Face masks have become a necessity in the current world due to the ongoing COVID-19 pandemic. Many countries and health organizations have advised people to wear masks in public to contain the spread of the virus. Many shops, pubs, mega-stores, and more businesses have strict mask-wearing rules to for customers and employees upon entrance entering.

Businesses and local governments enforcing these strict rules need some kind of mechanism to track people who are not wearing masks. Tracking every single person just with the human eye is more or less impossible.

Hence, we can start considering solutions that help us use computer vision systems to detect the presence of masks. We’ll implement a demo version of such a solution in this article, using image classification with TensorFlow.js.

Editor’s Note: This tutorial is for demonstration purposes only. All computer vision-based surveillance systems need to be designed and implemented with robust ethical standards, and models must be built in ways that minimize bias

In this tutorial, we’re going to implement a program that detects face mask from an image or video feed using the TensorFlow.js library. The idea behind it is pretty simple. We fetch the image from the camera fee and add the KNN classifier, along with a MobileNet model to determine whether or not a face mask is present in a given image.

Now, let’s get started!

#image-classification #javascript #tensorflow #machine-learning