Hello trend,
This is Satya Mallick from LearnOpenCV.com.
According to CDC, an estimated 1 in 25 adult drivers (18 years or older) report falling asleep while driving and drowsy driving was responsible for 91,000 crashes!
To help address such issues, in this post, we will create a Driver Drowsiness Detection and Alerting System using Mediapipe's Face Mesh solution API in Python. These systems assess the driver's alertness and warn the driver if needed.
While building the application you will learn the following:
- 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 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.
Without further ado, let's jump to the post!
Driver Drowsiness Detection using MediaPipe |
You can check out the code by clicking on the button below, and star us on GitHub to say thanks!
Download Code (GitHub) |
🎥 Highlights from the post
Check out the 3-minute video covering the highlights of the blog post:
📣 Winner of NVIDIA RTX 3080 Ti
We partnered with NVIDIA to giveaway a FREE RTX 3080 Ti to one of our subscribers. All the subscribers who had registered for GTC 2022 using a special link we had set up entered a lucky draw to win the NVIDIA RTX 3080 Ti.
🥁 Drumroll, we have a winner!
Rajathitan ( r...n..@gmail.com )
We also have additional 5 winners who will get credit for one paid course at Deep Learning Institute.
- Enrico (r....o@gmail.com)
- Belayneh (k....7@gmail.com)
- Malaya (m.....3@gmail.com)
- Tim (f....x@gmail.com)
- Harsh (h...h@gmail.com)
We will be reaching out to winners shortly.
In case you missed, we have curated and summarized some of the GTC sessions we found interesting:
The event has now concluded but you can still get exclusive access to view all the amazing sessions on-demand until October 10, 2022.
Cheers!
Satya
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