WGAN-GP-tensorflow

Tensorflow implementation of paper "Improved Training of Wasserstein GANs".

• 0 epoch

• 25 epoch

• 50 epoch

• 100 epoch

• 150 epoch

Prerequisites

• Python 2.7 or 3.5
• Tensorflow 1.3+
• SciPy
• Aligned&Cropped celebA dataset(download)
• (Optional) moviepy (for visualization)

Usage

• Download aligned&cropped celebA dataset(link) and unzip at ./data/img_align_celeba

• Train:

  $ python main.py --train
  

  Or you can set some arguments like:

  $ python main.py --dataset=celebA --max_epoch=50 --learning_rate=1e-4 --train
  

• Test:

  $ python main.py
  

Acknowledge

Based on the implementation carpedm20/DCGAN-tensorflow, LynnHo/DCGAN-LSGAN-WGAN-WGAN-GP-Tensorflow, shekkizh/WassersteinGAN.tensorflow and igul222/improved_wgan_training.