A simple Drowsiness Detection module for humans. 😴 🚫 🚗
drowsiness detection
This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.
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.
To identify the driver's drowsiness based on real-time camera image and image processing techniques. 졸음운전 감지 시스템. OpenCV
Am I drowsy enough to not drive? Take some glasses of water!
Android Based Drowsy Driver Detection Application
Repository for Classification of Open/Closed eyes for Android devices
This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.
This is a project implementing Computer Vision techniques to detect drowsiness of a driver and emit sound and luminous alert.
This webapp detects if a person is feeling drowsy and plays a sound to alert them. This is most useful for drivers.
Aware Driving (AD) is a mobile app that will assist you while you are driving.
The application analyses an image or a frame in which the the detected face must have Eye Aspect Ratio (EAR) must be greater that the selected threshold value.
Apply deeplearning for detecting and warning of driver drowsiness
An Integration of Amazon Rekognition and Flutter for Tracking Drivers’ Eyes to Prevent them from Sleeping.
Python application to assist drivers to alert when they feel drowsy and thus reduce the number of accidents.
In this project we will train our model on open and close eyes dataset then use that with face recognition library to check if the driver is sleeping or not.
Prevents Sleep deprivation road accidents by alerting drowsy drivers
Welcome to our drowsiness detection project using Python and the powerful dlib library! 😴 This repository hosts a user-friendly implementation to detect drowsiness in real-time using your computer's webcam. Our easy-to-understand Python code utilizes the dlib library's advanced facial landmark detection to monitor facial cues and alert users when
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