chuncbs / progressive_growing_of_gans_tensorflow

the Tensorflow code of PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION

PGGAN-tensorflow

the Tensorflow implementation of PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY, STABILITY, AND VARIATION.

The generative process of PG-GAN

Differences with the original paper.

• This implement use CelebA dataset, not CelebA-HQ.

• All tricks have been used, except "Equalized learning rate". You can make a PR if high-qualtiy generated samples with this technique can be achieved. Thanks for your contributions.

• Recently, just generate 64x64 and 128x128 pixels samples.

Setup

Prerequisites

• TensorFlow >= 1.1
• python 2.7

Getting Started

• Clone this repo:

git clone https://github.com/zhangqianhui/progressive_growing_of_gans_tensorflow.git
cd PGGAN-tensorflow

• Download the CelebA dataset

You can download the CelebA dataset and unzip CelebA into a directory. Noted that this directory don't contain the sub-directory.

• Train the model

python main.py --path your data-path

Results

Here is the generated 64x64 results of PGGAN-tensorflow(Left: generated; Right: Real):

Here is the generated 128x128 results of PGGAN-tensorflow(Left: generated; Right: Real):

Issue

If you find some bugs, Thanks for your issue to propose it.

Reference code

PGGAN Theano

PGGAN Pytorch