https://github.com/habout632/gan.pth

gan framework
https://github.com/habout632/gan.pth

generative-adversarial-network generative-model

Last synced: 13 days ago
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gan framework

• Host: GitHub
• URL: https://github.com/habout632/gan.pth
• Owner: habout632
• License: other
• Created: 2020-03-27T04:04:29.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2022-12-08T07:29:41.000Z (about 2 years ago)
• Last Synced: 2024-11-30T10:32:06.006Z (2 months ago)
• Topics: generative-adversarial-network, generative-model
• Language: Python
• Size: 130 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 22
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

        
# GAN.pth

a pytorch gan framework

# Features

* As GAN develop so quickly, keeping up to date matters

* Providing GAN specific features as possible i.e modular,but keep Flexible as possible

  - AdaIn, Spectral normalization, skip connections, resnets

  - Out-of-box Models

  - Trainer:train_generator, train_discriminator

  - GAN Loss

  - Metrics

  - Demo

  

* Documentation

* Production oriented, Research Friendly

  - distributed training(multiple gpus and multiple machines)

  - easy to deploy on production(performance optimized for mobile platform and server side)

* Custom Datasets & Pretrained Models provided in GANHub

* Easy to extension For Example 

  - do config through args file for each model

  - train_gene

  - well structured code(object oriented programming)

* well tested, as close as possible to official sota effect

Inspired by following frameworks

[torchgan](https://torchgan.readthedocs.io/en/latest/)

[PytorchGANZoo](https://github.com/facebookresearch/pytorch_GAN_zoo)

[PyTorch-GAN](https://github.com/eriklindernoren/PyTorch-GAN)

StarGAN_v2-Tensorflow

# Classical Models

StyleGAN/StyleGAN2

StarGAN/StarGAN2

FUNIT

# Components

## Discriminator

progressive growing (pggan)

self-attention

## Generator

style-based generator(stylegan)

# GAN Loss

Non-Saturating Loss + R1/R2

WGAN+GP

# Metrics 

IS(Inception Score)

FID(Inception Distance)

LPIPS

PPL

# Datasets

face aligner

# Utils

video interpolation

reporter: tensorboard reporter

# Demos

use GAN.pth framework to develop following apps as demos

## Demo GANS

* Vanilla GAN

* DCGAN

## Faceswap

## AI Stylist

## AI Portraits

Please access [GANHub]https://github.com/habout632/GANHub) for more demos, datasets, pretrained networks.

[Documentation](https://ganpth.readthedocs.io/en/latest/)

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