tjwei/GANotebooks
tjwei/GANotebooks has 1,486 GitHub stars and 361 forks. GitHot measured 0 stars in 24 hours and 0 in 7 days. Last checked 2026-11-14 00:54 UTC. Last push 2018-02-11.
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Über uns
wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch
Maschinelles LernenREADME.md
OriginalGenerative Adversarial Notebooks
Collection of my Generative Adversarial Network implementations
Most codes are for python3, most notebooks works on
CycleGAN
- CycleGAN-lasagne
- CycleGAN-keras
CycleGAN results
Result after 3 hours and 58 epochs on a GTX 1080. From top to bottom: Input, Fake, Recreate of the input.
Face-off result. From top to bottom: Input, Fake, Recreate of the input.
[youtube video](https://www.youtube.com/watch?v=Fea4kZq0oFQ)pix2pix
- pix2pix-keras: pix2pix GAN Keras implementation
- pix2pix-lasagne: pix2pix GAN Lasagne implementation
- pix2pix-torch: pix2pix GAN pytorch implementation
pix2pix sample results
Validation result of edges-to-shoes after 12 epochs. From top to bottom: Input, Ground truth, the result.
Validation result of facades dataset after 150 epochs using resnet. From top to bottom: Input, Ground truth, the result.WGAN on CIFAR10
- wgan-keras: Wasserstein GAN Keras implementation
- wgan-lasagne: Wasserstein GAN Lasagne implementation
- wgan-torch: Wasserstein GAN pytorch implementation based on https://github.com/martinarjovsky/WassersteinGAN
WGAN2 (improved WGAN/WGAN-gp)
- wgan2-lasagne: improved WGAN Lasagne implementation (on CIFAR10)
- wgan2-keras: improved WGAN Keras implementation (on CIFAR10)
- wgan2-lasagne-anime: WGAN on anime face images, lasagne
- wgan2-AC-lasagne: improved WGAN Lasagne implementation with Auxillary classfier
WGAN2 sample results
- cifar10 dataset

- cifar10 dataset with Auxillary classfier

- anime face dataset

InfoGAN
- mnist-infogan: InfoGAN Lasagne on MNIST dataset
- mnist-infogan-paper-uniform: InfoGAN Lasagne on MNIST dataset (fllowing the paper implementation)
InfoGAN sample results

DCGAN
- dcgan-lasagne: DCGAN in Lasagne
DCGAN sample results
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