Keras implementation of InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
- keras, theano or tensorflow backend
- h5py
- matplotlib
- opencv 3
- numpy
- tqdm
- parmap
Follow these instructions.
Follow these instructions
MNIST example results
Note 1 The figures below were obtained with a slight modification of the original InfoGAN paper: supervised categorical cross entropy loss for the discriminator and simple MSE loss for the continuous variables. Credits to @burisuriburi for the original idea.
Note 2 The code in this repository matches OpenAI's original implementation, without the trick of Note 1.
Varying the categorical code along each row:
Varying the continuous code along rows and columns:
