Driver drowsiness detection systems help reduce mishaps due to tired or sleepy drivers. Learn to build such a robust system using MediaPipe
Continuous driving can be tedious and exhausting. A motorist may get droopy and perhaps nod off due to inactivity. In this article, we will create a drowsy driver detection system to address such an issue. For this, we will use Mediapipe’s Face Mesh solution in python and the Eye Aspect ratio formula. Our goal is to create a robust and easy-to-use application that detects and alerts users if their eyes are closed for a long time.
In this post, we will:
Learn how to detect eye landmarks using the Mediapipe Face Mesh solution pipeline in python.
Introduce and demonstrate the Eye Aspect Ratio (EAR) technique.
Create a Driver Drowsiness Detection web application using streamlit.
Use streamlit-webrtc to help transmit real-time video/audio streams over the network.
Deploy it on a cloud service.
