Opti Tracker is an AI-powered application designed to monitor and analyze user activity in real-time using facial landmark detection and tracking mechanisms. It provides feedback alerts based on user posture, attention level, and fatigue, ensuring better focus and ergonomic posture.
- 🎭 Real-time Facial Landmark Tracking: Uses MediaPipe to detect and analyze face movement.
- 🔊 Audio Feedback Alerts: Notifies users if they are distracted, sleepy, or have poor posture.
- 🖥️ PyQt-based UI: Provides an interactive interface for tracking and feedback visualization.
- 📂 Modular Architecture: Components are structured separately for better code organization.
opti-tracker/
├── README.md # Project documentation
├── face_landmarks.py # Facial landmark detection script
├── icons.py # Handles icon resources
├── main.py # Main entry point for the application
├── requirements.txt # List of dependencies
│
├── Audio/ # Audio feedback alerts
│ ├── Distracted.ogg # Alert for distraction
│ ├── Posture.ogg # Alert for poor posture
│ └── Sleepy.ogg # Alert for drowsiness
│
├── media/ # Folder for media resources
├── mediapipe_experiments/ # Mediapipe experiment scripts
│ ├── face_landmarks.py # Face landmark detection experiments
│ └── face_lm_rec.py # Face recognition test script
│
└── models/ # Pre-trained AI models
└── face_landmarker.task # Model for face landmark detection
git clone https://github.com/yourusername/opti-tracker.git
cd opti-tracker
python3 -m venv venv
source venv/bin/activate # For Linux/macOS
venv\Scripts\activate # For Windows
pip install -r requirements.txt
The project relies on the following key libraries:
- PyQt5 – For GUI development.
- OpenCV - For Video Capture and processing.
- MediaPipe – For real-time facial landmark detection.
- PyDub – For playing audio feedback.
- Additional dependencies listed in
requirements.txt.
To run the Opti Tracker, execute:
python main.py
This will launch the application and start tracking the user's face, detecting distractions, posture issues, or fatigue, and providing real-time feedback.
Uses MediaPipe to analyze 68 facial landmarks in real time. Continuously monitors head position, eye movement, and posture. Triggers audio alerts from the Audio/ folder when:
- User looks away (distracted)
- Slouches (poor posture)
- Shows signs of drowsiness (sleepy)
We welcome contributions! Follow these steps:
https://github.com/SoumyaCO/Opti-Tracker.git
git checkout -b feature-name
git commit -m "Added new feature"
git push origin feature-name