MohamedSelimMaazouz993 / Deep-Learning-Project

dowsiness detection system

Drowsiness Detection System

Introduction

Our Project employs facial landmarks and the eye aspect ratio to detect drowsiness in real-time using a webcam feed. It utilizes the dlib library for face detection and shape prediction, along with essential libraries such as OpenCV, imutils, and pygame for audio alerts.

Libraries Used

• scipy.spatial.distance: Computes the Euclidean distance.
• imutils.face_utils: Provides facial landmark indices.
• imutils: Offers convenience functions for OpenCV.
• dlib: A toolkit for machine learning and computer vision.
• pygame: Used for playing an audio alert when drowsiness is detected.
• cv2: OpenCV library for computer vision.

Requirement

• Python : 3.11
• Pycharm 2023.2.23
• Download Cmake for Dlib Library make sure to tick "add to env path" Cmake 3.28.1

Features

• Real-time drowsiness detection using facial landmarks.
• Audio alert using pygame when drowsiness is detected.
• Saves a screenshot with a timestamp to a specified folder during an alert.

How to Run

If You are Using Pycharm

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

python -m venv venv

2. Install dependencies:

pip install -r requirements.txt

Start the development server:

python Drowsiness_Detection.py

If You Want to Run It Throw CMD

Run The "run_project.bat" it Will Install The Dependencies & Creates The "env"

Stay alert and drive safely!