A simple Drowsiness Detection module for humans. 😴 🚫 🚗

Driver Drowsiness Detector detects if a driver or a person is drowsy or not, using their eye movements.

A real-time drowsiness detection system for drivers, which alerts the driver if they fall asleep due to fatigue while still driving. The computer vision algorithm used for the implementation uses a trifold approach to detect drowsiness, including the measurement of forward head tilt angle, measurement of eye aspect ratio (to detect closure of eyes) and measurement of mouth aspect ratio (to detect yawning).

No description provided.

A computer vision system made with the help of opencv that can automatically detect driver drowsiness in a real-time video stream and then play an alarm if the driver appears to be drowsy.

Intelligent Driver Monitoring system for Autonomous Vehicles

Drowsiness Detector using Python. College Project with all Documents

A Realtime CPU eye detector to detect if the eyes are open or closed

To identify the driver's drowsiness based on real-time camera image and image processing techniques. 졸음운전 감지 시스템. OpenCV

A car safety technology that can auto-detect driver drowsiness in real-time. This system can prevent road accidents that are caused by drivers who fell asleep while driving.

This repo can detect and track user's eyes and mouth and alert when the user is feeling drowsy.

No description provided.

Repository for Classification of Open/Closed eyes for Android devices

Driver drowsiness detection is a car safety Technology which helps prevent accidents caused by the driver getting drowsy. The following code uses computer vision to observe the driver's face, either using a built-in cameraor on mobile devices.

✔👉A Centralized WebApp to Ensure Road Safety by checking on with the activities of the driver and activating label generator using NLP.

A drowsiness monitoring system for drivers.

DNDS is a vehicle safety recommendation system that monitors the driver’s facial behaviour to detect the driver’s drowsiness and yawning. The system also monitors the road in front to detect the road lanes, the lane curvature, the vehicle centre offset, and objects of multiple classes on the road, such as humans, animals, and other vehicles, etc.

A project which helps prevent accidents caused by the driver getting drowsy. The project is built on python using OpenCV library.

This is a project implementing Computer Vision techniques to detect drowsiness of a driver and emit sound and luminous alert.

No description provided.

Aware Driving (AD) is a mobile app that will assist you while you are driving.

This repository uses facial recognition to identify students and save their attendance in a CSV file. Moreover, it also continuously detects for signs of drowsiness in the student and prints a warning if required.

Prototype of an intelligent safety system for detecting driver drowsiness

Driver Drowsiness Detection with YOLOv8 and Facial Features Combat driver fatigue with this deep learning-powered system that utilizes YOLOv8 to detect open and closed eyes, accurately assessing drowsiness levels.

Real-time drowsiness detection on driver's face continuously for signs of fatigue using deep learning methodologies

Apply deeplearning for detecting and warning of driver drowsiness

Pytorch Real-Time Image Classification with CNN

Real-time driver drowsiness detection system using computer vision, OpenCV, and MediaPipe face mesh. Monitors eye movements and calculates Eye Aspect Ratio (EAR) to detect fatigue, providing immediate visual alerts for enhanced driving safety.

Driver Drowsiness Detection

Detect if the driver is feeling drowsy and sound an alarm on doing so to wake him/her up.