Python Image Processing Cookbook

Image generation with a GAN

A generative adversarial network (GAN) is a generative model that defines an adversarial net framework and is composed of a couple of models (both models are CNNs in general), namely a generator and a discriminator, with the goal of generating new realistic images when given a set of training images. These two models act as adversaries of each other: the generator learns to generate new fake images that look like real images (starting with random noise) whilethe discriminator learns to determine whether a sample image is a real or a fake image.

The generator plays the role of a counterfeiter that is trying to produce a fake image and fool the discriminator, whereas the discriminator plays the role of the police ...