The Self-Driving car might still be having difficulties understanding the difference between humans and garbage can, but that does not take anything away from the amazing progress state-of-the-art object detection models have made in the last decade. Combine that with the image processing abilities of libraries like OpenCV, it is much easier today to build a real-time object detection system prototype in hours. In this guide, I will try to show you how to develop sub-systems that go into a simple object detection application and how to put all of that together. I know some of you might be thinking why I am using Python, isn't it too slow for a real-time application, and you are right; to some extent. The most compute-heavy operations, like predictions or image processing, are being performed by PyTorch and OpenCV both of which use c behind the scene to implement these operations, therefore it won't make much difference if we use c or python for our use case here.