Abstract
AbstractThe Covid outbreak has caused a worldwide calamity with its poisonous spreading. It has become very important to protect ourselves and the people around us from this infection. The dangers of contagiousness can be limited only by following Covid rules such as wearing facemask and keeping up social distance. This paper proposes a system to distinguish whether the person is wearing a facemask or not and also if the people are maintaining a social distance. The framework used is MobileNetV2 for object recognition. The model is prepared on an image dataset and tested with live real time video with a decent precision. The precision is represented by red and green bounding boxes which indicates facemask accuracy as well as the depth for social distance. Red bounding box appears when the particular object is not wearing a mask or not following social distance and green bounding box displays if the object is following the criteria.KeywordsCOVID-19Social distanceFace mask detectionDeep learningMobile NetV2Bounding box
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