钟, 15分钟, 1小时
+
+    def start(self):
+        """启动同步服务"""
+        if self.running:
+            logger.warning("同步服务已在运行")
+            return
+
+        self.running = True
+
+        if self.cloud_enabled:
+            logger.info(f"启动云端同步服务，设备ID: {self.device_id}")
+        else:
+            logger.info("云端同步已禁用，使用本地模式")
+
+        # 启动工作线程
+        self.threads.append(threading.Thread(target=self._sync_worker, daemon=True))
+        self.threads.append(threading.Thread(target=self._alarm_worker, daemon=True))
+        self.threads.append(threading.Thread(target=self._status_worker, daemon=True))
+
+        for thread in self.threads:
+            thread.start()
+
+        logger.info("同步服务已启动")
+
+    def stop(self):
+        """停止同步服务"""
+        self.running = False
+
+        for thread in self.threads:
+            if thread.is_alive():
+                thread.join(timeout=5)
+
+        logger.info("同步服务已停止")
+
+    def _sync_worker(self):
+        """配置同步工作线程"""
+        while self.running:
+            try:
+                task = self.sync_queue.get(timeout=1)
+                self._execute_sync(task)
+            except Empty:
+                self._check_network_status()
+            except Exception as e:
+                logger.error(f"同步工作线程异常: {e}")
+
+    def _alarm_worker(self):
+        """报警上报工作线程"""
+        while self.running:
+            try:
+                alarm_id = self.alarm_queue.get(timeout=1)
+                self._upload_alarm(alarm_id)
+            except Empty:
+                continue
+            except Exception as e:
+                logger.error(f"报警上报工作线程异常: {e}")
+
+    def _status_worker(self):
+        """状态上报工作线程"""
+        while self.running:
+            try:
+                if self.network_status == "connected":
+                    self._report_status()
+            except Exception as e:
+                logger.error(f"状态上报失败: {e}")
+            time.sleep(self.status_report_interval)
+
+    def _check_network_status(self):
+        """检查网络状态"""
+        if not self.cloud_enabled:
+            self.network_status = "disabled"
+            return
+
+        try:
+            self.client.get('/health')
+            self.network_status = "connected"
+        except:
+            self.network_status = "disconnected"
+
+    def _execute_sync(self, task: SyncTask):
+        """执行同步任务"""
+        logger.info(f"执行同步任务: {task.entity_type.value}/{task.entity_id} ({task.operation})")
+
+        task.status = SyncStatus.SYNCING
+
+        try:
+            if task.entity_type == EntityType.CAMERA:
+                self._sync_camera(task)
+            elif task.entity_type == EntityType.ROI:
+                self._sync_roi(task)
+
+            task.status = SyncStatus.SUCCESS
+            logger.info(f"同步成功: {task.entity_type.value}/{task.entity_id}")
+
+        except requests.exceptions.RequestException as e:
+            self._handle_sync_error(task, str(e))
+        except Exception as e:
+            task.status = SyncStatus.FAILED
+            task.error_message = str(e)
+            logger.error(f"同步失败: {task.entity_type.value}/{task.entity_id}: {e}")
+
+    def _handle_sync_error(self, task: SyncTask, error: str):
+        """处理同步错误"""
+        task.retry_count += 1
+
+        if task.retry_count < self.max_retries:
+            task.status = SyncStatus.RETRY
+            delay = self.retry_delays[task.retry_count - 1]
+            task.error_message = f"第{task.retry_count}次失败: {error}"
+            logger.warning(f"同步重试 ({task.retry_count}/{self.max_retries}): {task.entity_type.value}/{task.entity_id}")
+            # 重新入队
+            time.sleep(delay)
+            self.sync_queue.put(task)
+        else:
+            task.status = SyncStatus.FAILED
+            task.error_message = f"已超过最大重试次数: {error}"
+            logger.error(f"同步失败，已达最大重试次数: {task.entity_type.value}/{task.entity_id}")
+
+    def _sync_camera(self, task: SyncTask):
+        """同步摄像头配置"""
+        if task.operation == 'update':
+            self.client.put(f"/api/v1/cameras/{task.entity_id}", json=task.data)
+        elif task.operation == 'delete':
