# WGAN-GP

Pure tensorflow implementation of WGAN-GP

**Sources:**

- [Improved Training of Wasserstein GANs](https://arxiv.org/abs/1704.00028)

# Requirements

## python modules

- tensorflow 1.0
- h5py
- matplotlib
- opencv 3
- numpy
- tqdm
- colorama
- terminaltables
- parmap

# Part 1. Getting the data

- Go to http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
- In the Downloads section, select Align&Cropped images.
- In the dropbox page that follows, download the Anno, Eval and Img folders.
- Copy these folders to `/data/raw`.
- Extract the zip files.

We are only going to use the images

# Part 2. Running the code

Follow [these instructions](https://github.com/tdeboissiere/DeepLearningImplementations/tree/master/WGAN-GP/src/model)


# WGAN-GP

Pure tensorflow implementation of WGAN-GP

**Sources:**

- [Improved Training of Wasserstein GANs](https://arxiv.org/abs/1704.00028)

# Requirements

## python modules

- terminaltables==3.1.0
- colorama==0.3.9
- matplotlib==2.0.2
- tensorflow_gpu==1.3.0
- tqdm==4.17.0
- numpy==1.13.3
- tensorflow==1.4.0rc1

# Part 1. Getting the data

- Go to http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
- In the Downloads section, select Align&Cropped images.
- In the dropbox page that follows, download the Anno, Eval and Img folders.
- Copy these folders to `/data/raw`.
- Extract the zip files.

We are only going to use the images

# Part 2. Running the code

Follow [these instructions](https://github.com/tdeboissiere/DeepLearningImplementations/tree/master/WGAN-GP/src/model)


Update requirements of WGAN GP
Update requirements of WGAN GP
