  Real-time object detection is a crucial problem to solve when in comes to
computer vision systems that needs to make appropriate decision based on
detection in a timely manner. I have chosen the YOLO v1 architecture to
implement it using PyTorch framework, with goal to familiarize with entire
object detection pipeline I attempted different techniques to modify the
original architecture to improve the results. Finally, I compare the metrics of
my implementation to the original.
