SafeSense

Introduction

SafeSense is a Driver Drowsiness Detection System designed to detect and alert drivers when they show signs of drowsiness or fatigue while operating a vehicle. This README file provides an overview of the system, its features, and instructions for installation and usage.

Features

• Real-time Drowsiness Detection: The system uses computer vision techniques and machine learning algorithms to analyze the driver's facial features and detect signs of drowsiness in real-time.
• Eye State Monitoring: The system tracks the driver's eye movements and monitors the eye state to detect if the eyes are closed or if the driver is blinking excessively, indicating potential drowsiness.
• Yawning Detection: The system identifies instances of yawning, which is a common symptom of drowsiness, by analyzing facial landmarks and mouth movements.
• Alarm and Alert System: When drowsiness is detected, the system triggers an alarm to alert the driver. The alert can be in the form of a sound, vibration, or visual notification, depending on the implementation.
• Adjustable Sensitivity: The system allows users to adjust the sensitivity of drowsiness detection based on their preferences or specific requirements.
• Robust Performance: The system is designed to work in various lighting conditions and can handle different driver positions and orientations.

Requirements

• Python (version 3.6 or higher)
• OpenCV (computer vision library)
• dlib (machine learning library)

Installation

1. Clone the repository:

   git clone https://github.com/jahnvisahni31/SafeSense.git
   cd SafeSense

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

Usage

1. Start the application:

   python main.py

2. Adjust the sensitivity (if needed):

   • Open the settings in the application interface and adjust the sensitivity slider to match your preferences.

3. Monitor for drowsiness:

   • The system will continuously monitor your facial features, eye state, and yawning to detect signs of drowsiness.
   • When drowsiness is detected, an alarm will trigger to alert you.

Contributing

Contributions are welcome! If you have any ideas, suggestions, or improvements, feel free to open an issue or submit a pull request.

To contribute:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature-branch

3. Make your changes.
4. Commit your changes:

   git commit -m "Description of changes"

5. Push to the branch:

   git push origin feature-branch

6. Open a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for more details.