A PyTorch Implementation of StyleGAN2 (Unofficial)

This repository contains a PyTorch implementation of the following paper:

Analyzing and Improving the Image Quality of StyleGAN (StyleGAN2) Authors: Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, Timo Aila

Paper: http://arxiv.org/abs/1912.04958 Video: https://youtu.be/c-NJtV9Jvp0

Picture: These people are not real – they were produced by our generator that allows control over different aspects of the image.

Motivation

To the best of my knowledge, there is still not a similar pytorch 1.0 implementation of styleGAN2 as NvLabs released(Tensorflow), therefore, i wanna implement it on pytorch1.0.1 to extend its usage in pytorch community.

Notice

@date: 2019.12.16

@info: settings are in opts/opts.py. you can change to your own dataset and choose resolution at 64, 128, 256 and so on.

Author

• Samuel Ko

Training

# ① pass your own dataset of training, batchsize and common settings in TrainOpts of `opts.py`.

# ② run train_stylegan.py
python3 train.py

# ③ you can get intermediate pics generated by stylegenerator in `opts.det/images/`

Project

we follow the release code of styleGAN2 carefully and if you found any bug or mistake in implementation, please tell us and improve it, thank u very much! .

Unfinished

• Inference code.

Related

1. StyleGAN - Official TensorFlow Implementation

2. The re-implementation of style-based generator idea

3. ptrblck_styleGAN

System Requirements

• Ubuntu18.04
• PyTorch 1.0.1
• Numpy 1.13.3
• torchvision 0.2.2
• scikit-image 0.15.0
• tqdm
• GTX 1080Ti or above

Q&A

Acknowledgements

My Email is [email protected], if you have any question and wanna to PR, please let me know, thank you.