Skip to content

Implementation of Deep Convolutional Generative Adverserial Network (DCGAN) in Tensorflow with support for Tensorboard and configured to be trained on CelebA dataset

Notifications You must be signed in to change notification settings

MohamedRamzy1/DCGAN-Tensorflow

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

1 Commit
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

DCGAN-Tensorflow

Implementation of Deep Convolutional Generative Adverserial Network (DCGAN) in Tensorflow with support for Tensorboard and configured to be trained on CelebA dataset.

Generator

DCGAN net

Disciminator

Discriminator

Requirements

Here are the requirements to run DCGAN-Tensorflow

  • Python 2.7 or Python 3.3+
  • Tensorflow >= 0.12
  • Numpy
  • tqdm
  • json
  • Bunch

Usage

Edit the values in config.json file to fit your experiment as follows:

{
    "exp_name" : "dcgan_small_64",
    "num_epochs": 20,
    "batch_size": 128,
    "img_size":64,
    "lr":0.0002,
    "beta1":0.5,
    "summaries_period":100, 
    "gf_dim":64,
    "df_dim":64,
    "data_dir": "../img_align_celeba",
    "noise_shape":100,
    "max_to_keep":3
}

summaries_period: How frequently summaries are written for example 20, then it will write summaries after every 20 steps.

gf_dim: Number of filters in the last layer in the Generator network.

gf_dim: Number of filters in the first layer in the Discriminator network.

max_to_keep: Maximum number of checkpoints kept in the checkpoints directory.

And then you run the code as follows:

python main.py

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT

About

Implementation of Deep Convolutional Generative Adverserial Network (DCGAN) in Tensorflow with support for Tensorboard and configured to be trained on CelebA dataset

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages