GithubHelp home page GithubHelp logo

generative-adversarial-nets-mnist's Introduction

Generative Adversarial Nets (GAN) for MNIST

TensorFlow implementation of "Generative Adversarial Nets" that generates images of handwritten digits.

Requirements

  • Python 3.5
  • TensorFlow 0.12
  • NumPy
  • Matplotlib

Usage

Clone the repository

$ git clone https://github.com/hayago/generative-adversarial-nets-mnist.git
$ cd gan-tensorflow-mnist

Execute

$ python gan.py

Result

0 iterations

alt text

20,000 iterations

alt text

40,000 iterations

alt text

80,000 iterations

alt text

120,000 iterations

alt text

References

  1. Generative Adversarial Nets
  2. Agustinus Kristiadi's Blog

generative-adversarial-nets-mnist's People

Contributors

hayago avatar

Watchers

James Cloos avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.