Face Mask Detection and Classification System Using Deep Learning
M. Dinesh Kumar, J. Sreerambabu, S. Kalidasan · International Journal for Research in Applied Science and Engineering Technology · 2022
Abstract: COVID-19 pandemic caused by novel corona virus is unendingly spreading up to now everywhere the planet. The impact of COVID-19 has been fallen on the majority sectors of development. The health care system goes through a crisis. several preventative measures are taken to cut back the unfold of this sickness wherever carrying a mask is most significant one in all them. In this paper, we have a tendency to propose a system that restricts the expansion of COVID-19 by looking for people that aren't carrying any facial mask in a very good town network wherever all the general public places area unit monitored with television system (CCTV) cameras. While someone while not a mask is detected, the corresponding authority is educated through the town network. A deep learning design is trained on a dataset that consists of pictures of individuals with and while not masks collected from numerous sources. The trained design achieved ninety-eight accuracies on characteristic folks with and while not a facial mask for antecedently unseen check knowledge. It's hoped that our study would be a useful gizmo to cut back the unfold of this disease for several countries within the world. A mask detection dataset consists of with mask and while not mask pictures, we have a tendency to area unit planning to use OpenCV to try to period of time face detection from a live stream via our digital camera We will use the dataset to create a COVID-19 mask detector with pc vision exploitation Python, OpenCV, and Tensor Flow and Kera’s. Our goal is to spot whether or not the person on image/video stream carrying a mask or not with the assistance of pc vision and deep learning