Introducing YOLO v2 

YOLO, is a very popular and fully conventional algorithm that is used for detecting images. It gives a very high accuracy rate compared to other algorithms, and also runs in real time. As the name suggests, this algorithm looks only once at an image. This means that this algorithm requires only one forward propagation pass to make accurate predictions. 

In this section, we will detect objects in images with a fully convolutional network (FCN) deep learning model. Given an image with some objects (for example, animals, cars, and so on), the goal is to detect objects in those images using a pre-trained YOLO model, with bounding boxes.

Many of the ideas are from the two original YOLO papers, available at https://arxiv.org/abs/1506.02640 and https://arxiv.org/abs/1612.08242. But before diving into the YOLO model, let's first understand some prerequisite fundamental concepts.

Classifying and localizing images and detecting objects

Let's first understand the concepts regarding...