CycleGAN

Why we included this project

CycleGAN lets you translate images between two domains without paired examples, so the same approach that turns horses into zebras can also turn sketches into photos. It's a reference implementation that bundles several unpaired translation methods, including pix2pix and BiGAN, along with training utilities in one Torch codebase. For anyone wanting to understand how cycle-consistency loss works or to prototype style transfer and domain adaptation ideas, the clear structure and well-documented training loop make it a good place to start. Just keep in mind the original code targets Torch; if you're building a modern pipeline, the maintained PyTorch port is the more practical starting point.