kvmanohar22 / Generative Models
Comparison of Generative Models in Tensorflow
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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.
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