Face-mask detection Software

Abstract

The aim or goal of this thesis was to develop a software that can help reduce the spread of Covid-19 by detecting people not wearing face-mask in public areas. The coronavirus epidemic had a very huge impact on the world economy, private businesses, and teaching institutions. This thesis first examines a dataset of people with a mask and people without a mask and use it to train a model for detecting face mask on people’s face using machine learning. In the second stage, the model was tested with a sample of real images and videos, finally, a software with a graphical user interface was developed for use in public places. The thesis is composed of 3 chapters, each explaining different aspects of artificial intelligence algorithms.