Basics of Object Detection

In the previous chapters, we learned about performing image classification. Imagine a scenario where we leverage computer vision for a self-driving car. It is not only necessary to detect whether the image of a road contains images of vehicles, a sidewalk, and pedestrians, but it is also important to identify where those objects are located. The various techniques of object detection that we will study in this chapter and the next will come in handy in such a scenario.

In this chapter and the next, we will learn about some of the techniques for performing object detection. We will start by learning the fundamentals – labeling the ground truth bounding-box of objects within an image using a tool named ybat, extracting region proposals using the selectivesearch method, and defining the accuracy of bounding-box predictions by using the intersection over union (IoU) and mean average precision metrics. After this, we will learn about two region proposal...