Detection of Face Mask and Social Distance Calculation Using Deep Learning

The COVID 19 epidemic is causing a worldwide health disaster. The epidemic caused governments all over the world to institute lockdowns in order to limit viral spread. According to study data, wearing a face mask and keeping social distance in public places significantly reduces the risk of transmission. The project's ultimate goal is the development of a real-time, very accurate system that can detect any non-masked faces anywhere and compulsively require people to wear masks in the interest of public health. The proposed system combines state-of-the-art deep learning algorithms with geometric methods to provide a reliable modal that is effective at detection, tracking, and validation. Consequently, the proposed method is helpful to society because it reduces the spread of the corona virus while saving time. In light of the current situation, where the lockdown is being removed to permit inspections at public gatherings, retail malls, and other areas, this may prove to be effective. Automated inspection saves resources since it reduces the need for human inspectors. In addition, it is applicable in any circumstance.