How do we actually implement this?

We have now arrived at the core. The previous introduction was necessary because it gives you the background required to build an object detection and recognition system. Now, let's build an object recognizer that can recognize whether the given image contains a dress, a pair of shoes, or a bag. We can easily extend this system to detect any number of items. We are starting with three distinct items so that you can start experimenting with it later.

Before we start, we need to make sure that we have a set of training images. There are many databases available online, where the images are already arranged into groups. Caltech256 is perhaps one of the most popular databases for object recognition. You can download it from http://www.vision.caltech.edu/Image_Datasets/Caltech256. Create a folder called images and create three sub folders inside it—that is, dress, footwear, and bag. Inside each of those sub folders, add 20 images corresponding to that item. You...