Abstract
Abstract: COVID-19 cases have been a big threat to human mankind with different variants found worldwide infecting many people alike. The whole world struggled through different waves of coronavirus and is struggling to reduce the spread effectively. The use of mitigation and suppression was practised throughout and it was concluded use of suppression couldn’t come without economic downfall for long term. With results fromChina and South Korea it was clear that use of masks helped reduce spread within social gatherings ,to ensure everyone wears a mask is one thing and to wear a mask properly covering their nose and mouth fully leaving no part exposed was other problem to tackle. This paper attempts to develop effective yet simple approach to monitor real time data of people wearing masks. The main aim of this project is to help identify and monitor gatheringin public places where wearing mask is essential as it takes a week to show symptoms and anyone can get infected, results show if two individuals are wearing a mask the risk of virus spreading is at its lowest. This model successfully recognizes ifany individual is wearing face mask or not and also determinesif the face mask covers nose and mouth only then it recognizesit as an masked individual.
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