Pix2pix is a type of Generative Adversarial Network (GAN) that is used for image-to-image translation. Image-to-image translation is a method for translating one representation of an image into another representation. Pix2pix learns a mapping from input images into output images. It can be used to convert black and white images to color images, sketches to photographs, day images to night images, and satellite images to map images. The pix2pix network was first introduced in the paper titled Image-to-Image Translation with Conditional Adversarial Networks, by Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, Alexei A. Efros; which can be found at the following link: https://arxiv.org/pdf/1611.07004.pdf.
In this chapter, we will cover the following topics:
- Introducing the Pix2pix network
- The architecture of the Pix2pix network
- Data gathering and preparation
- The Keras implementation of Pix2pix
- Objective functions
- Training Pix2pix
- Evaluating the trained model
- Practical applications of the Pix2pix network