# Surveillance Dashboard

Real-time multi-camera surveillance app with:

- Person detection using Ultralytics YOLO
- Group gathering detection (2+ people together)
- Alert when group duration is over 20 seconds
- Web dashboard with live feed, camera selector, and alert history
- GPU-only inference (CUDA required)

## Features

- Switch between multiple cameras from UI
- Draw person boxes and group timer overlays
- Save alert snapshots to `alerts/`
- Read camera credentials from `.env`

## Project Structure

- `camera_stream.py` - backend stream processing, detection, and API
- `templates/dashboard.html` - dashboard UI
- `requirements.txt` - minimal Python dependencies
- `.env` - credentials and camera IPs
- `alerts/` - captured alert images

## Requirements

- Python 3.11+ (3.14 can work but ecosystem support may vary)
- NVIDIA GPU + CUDA drivers
- RTSP cameras reachable from this machine
- Utopia VPN access to reach the camera network

## Setup

Create and activate virtual environment:

```powershell
python -m venv .venv
.\.venv\Scripts\Activate.ps1
```

Install PyTorch with CUDA (recommended command from PyTorch site):

```powershell
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu124
```

Install project dependencies:

```powershell
pip install -r requirements.txt
```

## Environment Variables

Create `.env` in project root:

```env
username=YOUR_CAMERA_USERNAME
password=YOUR_CAMERA_PASSWORD
camera_ip_1=192.168.x.x
camera_ip_2=192.168.x.x
```

To add more cameras, add more `camera_ip_*` keys and update code list size if needed.

## Run

```powershell
.\.venv\Scripts\python camera_stream.py
```

Open:

- http://localhost:5000

## Notes

- App is configured to require CUDA GPU; it will exit if CUDA is not available.
- Alert condition: at least 2 people in a group for 20+ seconds.
- Alert snapshots are stored in `alerts/`.
- Utopia VPN is required to access camera streams from outside the office network.
- For VPN or camera network access, contact Samad (IT Department, Head Office).