Providing user guidance to use and train a generative adversarial network

Abstract

Provided are a computer program product, system, and method for providing user guidance to use and train a generative adversarial network. A discriminator, implementing machine learning, is trained to output a high probability from input comprising an input image comprising a real image representing a desirable design item superimposed on a body in a pose represented in the input image, a context of the input image and a pose of the body represented in the input image. A generator, implementing machine learning, generates an output image based on an input context, an input pose, and random noise. The discriminator outputs a probability the output image, from the generator, represents a real image having a desirable design item from input comprising the output image, the input context, and the input pose. The generator is trained to output the output image for the input pose and the input context with the probability.