mjdietzx/GAN-Sandbox
Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising variations of GANs like conditional and Wasserstein.
This project helps machine learning researchers and practitioners rapidly experiment with Generative Adversarial Networks (GANs). It provides a structured starting point and various pre-implemented GAN architectures, taking in raw data (like images) and producing new, synthetic data that mimics the original. It's designed for those who develop or research AI models capable of generating realistic content.
219 stars. No commits in the last 6 months.
Use this if you are a machine learning researcher or engineer looking to quickly test and iterate on different GAN architectures for synthetic data generation.
Not ideal if you are an end-user seeking an out-of-the-box solution for generating specific types of data without diving into the underlying model architecture and training process.
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219
Forks
71
Language
Python
License
MIT
Category
Last pushed
May 18, 2017
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