SpriteGAN

SpriteGAN generates Pokèmon sprites from original 151 Pokèmon Yellow sprites. It is a implementation of DCGAN using the keras library.

Deep Convolutional Generative Adversarial Network consists of two networks:

Generator - tries to generate fake images from noise so as to fool the discriminator network
Discriminator - tries to distinguish real images from fake ones

Dependencies

Usage

Download and install Jupyter Notebook and IPython kernel
run a Jupyter environment locally using jupyter notebook in the terminal
set path variable in model_train
set save location in save_imgs()
set use_prev to false to use pretrained models
call model_train for atleast 10 epochs to generate novel sprites

Example Output

References

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks