Skip to main content

Simple Python Framework for creating GANs and seeing evolution through time

Project description

PyGANs (Machine Learning Framework)

Python Framework for Generative Adversarial Networks. It provides an Abstraction layer to create and train GANs with an integrated monitoring module to see the evolution of the Network through time.

There are incorporated examples that show the usage of the framework in 2D functions and generating Hand Written Digits.

Tested Models:

  • Trigonometric Functions (f(x)=sin(x))
  • Polynomial Functions, for example:
    O f(x) = x**2
    O f(x) = x**5 - 3x**2 - 4
  • HandWritten Digits (MNIST)


PyGANs is available in the Python Package Index (PyPI), so it's possible to install it using the package installer for Python (pip), which install automatically the external dependencies:

$ pip install pygans

External Dependencies

If you install the library using pip, it will install automatically the dependencies.

  • Keras
  • Tensorflow
  • Numpy
  • Matplotlib



BugFix: Random Generation in Dataset_Generator_2D


  • BugFix: MNIST Animation


  • MNIST Supported
  • Simplified API
  • Optimizing training process
  • BugFix: Latent points generation on Standard normal distribution


  • 2D Functions tested
  • 2D animation supported

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for pygans, version 2.0.3
Filename, size File type Python version Upload date Hashes
Filename, size pygans-2.0.3-py3-none-any.whl (8.2 kB) File type Wheel Python version py3 Upload date Hashes View hashes
Filename, size pygans-2.0.3.tar.gz (4.5 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page