+            self.client.delete(f"/api/v1/cameras/{task.entity_id}")
+
+    def _sync_roi(self, task: SyncTask):
+        """同步 ROI 配置"""
+        if task.operation == 'update':
+            self.client.put(f"/api/v1/rois/{task.entity_id}", json=task.data)
+        elif task.operation == 'delete':
+            self.client.delete(f"/api/v1/rois/{task.entity_id}")
+
+    def _upload_alarm(self, alarm_id: int):
+        """上传报警记录"""
+        from db.crud import get_alarm_by_id, update_alarm_status
+        from db.models import get_session_factory
+
+        SessionLocal = get_session_factory()
+        db = SessionLocal()
+
+        try:
+            alarm = get_alarm_by_id(db, alarm_id)
+            if not alarm:
+                logger.warning(f"报警记录不存在: {alarm_id}")
+                return
+
+            # 准备数据
+            alarm_data = {
+                'device_id': self.device_id,
+                'camera_id': alarm.camera_id,
+                'alarm_type': alarm.event_type,
+                'confidence': alarm.confidence,
+                'timestamp': alarm.created_at.isoformat() if alarm.created_at else None,
+                'region': alarm.region_data
+            }
+
+            # 上传图片
+            if alarm.snapshot_path and os.path.exists(alarm.snapshot_path):
+                with open(alarm.snapshot_path, 'rb') as f:
+                    files = {'file': f}
+                    response = self.client.post('/api/v1/alarms/images', files=files)
+                    alarm_data['image_url'] = response.json().get('data', {}).get('url')
+
+            # 上报报警
+            response = self.client.post('/api/v1/alarms/report', json=alarm_data)
+            cloud_id = response.json().get('data', {}).get('alarm_id')
+
+            # 更新本地状态
+            update_alarm_status(db, alarm_id, status='uploaded', cloud_id=cloud_id)
+            logger.info(f"报警上报成功: {alarm_id} -> 云端ID: {cloud_id}")
+
+        except requests.exceptions.RequestException as e:
+            update_alarm_status(db, alarm_id, status='retry', error_message=str(e))
+            self.alarm_queue.put(alarm_id)  # 重试
+        except Exception as e:
+            update_alarm_status(db, alarm_id, status='failed', error_message=str(e))
+            logger.error(f"报警处理失败: {alarm_id}: {e}")
+        finally:
+            db.close()
+
+    def _report_status(self):
+        """上报设备状态"""
+        import psutil
+        from db.crud import get_active_camera_count
+
+        try:
+            metrics = {
+                'device_id': self.device_id,
+                'cpu_percent': psutil.cpu_percent(),
+                'memory_percent': psutil.virtual_memory().percent,
+                'disk_usage': psutil.disk_usage('/').percent,
+                'timestamp': datetime.utcnow().isoformat()
+            }
+
+            self.client.post('/api/v1/devices/status', json=metrics)
+            logger.debug(f"设备状态上报成功: CPU={metrics['cpu_percent']}%")
+        except requests.exceptions.RequestException as e:
+            logger.warning(f"设备状态上报失败: {e}")
+
+    # 公共接口
+
+    def queue_camera_sync(self, camera_id: int, operation: str = 'update', data: Dict[str, Any] = None):
+        """将摄像头同步加入队列"""
+        task = SyncTask(
+            entity_type=EntityType.CAMERA,
+            entity_id=camera_id,
+            operation=operation,
+            data=data
+        )
+        self.sync_queue.put(task)
+
+    def queue_roi_sync(self, roi_id: int, operation: str = 'update', data: Dict[str, Any] = None):
+        """将 ROI 同步加入队列"""
+        task = SyncTask(
+            entity_type=EntityType.ROI,
+            entity_id=roi_id,
+            operation=operation,
+            data=data
+        )
+        self.sync_queue.put(task)
+
+    def queue_alarm_upload(self, alarm_id: int):
+        """将报警上传加入队列"""
+        self.alarm_queue.put(alarm_id)
+
+    def sync_config_from_cloud(self, db: Session) -> Dict[str, int]:
+        """从云端拉取配置"""
+        result = {'cameras': 0, 'rois': 0}
+
+        if not self.cloud_enabled:
+            logger.info("云端同步已禁用，跳过配置拉取")
+            return result
+
+        try:
+            logger.info("从云端拉取配置...")
