Inferring with YOLO

Because the architecture of the model can be quite hard to understand in one go, we will split the model into two parts—inference and training. Inference is the process of taking an image input and computing results. Training is the process of learning the weights of the model. When implementing a model from scratch, inference cannot be used before the model is trained. But, for the sake of simplicity, we are going to start with inference.