The Drowsiness Detection Application is designed to monitor driver behavior and detect signs of drowsiness in real time. By analyzing facial landmarks, eye movements, and head poses using a webcam, the app aims to enhance safety by providing timely alerts and preventing accidents caused by driver fatigue.

• Frontend: HTML, CSS, JavaScript
• Backend: Python (Flask)
• Libraries: TensorFlow, OpenCV

To run this application, ensure you have the following installed:

• Python 3.6 or higher
• pip (Python package manager)
• A webcam for real-time monitoring

git clone git@github.com:Ali-Almadhagi/COSC480-project.git

cd COSC480-project

python3 -m venv venv

• For macOS/Linux:

  source venv/bin/activate

• For Windows:

  venv\Scripts\activate

cd backend

pip install -r requirements.txt

python3 app.py

• Open the URL provided in the terminal (e.g., http://127.0.0.1:5000) in your web browser.
• Ensure proper lighting conditions.
• Position yourself at a distance similar to the gap between a car dashboard and the driver for accurate cropping and detection.

• Ensure that the webcam is functional and accessible by the application.
• The application performs best under good lighting conditions.
• Testing at a realistic distance helps simulate real-world usage effectively.

• If dependencies fail to install, verify your Python version and pip installation.
• Check the terminal output for error messages and debug accordingly.
• Ensure the virtual environment is activated before running any commands.