+
+            # 拉取设备配置
+            response = self.client.get(f"/api/v1/devices/{self.device_id}/config")
+            config = response.json().get('data', {})
+
+            # 处理摄像头
+            cameras = config.get('cameras', [])
+            for cloud_cam in cameras:
+                self._merge_camera(db, cloud_cam)
+                result['cameras'] += 1
+
+            logger.info(f"从云端拉取配置完成: {result['cameras']} 个摄像头")
+
+        except requests.exceptions.RequestException as e:
+            logger.error(f"从云端拉取配置失败: {e}")
+        except Exception as e:
+            logger.error(f"处理云端配置时出错: {e}")
+
+        return result
+
+    def _merge_camera(self, db: Session, cloud_data: Dict[str, Any]):
+        """合并摄像头配置"""
+        from db.crud import get_camera_by_cloud_id, create_camera, update_camera
+        from db.models import Camera
+
+        cloud_id = cloud_data.get('id')
+        existing = get_camera_by_cloud_id(db, cloud_id)
+
+        if existing:
+            # 更新现有记录
+            if not existing.pending_sync:
+                update_camera(db, existing.id, {
+                    'name': cloud_data.get('name'),
+                    'rtsp_url': cloud_data.get('rtsp_url'),
+                    'enabled': cloud_data.get('enabled', True),
+                    'fps_limit': cloud_data.get('fps_limit', 30),
+                    'process_every_n_frames': cloud_data.get('process_every_n_frames', 3),
+                })
+        else:
+            # 创建新记录
+            camera = create_camera(db, {
+                'name': cloud_data.get('name'),
+                'rtsp_url': cloud_data.get('rtsp_url'),
+                'enabled': cloud_data.get('enabled', True),
+                'fps_limit': cloud_data.get('fps_limit', 30),
+                'process_every_n_frames': cloud_data.get('process_every_n_frames', 3),
+            })
+            # 更新 cloud_id
+            camera.cloud_id = cloud_id
+            db.commit()
+
+    def get_status(self) -> Dict[str, Any]:
+        """获取同步服务状态"""
+        return {
+            'running': self.running,
+            'cloud_enabled': self.cloud_enabled,
+            'network_status': self.network_status,
+            'device_id': self.device_id,
+            'pending_sync': self.sync_queue.qsize(),
+            'pending_alarms': self.alarm_queue.qsize(),
+        }
+
+
+# 单例
+_sync_service: Optional[SyncService] = None
+
+
+def get_sync_service() -> SyncService:
+    """获取同步服务单例"""
+    global _sync_service
+    if _sync_service is None:
+        _sync_service = SyncService()
+    return _sync_service
+
+
+def start_sync_service():
+    """启动同步服务"""
+    service = get_sync_service()
+    service.start()
+
+
+def stop_sync_service():
+    """停止同步服务"""
+    global _sync_service
+    if _sync_service:
+        _sync_service.stop()
+        _sync_service = None

sort.py

@@ -1,214 +0,0 @@
-import numpy as np
-from scipy.optimize import linear_sum_assignment
-from filterpy.kalman import KalmanFilter
-
-def linear_assignment(cost_matrix):
-    x, y = linear_sum_assignment(cost_matrix)
-    return np.array(list(zip(x, y)))
-
-def iou_batch(bb_test, bb_gt):
-    """
-    From SORT: Computes IOU between two bboxes in the form [x1,y1,x2,y2]
-    """
-    bb_test = np.expand_dims(bb_test, 1)
-    bb_gt = np.expand_dims(bb_gt, 0)
-    xx1 = np.maximum(bb_test[..., 0], bb_gt[..., 0])
-    yy1 = np.maximum(bb_test[..., 1], bb_gt[..., 1])
-    xx2 = np.minimum(bb_test[..., 2], bb_gt[..., 2])
-    yy2 = np.minimum(bb_test[..., 3], bb_gt[..., 3])
-    w = np.maximum(0., xx2 - xx1)
-    h = np.maximum(0., yy2 - yy1)
-    wh = w * h
-    o = wh / ((bb_test[..., 2] - bb_test[..., 0]) * (bb_test[..., 3] - bb_test[..., 1])
-              + (bb_gt[..., 2] - bb_gt[..., 0]) * (bb_gt[..., 3] - bb_gt[..., 1]) - wh)
-    return o
-
-def convert_bbox_to_z(bbox):
-    """
-    Takes a bounding box in the form [x1,y1,x2,y2] and returns z in the form
-      [x,y,s,r] where x,y is the centre of the box and s is the scale/area and r is
-      the aspect ratio
-    """
-    w = bbox[2] - bbox[0]
-    h = bbox[3] - bbox[1]
-    x = bbox[0] + w / 2.
