Covid-19 Face Mask Detection Using Convolutional Neural Network: Proposed System

Covid-19 Face Mask Detection Using Convolutional Neural Network: Proposed System

Nihal Bagwan¹, Pushkar Joshi², Bhagyesh Sitapati³,Shubham Bade⁴ ,Dr. Sandeep Chaware⁵

^1,2,3,4,5Information Technology, JSPM’s Rajarshi Shahu college of Engineering, Pune, Maharashtra, India

ABSTRACT

Reports from the World Health Organization (WHO) suggest that the two main ways to transmit COVID-19 virus are respiratory and physical contact Wearing a medical mask can help reduce the spread of COVID-19 and other respiratory illnesses. As a result, it is vital to wear a good mark in public locations like supermarkets. In this paper, a system is developed for detecting if a person is wearing a mask properly or not. Only a few experiments have been done on using streaming video to get a face mask. It contains a two-stage facial mask formulation and will use OpenCV, TensorFlow, Harr-Cascaded classifier and MobileNetV2 to achieve maximum accuracy. Coronavirus is the latest pandemic that has forced a global health emergency. It primarily spreads from person to person via airborne transmission and physical touch. Infectious infections have become more common all around the world. As a precaution, many countries have enacted tight restrictions about wearing a mask in public places. In this paper, a MobileNetV2 model which is CNN architecture are used for face mask detection is introduced.

Keywords: OpenCV, MobileNetV2, TensorFlow, Keras, COVID-19, Face Mask.