Real-time computer vision system for monitoring worker safety in industrial environments. Detects improper hand placement and worker distraction, triggering instant alerts with automated incident logging.
- 🚨 Real-time violation detection - 30 FPS continuous monitoring
- 🖐️ Pose & hand landmark detection using MediaPipe AI
- 📝 Automated incident logging to Supabase database
- 📈 Analytics dashboard with Metabase for safety metrics
- ⚡ <100ms alert latency for instant response
- 🔧 Scalable to multiple camera feeds
Factory workers face safety risks from improper hand placement near hazardous zones and distraction. Manual incident reporting is slow, error-prone, and often misses violations. This system automates real-time monitoring with instant alerts.
Camera Feed → OpenCV Capture → MediaPipe Processing → Violation Detection → Alert Trigger → Supabase Logging → Metabase Dashboard
| Category | Technologies |
|---|---|
| Language | Python 3.9+ |
| Computer Vision | OpenCV, MediaPipe |
| Database | Supabase (PostgreSQL) |
| Analytics | Metabase |
| Version Control | Git |
- Python 3.9 or higher
- Webcam (or video file for testing)
- Supabase account (free tier works)
- Metabase instance (local or cloud)
- Python 3.9+ → Download here
- Git → Download here
- Docker Desktop → Download here (only for Metabase dashboard)
- A Webcam → Any standard USB webcam works
Step 1: Clone the repository
1. Clone the Repository
git clone https://github.com/palak172/FSDS-Deep-V2.git
cd FSDS-Deep-V2
2. Create a Virtual Environment (Recommended)
This isolates project dependencies.
Windows:
python -m venv venv
.\venv\Scripts\activate
macOS/Linux:
python3 -m venv venv
source venv/bin/activate
3. Install Dependencies
pip install -r requirements.txt
5. Configure Environment Variables
Copy the example environment file and add your Supabase credentials:
cp .env.example .env
Then open .env and fill in your details:
SUPABASE_URL=https://your-project-ref.supabase.co
SUPABASE_KEY=your_supabase_anon_key
5. Run the Application
Start the main safety monitoring system:
python main.py
6. Start the Metabase Dashboard (Optional)
To view the analytics dashboard, run Metabase in a Docker container:
docker run -d -p 3000:3000 --name metabase metabase/metabase
Then open your browser and go to http://localhost:3000.
Troubleshooting Common Issues
pip install -r requirements.txt fails: Upgrade pip first:
pip install --upgrade pip
Modules not found: Ensure your virtual environment is activated before running python main.py.
Docker command not found: Install and start Docker Desktop.
Camera not detected: Check your webcam connection and try changing CAMERA_INDEX in your .env file (e.g., 0, 1, or 2).
⚙️ Configuration Create a .env file with:
-SUPABASE_URL=your_supabase_project_url
-SUPABASE_KEY=your_supabase_anon_key
-ALERT_THRESHOLD=0.7
-CAMERA_INDEX=0
-FPS_TARGET=30
🤝 Contributing Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit changes (git commit -m 'Add amazing feature')
Push to branch (git push origin feature/amazing-feature)
Open a Pull Request
📝 License Distributed under the MIT License. See LICENSE for more information.
📧 Contact Palak Arora - ar.palak0217@gmail.com - https://www.linkedin.com/in/palak-arora172/
Project Link: https://github.com/palak172/FSDS-Deep-V2
🙏 Acknowledgements MediaPipe for pose estimation
OpenCV community
Supabase for database hosting