Skip to content

A camera-based solution for checking a blind spot programmatically using machine learning.

License

Notifications You must be signed in to change notification settings

AritroSaha10/BlindSpotDetection

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Blind Spot Detection using Machine Learning

A lightweight camera-based solution for checking a blind spot programmatically using TensorFlow and Python on a Raspberry Pi.

Repository Contents

This repository contains multiple elements of the project. These elements include:

  • Jupyter Notebook going into how the model was made
  • The trained model
  • Python program that uses the model on two cameras

Model Info

Using transfer learning on MobileNetV2, an accuracy of ~98% was reached for blind spot detection with an average prediction time of 0.09s on the Raspberry Pi 4 without any machine learning accelerators. Given an ML accelerator such as the Google Coral USB Accelerator, it would likely reach prediction times of 0.0026s (2.6ms, source).

Demo Video

Want to skip straight into the details? Check out this video demoing the machine learning algorithm.

Demo Video

License

This project is under the GNU General Public License, version 3. More info is available in LICENSE

About

A camera-based solution for checking a blind spot programmatically using machine learning.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published