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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Image-to-Image Translation in PyTorch
| Date | Stars |
|---|---|
| 2026-07-24 | 25206 |
| 2026-07-25 | 25207 |
| 2026-07-28 | 25207 |
| 2026-07-30 | 25212 |
| 2026-08-06 | 25212 |
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<img src='imgs/horse2zebra.gif' align="right" width=384> <br><br><br> # CycleGAN and pix2pix in PyTorch **Udpate in 2025**: we recently updated the code to support Python 3.11 and PyTorch 2.4. It also supports DDP for single-machine multiple-GPU training. (Please use `torchrun --nproc_per_node=4 train.py ...`) **New**: Please check out [img2img-turbo](https://github.com/GaParmar/img2img-turbo) repo that includes both pix2pix-turbo and CycleGAN-Turbo. Our new one-step image-to-image translation methods can support both paired and unpaired training and produce better results by leveraging the pre-trained StableDiffusion-Turbo model. The inference time for 512x512 image is 0.29 sec on A6000 and 0.11 sec on A100. Please check out [contrastive-unpaired-translation](https://github.com/taesungp/contrastive-unpaired-translation) (CUT), our new unpaired image-to-image translation model that enables fast and memory-efficient training. We provide PyTorch implementations for both unpaired and paired image-to-image translation. The code was written by [Jun-Yan Zhu](https://github.com/junyanz) and [Taesung Park](https://github.com/taesungp), and supported by [Tongzhou Wang](https://github.com/SsnL). This PyTorch implementation produces results comparable to or better than our original Torch software. If you would like to reproduce the same results as in the papers, check out the original [CycleGAN Torch](https://github.com/junyanz/CycleGAN) and [pix2pix Torch](https://github.com/phillipi/pix2pix) code in Lua/Torch. **Note**: The current software works well with PyTorch 2.4+. Check out the older [branch](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/tree/pytorch0.3.1) that supports PyTorch 0.1-0.3. You may find useful information in [training/test tips](docs/tips.md) and [frequently asked questions](docs/qa.md). To implement custom models and datasets, check out our [templates](#custom-model-and-dataset). To help users better understand and adapt our codebase, we provide an [overview](docs/overview.md) of the code structure of this repository. **CycleGAN: [Project](https://junyanz.github.io/CycleGAN/) | [Paper](https://arxiv.org/pdf/1703.10593.pdf) | [Torch](https://github.com/junyanz/CycleGAN) | [Tensorflow Core Tutorial](https://www.tensorflow.org/tutorials/generative/cyclegan) | [PyTorch Colab](https://colab.research.google.com/github/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/CycleGAN.ipynb)** <img src="https://junyanz.github.io/CycleGAN/images/teaser_high_res.jpg" width="800"/> **Pix2pix: [Project](https://phillipi.github.io/pix2pix/) | [Paper](https://arxiv.org/pdf/1611.07004.pdf) | [Torch](https://github.com/phillipi/pix2pix) | [Tensorflow Core Tutorial](https://www.tensorflow.org/tutorials/generative/pix2pix) | [PyTorch Colab](https://colab.research.google.com/github/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/pix2pix.ipynb)** <img src="https://phillipi.github.io/pix2pix/images/teaser_v3.png" width="800px"/> **[EdgesCats Demo](https://affinelayer.com/pixsrv/) | [pix2pix-tensorflow](https://github.com/affinelayer/pix2pix-tensorflow) | by [Christopher Hesse](https://twitter.com/christophrhesse)** <img src='imgs/edges2cats.jpg' width="400px"/> If you use this code for your research, please cite: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks.<br> [Jun-Yan Zhu](https://www.cs.cmu.edu/~junyanz/)\*, [Taesung Park](https://taesung.me/)\*, [Phillip Isola](https://people.eecs.berkeley.edu/~isola/), [Alexei A. Efros](https://people.eecs.berkeley.edu/~efros). In ICCV 2017. (\* equal contributions) [[Bibtex]](https://junyanz.github.io/CycleGAN/CycleGAN.txt) Image-to-Image Translation with Conditional Adversarial Networks.<br> [Phillip Isola](https://people.eecs.berkeley.edu/~isola), [Jun-Yan Zhu](https://www.cs.cmu.edu/~junyanz/), [Tinghui Zhou](https://people.eecs.berkeley.edu/~tinghuiz), [Alexei A. Efros](https://people.eecs.berkeley.edu/~efros). In CVPR 2017. [[Bibtex]](
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Jun-Yan Zhu · Carnegie Mellon University: · United States
252
Taesung Park
45
Tongzhou Wang · MIT
16
Hungryof
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Ayush Chaurasia · India
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Srinath Mannam
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Charles Dove
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Bilal Khan
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Iver Jordal · ElevenLabs · Norway
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Shreyas Bhat Kera · SiMa.ai · United States
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Alex Kassil · United States
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Alan Yee · United States
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Andy Li · United Kingdom
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Jean-Philippe Mercier · Cofounder @ NQB.AI · Canada
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Salas · Taiwan
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Zirveda Aytimur
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Zhedong Zheng · University of Macau · China
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Yuanchun Shen · @aws @opensearch-project · China
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:bdead5cf18ee216b, topic:deep-learning, topic:pytorch
matched fp:bdead5cf18ee216b, topic:computer-vision
matched fp:bdead5cf18ee216b, topic:image-generation, topic:gan