-    y = bbox[1] + h / 2.
-    s = w * h  # scale is just area
-    r = w / float(h)
-    return np.array([x, y, s, r]).reshape((4, 1))
-
-def convert_x_to_bbox(x, score=None):
-    """
-    Takes a bounding box in the centre form [x,y,s,r] and returns it in the form
-      [x1,y1,x2,y2] where x1,y1 is the top left and x2,y2 is the bottom right
-    """
-    w = np.sqrt(x[2] * x[3])
-    h = x[2] / w
-    if score is None:
-        return np.array([x[0] - w / 2., x[1] - h / 2., x[0] + w / 2., x[1] + h / 2.]).reshape((1, 4))
-    else:
-        return np.array([x[0] - w / 2., x[1] - h / 2., x[0] + w / 2., x[1] + h / 2., score]).reshape((1, 5))
-
-class KalmanBoxTracker(object):
-    """
-    This class represents the internal state of individual tracked objects observed as bbox.
-    """
-    count = 0
-
-    def __init__(self, bbox):
-        """
-        Initialises a tracker using initial bounding box.
-        """
-        self.kf = KalmanFilter(dim_x=7, dim_z=4)
-        self.kf.F = np.array([[1, 0, 0, 0, 1, 0, 0],
-                              [0, 1, 0, 0, 0, 1, 0],
-                              [0, 0, 1, 0, 0, 0, 1],
-                              [0, 0, 0, 1, 0, 0, 0],
-                              [0, 0, 0, 0, 1, 0, 0],
-                              [0, 0, 0, 0, 0, 1, 0],
-                              [0, 0, 0, 0, 0, 0, 1]])
-        self.kf.H = np.array([[1, 0, 0, 0, 0, 0, 0],
-                              [0, 1, 0, 0, 0, 0, 0],
-                              [0, 0, 1, 0, 0, 0, 0],
-                              [0, 0, 0, 1, 0, 0, 0]])
-
-        self.kf.R[2:, 2:] *= 10.
-        self.kf.P[4:, 4:] *= 1000.  # give high uncertainty to the unobservable initial velocities
-        self.kf.P *= 10.
-        self.kf.Q[-1, -1] *= 0.01
-        self.kf.Q[4:, 4:] *= 0.01
-
-        self.kf.x[:4] = convert_bbox_to_z(bbox)
-        self.time_since_update = 0
-        self.id = KalmanBoxTracker.count
-        KalmanBoxTracker.count += 1
-        self.history = []
-        self.hits = 0
-        self.hit_streak = 0
-        self.age = 0
-
-    def update(self, bbox):
-        """
-        Updates the state vector with observed bbox.
-        """
-        self.time_since_update = 0
-        self.history = []
-        self.hits += 1
-        self.hit_streak += 1
-        self.kf.update(convert_bbox_to_z(bbox))
-
-    def predict(self):
-        """
-        Advances the state vector and returns the predicted bounding box estimate.
-        """
-        if (self.kf.x[6] + self.kf.x[2]) <= 0:
-            self.kf.x[6] *= 0.0
-        self.kf.predict()
-        self.age += 1
-        if self.time_since_update > 0:
-            self.hit_streak = 0
-        self.time_since_update += 1
-        self.history.append(convert_x_to_bbox(self.kf.x))
-        return self.history[-1]
-
-    def get_state(self):
-        """
-        Returns the current bounding box estimate.
