REPOSITORY OVERVIEWLive repository statistics
★ 0Stars
⑂ 0Forks
◯ 0Open issues
◉ 0Watchers
63/100
OPENREPOHUB HEALTH SIGNALMixed signals
A transparent discovery signal based on current public GitHub metadata.
Recent activity35% weight
100 Community adoption25% weight
0 Maintenance state20% weight
100 License clarity10% weight
0 Project information10% weight
75 This score does not audit code, security, maintainers, documentation quality, or suitability. Verify the repository and its current documentation before adoption.
README preview
🚗 Drowsy Driver Alert System
A real-time driver drowsiness detection system developed using Python, OpenCV, MediaPipe Face Mesh, and Pygame. The system continuously monitors the driver's eye movements using a webcam and detects drowsiness by calculating the Eye Aspect Ratio (EAR). When the driver's eyes remain closed for a predefined number of consecutive frames, an alarm is triggered to alert the driver.
Features
- Real-time webcam monitoring
- Face detection using MediaPipe Face Mesh
- Eye landmark detection
- Eye Aspect Ratio (EAR) calculation
- Drowsiness detection using EAR threshold
- Continuous alarm sound when drowsiness is detected
- Automatic alarm stop when eyes reopen
- User-friendly interface displaying:
- EAR value
- Counter
- Driver status
- Alarm status
Technologies Used
- Python
- OpenCV
- MediaPipe
- Pygame
- Math Library
Project Structure
Drowsy-Driver-Alert-System
│
├── drowsy_driver_alert.py
├── alarm.wav
├── requirements.txt
└── README.md
Installation
Clone the repository:
git clone https://github.com/Yashjal11/Drowsy-Driver-Alert-System.git
Install the required libraries:
pip install -r requirements.txt
Run the project:
python drowsy_driver_alert.py
Working
- Capture live video using the webcam.
- Detect the driver's face using MediaPipe Face Mesh.
- Extract eye landmarks.
- Calculate the Eye Aspect Ratio (EAR).
- Compare the EAR with the threshold value.
- Increase the frame counter when the eyes remain closed.
- Trigger the alarm when the counter reaches the predefined limit.
- Stop the alarm when the driver's eyes reopen.
Future Improvements
- Yawning detection
- Head pose estimation
- Mobile notifications
- Driver distraction detection
- Cloud monitoring
- Night vision support
Screenshots
ALGORITHMICALLY RELATEDSimilar Open-Source Projects
Selected from shared topics, language and repository description—not editorial ratings.
A real-time drowsiness detection system for drivers, which alerts the driver if they fall asleep due to fatigue while still driving. The computer vision algorithm used for the implementation uses a trifold approach to detect drowsiness, including the measurement of forward head tilt angle, measurement of eye aspect ratio (to detect closure of eyes) and measurement of mouth aspect ratio (to detect yawning).
60/100 healthActive repository
PythonNo license#dlib#drowsiness-detection#eye-status#opencv
⑂ 23 forks◯ 4 issuesUpdated Jun 18, 2026
A deep learning project to detect driver drowsiness using computer vision. Features real-time monitoring and alert system. Built with Python, OpenCV, and yolov8.
56/100 healthActive repository
PythonMIT
⑂ 1 forks◯ 0 issuesUpdated Mar 26, 2026