Skip to content

Conditional Wasserstein GAN with gradient penalty for image generation trained with mnist dataset

Notifications You must be signed in to change notification settings

avkhimen/CWGAN-GP-image-generation

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Conditional Wasserstein GAN for Synthetic Image Generation

Conditional Wasserstein GAN with gradient penalty for the generation of synthetic images.

Description

MNIST dataset was used to train the conditional WGAN. Gradient Penalty was also implemented.

Run the cells in sequence in cwgan-gp.ipynb jupyter notebook. Final cell contains code to create synthetic image conditioned on a label.

Code in part based on:

Getting Started

Dependencies

  • tensorflow
  • numpy
  • matplotlib

See requirements.txt file.

License

Free to use for any purpose

About

Conditional Wasserstein GAN with gradient penalty for image generation trained with mnist dataset

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published