ArtGan

Creating Art with Generative Adversarial Networks

Implementations of DC-GANs and WGANs in order to generate Art. Art images from Wikiart. MNIST and CIFAR-10 are also avalaible as toy datasets. The networks are trained to not only learn the dataset distribution, but also be able to chose the art style generated.

Example of generated art

Mixing of different art style generated

The network is asked to generate 2 art styles at the same time.

To train your own network

MNIST

Run python main_mnist.py for DC-GAN or python main_mnist_wgan.py for wgan.

CIFAR-10

Run python main_cifar.py for DC-GAN or python main_cifar_wgan.py for wgan.

WikiArt

Download wikipaintings at www.lamsade.dauphine.fr/~bnegrevergne/webpage/software/rasta/wikipaintings_full.tgz.

Update the data path in main_art_wgan.py

Run the command python main_art_wgan.py