• Vivek Kumar
• Tushant Yadav
• Tarun Sharma
• Bhavnesh Jaint

In this current ongoing situation of a Worldwide Pandemic due to the COVID-19 Virus, Social Distancing and wearing a Face Mask are two of the most important and viable means of the prevention of this Virus. As per the guidelines issued by WHO, Social Distancing should be practiced with a distance of at least 1m between 2 individuals. You Only Look Once (YOLO) is one of the best available CNN Architecture for detecting various Objects. For Object detection, bounding boxes for different objects placed under different classes deem to be the best option. YOLO architecture utilizes the concept of Transfer Learning. Transfer learning is a machine learning method in which a model which has already been developed for a particular task is reused as the base to perform another task. We have implemented YOLO in our project using the Darknet framework. In this paper, we will be using a pre-trained YOLO model and train it for Social Distancing detection and Face Mask detection.

COVID-19, Social Distancing, CNN, You Only Look Once (YOLO), Transfer Learning, Darknet

"Covid-19 Saftey Protocol Violation Detection Using YOLO", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.b8-b15, May-2022, Available :http://www.jetir.org/papers/JETIR2205102.pdf

"Covid-19 Saftey Protocol Violation Detection Using YOLO", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppb8-b15, May-2022, Available at : http://www.jetir.org/papers/JETIR2205102.pdf