Metadata-Version: 2.1
Name: simplegan
Version: 0.2.7
Summary: Framework to ease training of generative models based on TensorFlow
Home-page: https://github.com/grohith327
Author: Rohith Gandhi G
Author-email: grohith327@gmail.com
License: MIT
Keywords: GAN,Computer Vision,Deep Learning,TensorFlow,Generative Models,Neural Networks,AI
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
Requires-Dist: tensorflow (==2.0.1)
Requires-Dist: tqdm
Requires-Dist: numpy
Requires-Dist: opencv-python
Requires-Dist: imageio
Requires-Dist: tensorflow-datasets

# SimpleGAN

[![License](http://img.shields.io/badge/license-MIT-brightgreen.svg?style=flat)](LICENSE) [![Documentation Status](https://readthedocs.org/projects/simplegan/badge/?version=latest)](https://simplegan.readthedocs.io/en/latest/?badge=latest)

**Framework to ease training of generative models**

SimpleGAN is a framework based on [TensorFlow](https://www.tensorflow.org/) to make training of generative models easier. SimpleGAN provides high level APIs with customizability options to user which allows them to train a generative model with few lines of code.
### Requirements
Make sure you have the following packages installed
* [tensorflow](https://www.tensorflow.org/install)
* [tqdm](https://github.com/tqdm/tqdm#latest-pypi-stable-release)
* [imagio](https://pypi.org/project/imageio/)
* [opencv](https://pypi.org/project/opencv-python/)
* [tensorflow-datasets](https://www.tensorflow.org/datasets/overview#installation)
### Installation
Latest stable release:
```bash
  $ pip install simplegan
```
Latest Development release:
```bash
  $ pip install git+https://github.com/grohith327/EasyGAN.git
```
### Getting Started
##### DCGAN
```python
>>> from simplegan.gan import DCGAN
>>> gan = DCGAN()
>>> train_ds = gan.load_data(use_mnist = True)
>>> samples = gan.get_sample(train_ds, n_samples = 5)
>>> gan.fit(train_ds = train_ds)
>>> generated_samples = gan.generate_samples(n_samples = 5)
```
##### Convolutional Autoencoder
```python
>>> from simplegan.autoencoder import ConvolutionalAutoencoder
>>> autoenc = ConvolutionalAutoencoder()
>>> train_ds, test_ds = autoenc.load_data(use_cifar10 = True)
>>> train_sample = autoenc.get_sample(data = train_ds, n_samples = 5)
>>> test_sample = autoenc.get_sample(data = test_ds, n_samples = 1)
>>> autoenc.fit(train_ds = train_ds, epochs = 5, optimizer = 'RMSprop', learning_rate = 0.002)
>>> generated_samples = autoenc.generate_samples(test_ds = test_ds.take(1))
```
To have a look at more examples in detail, check [here](examples)
### Documentation
Check out the [docs page](https://simplegan.readthedocs.io/en/latest/)
### Provided models
* Autoencoders
    * Vanilla Autoencoder
    * Convolutional Autoencoder
    * Variational Autoencoder [[Paper](https://arxiv.org/abs/1312.6114)]
    * Vector Quantized - Variational Autoencoder [[Paper](https://arxiv.org/abs/1711.00937)]
* Generative Adversarial Networks(GANs)
    * Vanilla GAN [[Paper](https://arxiv.org/abs/1406.2661)]
    * DCGAN [[Paper](https://arxiv.org/abs/1511.06434)]
    * WGAN [[Paper](https://arxiv.org/abs/1701.07875)]
    * CGAN [[Paper](https://arxiv.org/abs/1411.1784)]
    * InfoGAN [[Paper](https://arxiv.org/abs/1606.03657)]
    * Pix2Pix [[Paper](https://arxiv.org/abs/1611.07004)]
    * CycleGAN [[Paper](https://arxiv.org/abs/1703.10593)]
### Contributing
We appreciate all contributions. If you are planning to perform bug-fixes, add new features or models, please file an issue and discuss before making a pull request.
### Contributors 
* [Rohith Gandhi](https://github.com/grohith327)
* [Prem Kumar](https://github.com/Prem-kumar27)


