WIP of Robbie Barrat's Art DCGAN in Keras.

I didn't know how GANs worked, and I wanted to know how GANs worked... oh, and that AI painting sold for $432,500.

Since Torch is an utter nightmare to install on Windows, here's a Keras implementation of Barrat's Art DCGAN

The code was originally Jason Brownlee's CIFAR10 GAN before I butchered it

The topology of the Discriminator and Generator are from Barrat's Art DCGAN with fewer filters so it doesn't OOM on a GTX980Ti

Model based on Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks (2015 preprint, Radford, et al.)

Currently, images MUST be RGB and 128x128

python keras-art-dcgan.py -dataset=datasetname

Image data should all be in /data/datasetname

Four examples and models are saved every time an epoch is finished

python keras-art-dcgan.py -dataset=datasetname -save_model=faces -load_model=faces

The d and g models will be saved into ./output/weights/ as faces-d.h5 and faces-g.h5 The d and g models will be loaded from the above, selecting the -d and -g is automated, just provide a name

• Keras
• Tensorflow (or Theano if you switch it to channels last)
• NumPy
• Pillow
• progressbar

This is very heavily a WIP!

Wishlist:

• Let user define network hyperparameters
• Dynamic image input size
• Allow images of only one colour channel
• Figure out a better topology for faster learning
• Figure out a better topology to prevent failure cases (eg. losses hitting 0 and training ceasing)
• Properly implement and test Barrat's topology - currently I am using a GTX980Ti which doesn't have enough memory for the amount of filters he uses in the two networks. I've watered it down slightly as to have fewer parameters

Sometimes, depending on data, losses can hit 0 and training will cease.

I'm not sure (yet) how to fix this if it's the Generator, but if the Discriminator is too strong then it can help to add Leaky ReLu or Dropout between the CNN layers.

Datasets should be relatively varied, but not so much as to throw the model off-genre (unless that's what you're going for!)

I'd love to see what you generate using this, please post your synthesised images!

Cheers,

Jordan J. Bird

http://jordanjamesbird.com/