StudyBuzz is a real-time computer vision tool that monitors eye and mouth movements to detect signs of drowsiness and yawning using your webcam. Designed with students in mind, it provides instant voice alerts to help you stay focused while studying.
- 👁️ Detects eye closure using Eye Aspect Ratio (EAR)
- 😮 Detects yawning using Mouth Aspect Ratio (MAR)
- 🔊 Real-time text-to-speech alerts
- 🧠 Works entirely offline using
pyttsx3 - ⏳ Includes a cooldown timer to avoid repeated alerts
- ⚙️ Built with
MediaPipe,OpenCV, andPython
Webcam Input → MediaPipe FaceMesh → EAR & MAR Calculation → Condition Check → Text-to-Speech Alert
- EAR < 0.25 (for 2 seconds) → "Eyes closed! Wake up!"
- MAR > 0.03 → "You are yawning. Stay awake!"
- Clone the repository
- (Optional) Create a virtual environment python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate
- Install dependencies pip install -r requirements.txt
- Open a terminal in the project directory.
- Run the following command: python StudyBuzz_main.py
- Keep your face visible in the webcam frame.
- Voice alerts will trigger when: "Eyes are closed for more than 2 seconds." "A yawn is detected."
- Press q to exit the application.
opencv-python mediapipe pyttsx3
StudyBuzz/
├── StudyBuzzz_main.py # Main application file
├── README.txt # Instructions and project summary
├── requirements.txt # Dependency list
├── StudyBuzzR_Report.pdf # Summary report
├── StudyBuzzR_Presentation.pptx # Presentation
└── demo_video.mp4 # Demo video (Optional)
"Eyes closed! Wake up!" "You are yawning. Stay awake!"
- Session logging & analytics
- User calibration for EAR/MAR thresholds
- Browser integration (Chrome/Zoom)
- Mobile version with offline speech alerts
Roopakjeet Kaur
Developed as part of the ELC Computer Vision Activity at Thapar Institute of Engineering and Technology (2024–25)
This project is licensed under the MIT License.