MINOR-PROJECT

Accident Detection and Real-Time Driver Drowsiness System

Overview

This project is a collaborative effort aimed at enhancing road safety. We have developed an accident detection model using a video dataset and YOLOv8, and a real-time driver drowsiness detection system in Python.

Features

1. Accident Detection: Utilizes a video dataset and the YOLOv8 model to detect accidents. The model has been trained to recognize various types of accidents.
2. Driver Drowsiness Detection: Monitors the driver in real-time using a webcam. The system can detect signs of drowsiness or inattention, and can alert the driver or stop the vehicle to prevent accidents.

Prerequisites

• Python 3.x
• OpenCV
• Numpy
• Ultralytics YOLOv8
• Pandas
• Opencv
• Imutils
• dlib

Installation

1. Clone the repository: git clone https://github.com/your-repo-link
2. Install the dependencies: pip install -r requirements.txt

Contributors

• Ayush Trivedi
• Sanskar Upadhyay
• Aditya Badgotiya

License

This project is licensed under the GPL 3.0 License. See the LICENSE file for details.

Acknowledgements

We would like to thank our mentors and peers for their guidance and support throughout the development of this project.