-        """
-        return convert_x_to_bbox(self.kf.x)
-
-class Sort(object):
-    def __init__(self, max_age=5, min_hits=2, iou_threshold=0.3):
-        """
-        Sets key parameters for SORT
-        """
-        self.max_age = max_age
-        self.min_hits = min_hits
-        self.iou_threshold = iou_threshold
-        self.trackers = []
-        self.frame_count = 0
-
-    def update(self, dets=np.empty((0, 5))):
-        """
-        Params:
-          dets - a numpy array of detections in the format [[x1,y1,x2,y2,score],...]
-        Requires: this method must be called once for each frame even with empty detections.
-        Returns the a similar array, where the last column is the object ID.
-
-        NOTE: The number of objects returned may differ from the number of detections provided.
-        """
-        self.frame_count += 1
-        trks = np.zeros((len(self.trackers), 5))
-        to_del = []
-        ret = []
-        for t, trk in enumerate(trks):
-            pos = self.trackers[t].predict()[0]
-            trk[:] = [pos[0], pos[1], pos[2], pos[3], 0]
-            if np.any(np.isnan(pos)):
-                to_del.append(t)
-        trks = np.ma.compress_rows(np.ma.masked_invalid(trks))
-        for t in reversed(to_del):
-            self.trackers.pop(t)
-        matched, unmatched_dets, unmatched_trks = associate_detections_to_trackers(dets, trks, self.iou_threshold)
-
-        # update matched trackers with assigned detections
-        for m in matched:
-            self.trackers[m[1]].update(dets[m[0], :])
-
-        # create and initialise new trackers for unmatched detections
-        for i in unmatched_dets:
-            trk = KalmanBoxTracker(dets[i, :])
-            self.trackers.append(trk)
-        i = len(self.trackers)
-        for trk in reversed(self.trackers):
-            d = trk.get_state()[0]
-            if (trk.time_since_update < 1) and (trk.hit_streak >= self.min_hits or self.frame_count <= self.min_hits):
-                ret.append(np.concatenate((d, [trk.id + 1])).reshape(1, -1))  # +1 as MOT benchmark requires positive
-            i -= 1
-            # remove dead tracklet
-            if trk.time_since_update > self.max_age:
-                self.trackers.pop(i)
-        if len(ret) > 0:
-            return np.concatenate(ret)
-        return np.empty((0, 5))
-
-def associate_detections_to_trackers(detections, trackers, iou_threshold=0.3):
-    """
-    Assigns detections to tracked object (both represented as bounding boxes)
-    Returns 3 lists of matches, unmatched_detections, unmatched_trackers
-    """
-    if len(trackers) == 0:
-        return np.empty((0, 2), dtype=int), np.arange(len(detections)), np.empty((0, 1), dtype=int)
-    iou_matrix = iou_batch(detections, trackers)
-
-    if min(iou_matrix.shape) > 0:
-        a = (iou_matrix > iou_threshold).astype(np.int32)
-        if a.sum(1).max() == 1 and a.sum(0).max() == 1:
-            matched_indices = np.stack(np.where(a), axis=1)
-        else:
-            matched_indices = linear_assignment(-iou_matrix)
-    else:
-        matched_indices = np.empty(shape=(0, 2))
-
-    unmatched_detections = []
-    for d, det in enumerate(detections):
-        if d not in matched_indices[:, 0]:
-            unmatched_detections.append(d)
-    unmatched_trackers = []
-    for t, trk in enumerate(trackers):
-        if t not in matched_indices[:, 1]:
-            unmatched_trackers.append(t)
-
-    matches = []
-    for m in matched_indices:
-        if iou_matrix[m[0], m[1]] < iou_threshold:
-            unmatched_detections.append(m[0])
-            unmatched_trackers.append(m[1])
-        else:
-            matches.append(m.reshape(1, 2))
-    if len(matches) == 0:
-        matches = np.empty((0, 2), dtype=int)
-    else:
-        matches = np.concatenate(matches, axis=0)
-
-    return matches, np.array(unmatched_detections), np.array(unmatched_trackers)