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tjwei

GANotebooks

wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch

TutorialsML/AI fundamentalsJupyter Notebook
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创建于 2016-12-09 · 更新于 2026-10-06 · 今日第 10183 名
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tjwei

tjwei/GANotebooks 排名第 10,183，有 1,487 个星标。

同类别比较

tjwei/GANotebooks 排名第 10,183，此处有 8 个同类条目；ahangchen/GDLnotes 排名第 10,176。

同类别比较
名称排名指标
dvgodoy/PyTorchStepByStep10,152
语言:
Jupyter Notebook
星标数:
1,502
分叉数:
513
简介:
Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"
alicezheng/feature-engineering-book10,161
语言:
Jupyter Notebook
星标数:
1,499
分叉数:
671
简介:
Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018
google-deepmind/educational10,168
语言:
Jupyter Notebook
星标数:
1,495
分叉数:
204
ahangchen/GDLnotes10,176
语言:
Python
星标数:
1,488
分叉数:
465
简介:
Google Deep Learning Notes（TensorFlow教程）
pkmital/CADL10,192
语言:
Jupyter Notebook
星标数:
1,484
分叉数:
714
简介:
ARCHIVED: Contains historical course materials/Homework materials for the FREE MOOC course on "Creative Applications of Deep Learning w/ Tensorflow" #CADL
bat67/pytorch-tutorials-examples-and-books10,210
语言:
Jupyter Notebook
星标数:
1,478
分叉数:
310
简介:
PyTorch tutorials, examples and some books I found 【不定期更新】整理的PyTorch 最新版教程、例子和书籍
ericdouglas/traduz-ai10,215
星标数:
1,477
分叉数:
292
简介:
:pencil: Coleção de artigos de desenvolvimento de software traduzidos para pt-br
GeostatsGuy/PythonNumericalDemos10,223
语言:
Jupyter Notebook
星标数:
1,474
分叉数:
498
简介:
Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.
关键参数与规格
关键参数与规格
参数值
语言Jupyter Notebook
类别Tutorials
子类别ML/AI fundamentals
关键词Image production
星标数1,487
分叉数362
贡献者1
创建日期2016-12-09
更新日期2026-10-06
1 天星标数0
7 天星标数0
排名10,183
上次排名10,202
排名变化19
7 天星标排名12,538
上次 7 天星标排名12,577
7 天星标排名变化39
总星标排名8,145
上次总星标排名8,134
总星标排名变化-11
国家Taiwan
README 摘录

Generative 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. From top to bottom: Input, Fake, Recreate of the input. youtube video 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 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

常见问题

记录了多少星标和分叉？

tjwei/GANotebooks 有 1,487 个星标和 362 个分叉。

仓库排名是多少？

tjwei/GANotebooks 排名第 10,183。

记录的语言和类别是什么？

tjwei/GANotebooks 有 1,487 个星标，语言为 Jupyter Notebook，类别为 Tutorials。

哪个仓库排名最接近？

tjwei/GANotebooks 与 ahangchen/GDLnotes 比较，后者排名第 10,176，有 1,488 个星标。

README

Generative 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

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

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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