Drowsiness Detection System

Overview

This project implements a drowsiness detection system using OpenCV, dlib, and playsound. The system detects a user's face and monitors their eye aspect ratio (EAR) to determine if they are drowsy. If the EAR falls below a predefined threshold for a certain number of frames, an alert message is displayed, and an alarm sound is played to wake up the user.

Features

• Real-time face and eye detection
• Eye Aspect Ratio (EAR) calculation to detect drowsiness
• Visual alert message displayed on the screen
• Audio alarm when drowsiness is detected

Dependencies

Ensure you have the following dependencies installed before running the script:

pip install opencv-python imutils dlib playsound

Additionally, you need to download the pre-trained dlib facial landmark model:

• shape_predictor_68_face_landmarks.dat

Extract and place the file in the models/ directory of your project.

Installation

1. Clone the repository:

git clone https://github.com/yourusername/drowsiness-detection.git

2. Navigate to the project directory:

cd drowsiness-detection

3. Install required dependencies:

pip install -r requirements.txt

Usage

Run the script to start the drowsiness detection system:

python drowsiness_detection.py

Key Components:

• eye_aspect_ratio(eye): Computes the EAR to determine if eyes are closed.
• detect: Uses dlib's frontal face detector.
• predict: Uses dlib's landmark predictor to identify facial landmarks.
• playsound(): Triggers an alarm sound if drowsiness is detected.

Controls:

• Press q to exit the program.

Configuration

You can modify the following parameters to fine-tune detection:

• thresh = 0.25 (Eye Aspect Ratio threshold for drowsiness detection)
• frame_check = 20 (Number of consecutive frames required to trigger an alert)

Troubleshooting

• Ensure your webcam is properly connected.
• If the alarm sound does not play, check the path to the .mp3 file and verify that playsound is installed.
• If dlib installation fails, ensure you have CMake installed and use:

  pip install dlib --verbose

License

This project is open-source and available under the MIT License.

Acknowledgments

• OpenCV and dlib for facial landmark detection
• Imutils for image processing helpers