junyanz/pytorch-CycleGAN-and-pix2pix

Health v2 · maintenance only

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Adoption not part of the score

25232 stars · 6569 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Official PyTorch implementations of CycleGAN and pix2pix for paired and unpaired image-to-image translation. It includes training and testing scripts, pretrained models, and support for multi-GPU DDP training with PyTorch 2.4+.

Use cases

• translate photos between styles without paired training data
• convert sketches or edges to realistic images
• train a pix2pix model on my own paired dataset
• turn horses into zebras with cyclegan
• reproduce GAN image-to-image translation paper results
• learn how GANs are implemented in PyTorch

When to choose

• you need well-tested reference implementations of CycleGAN or pix2pix
• you want pretrained models for common translation tasks
• you need a codebase to adapt for custom image translation research

When to avoid

• you need fast one-step translation - the authors recommend img2img-turbo instead
• you want diffusion-based image editing rather than GANs
• you need a production inference service rather than research code

Facets

library · maturity stable

machine-learning deep-learning image-processing computer-vision graphics deep-learning computer-vision image-processing machine-learning graphics python windows cross-platform gan cyclegan pix2pix image-to-image-translation pytorch generative-models research-code unpaired-translation gpu linux macos

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