Skip to content

Keras implementation of Deep Convolutional Generative Adversarial Networks

Notifications You must be signed in to change notification settings

jacobgil/keras-dcgan

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

20 Commits
 
 
 
 
 
 

Repository files navigation

KERAS-DCGAN

Implementation of http://arxiv.org/abs/1511.06434 with the (awesome) keras library, for generating artificial images with deep learning.

This trains two adversarial deep learning models on real images, in order to produce artificial images that look real.

The generator model tries to produce images that look real and get a high score from the discriminator.

The discriminator model tries to tell apart between real images and artificial images from the generator.


This assumes theano ordering. You can still use this with tensorflow, by setting "image_dim_ordering": "th" in ~/.keras/keras.json (although this will be slower).


Usage

Training:

python dcgan.py --mode train --batch_size <batch_size>

python dcgan.py --mode train --path ~/images --batch_size 128

Image generation:

python dcgan.py --mode generate --batch_size <batch_size>

python dcgan.py --mode generate --batch_size <batch_size> --nice : top 5% images according to discriminator

python dcgan.py --mode generate --batch_size 128


Result

generated images :

generated_image.png

nice_generated_image.png

train process :

training_process.gif


About

Keras implementation of Deep Convolutional Generative Adversarial Networks

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •  

Languages