With the rise in the number of Covid-19 cases over the world, social distancing has become an important safety measure. It is advised to stay at a distance of at least 6 feet from other people to reduce the spread of the virus. However, it is very difficult to maintain social distancing in public places like malls and stores due to the large crowd present in an enclosed area. Manually separating people or counting the number of visitors is tedious and very inefficient. Hence, there is a need to fulfill the above role without engaging manpower in it. The primary aim of our project is to solve the above problem by counting people in a store or mall in real-time and alerting the authorities if the maximum limit is reached. We plan to tackle the above-mentioned problem using Computer Vision. The CCTV Camera feed will be retrieved in real-time and will be passed through our model. It will detect the number of people entering and leaving an area and the data will be stored.. The camera feed can be directly retrieved from the CCTV cameras already installed in the stores. Hence, this solution has a negligible hardware cost.This project can be scaled for larger regions and areas too. The real-time stream can also be optimized for better performance using threading. Schedulers and timers also make the work of shopkeepers easy. This acts as a measure towards footfall analysis and in a way to tackle COVID-19..