AIP_project

This project is done for the course Advanced Image Processing 2022 at Indian Institute odf Science.

We attempt to understand and analyze recently proposed Style based image generators, popularly known as StyleGANs.

StyleGAN: Analyse the improvements

• Compared the network architecture of StyleGAN and StyleGAN2
• Proposed error metrics for quantitatively compare these two GANs
• Have validated the improvements of StyleGAN2 over StyleGAN

System Requirements

• Both Linux and Windows are supported, but we strongly recommend Linux for performance and compatibility reasons.
• 64-bit Python 3.6 installation. We recommend Anaconda3 with numpy 1.14.3 or newer.
• TensorFlow 1.10.0 or newer with GPU support.
• One or more high-end NVIDIA GPUs with at least 11GB of DRAM. We recommend NVIDIA DGX-1 with 8 Tesla V100 GPUs.
• NVIDIA driver 391.35 or newer, CUDA toolkit 9.0 or newer, cuDNN 7.3.1 or newer.

Code for StyleGAN and StyleGAN2

https://colab.research.google.com/github/keras-team/keras-io/blob/master/examples/generative/ipynb/stylegan.ipynb https://colab.research.google.com/github/parthsuresh/stylegan2-colab/blob/master/StyleGAN2_Google_Colab.ipynb