Distracted-Drowsy-Driver-Detection

KO | EN

gitlite — search

#python #java #python3 #arduino #golang #machine-learning #rust #html #flask #javascript #seismology #nodejs

Distracted-Drowsy-Driver-Detection

★ 10 Open GitHub ↗

An application to run on any device can be used as to track driver activity, whether a driver is Distracted or Drowsy and alert the Driver accordingly based on the alert meter. It tracks and detects various Driver activity such as Wearing Seatbelt, Using Phone, Where Driver is looking, eyes opened or closed and others.

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# DRIVER ACTIVITY TRACKER

This project is an application designed to run on any device to track driver activity. It aims to enhance road safety by monitoring whether a driver is distracted or drowsy, and alerting the driver accordingly based on an alert meter. This project is made using the model trained using YoloV8, Dlib, OpenCV's libraries, etc.

## Capabilities
The application is capable of tracking and detecting various driver activities such as:
- Whether the Driver is wearing a Seatbelt
- Whether the Driver is using a Phone
- Whether the Driver is using a Yawing
- Where the Driver is Looking
- Whether the Driver's Eyes are Opened or Closed
- And many more...

## Features

- **Real-time Detection**: Utilizes live video feed to detect drowsiness and distraction behaviors.
- **Multiple Behaviors Recognition**: Capable of recognizing various behaviors indicating drowsiness (e.g., frequent yawning, eye closure) and distraction (e.g., mobile phone usage).
- **Alert System**: Generates audible alerts to wake or alert the driver upon detection of any drowsy or distracted behavior.
- **Extensive Training Data**: Includes trained models and datasets for eyes closed, mobile usage, yawning detection, and seatbelt usage.

## Project Structure

- `Application.py`: The main application script for running the detection system.
- `Project Images/`: Contains various project-related images, including abstracts, infographics, and sample detection images.
- `Train/`: Includes training scripts and results for different behaviors (Eyes Closed, Mobile Usage, Yawning, Seatbelt).
  - `Eyes_Closed_Train/`, `Mobile_Train/`, `Yawn_Train/`, `Seatbelt_Train/`: Each directory contains training results, curves (F1, PR, P, R), confusion matrices, and trained model weights.
- `alert_sound.wav`: The alert sound file played when a drowsy or distracted behavior is detected.
- `best_*.pt`: Pre-trained model weights for different detection modules.
- `shape_predictor_68_face_landmarks.dat`: Facial landmark predictor used for detecting facial features related to drowsiness and distraction.

## Getting Started

To run the Distracted Drowsy Driver Detection system, follow these steps:

1. Clone the repository to your local machine.
2. Ensure you have Python installed along with necessary libraries such as OpenCV, PyTorch, and dlib.
3. Run `Application.py` to start the detection system.
4. Adjust the camera to ensure it captures the driver's face clearly.

## Contributing

Contributions to the Distracted Drowsy Driver Detection project are welcome. Please feel free to fork the repository, make your changes, and submit a pull request.

Distracted-Drowsy-Driver-Detection

Was this content helpful?

Recent Feedback

Download README