jeffei / Generative-Models

Comparison of Generative Models in Tensorflow

Comparison of Generative Models in Tensorflow

The different generative models considered here are Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs).

This experiment is accompanied by blog post at : https://kvmanohar22.github.io/Generative-Models

Usage

• Download the MNIST and CIFAR datasets

Train VAE on mnist by running:

python main.py --train --model vae --dataset mnist

Train GAN on mnist by running:

python main.py --train --model gan --dataset mnist

For the complete list of command line options, run:

python main.py --help

The model generates images at a frequence specified by generate_frq which is by default 1.

Results of training GAN on mnist

Sample images from MNIST data is :

On the left is image generated from VAE and on the right is GIF showing images generated from GAN as a function of epochs:

For examples and explanation, have a look at the blog post.