Social Distance Analysing - COVID-19 Using Deep Learning and Computer Vision
In the combat in opposition to the coronavirus, social distancing has tested to be an effective degree to bog down the unfold of the disease. The machine provided is for reading social distancing through calculating the space among humans for you to gradual down the unfold of the virus. This machine makes use of enter from video frames to parent out the space among people to relieve the impact of this pandemic. This is performed through comparing a video feed acquired through a surveillance camera. The video is calibrated into bird’s view and fed as an enter to the YOLOv3 version that is an already educated item detection version. The YOLOv3 version is educated using the Common Object in Context (COCO). The proposed machine turned into corroborated on a pre-filmed video. The outcomes and consequences acquired through the machine display that assessment of the space among more than one people and figuring out if policies are violated or not. If the space is less than the minimal threshold value, the people are represented through a purple bounding box, if not then it's far represented through a inexperienced bounding box. This machine may be similarly advanced to detect social distancing in real-time applications.