Brunopaes / evil-eye

This project aims in implementing a image GAN. Ideally will be used to learn and generate artists/cartoonists painting styles or in generation of new unique landscapes/scenes.

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Evil Eye: Generative Adversarial Network

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Optimized for python 3.6

This project aims in implementing a image GAN. Ideally will be used to learn and generate artists/cartoonists painting styles or in generation of new unique landscapes/scenes.


Dependencies

For installing the requirements, in your venv or anaconda env, just run the following command:

pip install -r requirements.txt

Project's Structure

.
└── grzmot-gan
    ├── data
    │   ├── generated_data
    │   │   └── generated_data
    │   │       └── 2020-04-02
    │   │           ├── gan_generated_1.png
    │   │           ├── ...
    │   │           └── gan_generated_20.png
    │   └── train_data
    │       ├── img_0.jpg
    │       ├── ...
    │       └── img_128.jpg
    ├── docs
    │   └── CREDITS
    ├── src
    │   ├── __init__.py
    │   └── settings.json
    ├── tests
    │   └── unittests
    │       └── __init__.py
    ├── .gitignore
    ├── LICENSE
    ├── README.md
    └── requirements.txt

Directory description

  • data: The data dir. Group of non-script support files.
  • docs: The documentation dir.
  • src: The scripts & source code dir.
  • tests: The unittests dir.

Usage Notes

Section aimed on clarifying some running issues.

Running

For running it, at the ~/src directory just run:

python fitting.py

or, if importing it as a module, just run:

from fitting import training

if __name__ == '__main__':
    training(100, 128)

About

This project aims in implementing a image GAN. Ideally will be used to learn and generate artists/cartoonists painting styles or in generation of new unique landscapes/scenes.

License:MIT License


Languages

Language:Python 100.0%