Skip to content

A GAN model to perform super-resolution - convert low quality image to high quality by filling missing data

Notifications You must be signed in to change notification settings

grajat90/ResampleGAN

Repository files navigation

ResampleGAN

Resample LQ images to HQ using Generative Adversarial Networks


Implementations

The following models have been created for rough reference: GEN DIS


Our results

COMPARISON


Tools:

We'll be working with these currently for rapid prototyping and realising the models:

  • Tensorflow
  • Keras
  • Pandas
  • Numpy
  • Matplolib
  • PILlow

Clone this repo

Install git from here(windows) or in mac, run: Note: You can skip installing git on a mac if you have xcode command line tools installed

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install.sh)"
brew install git

After that, just run

git clone https://github.com/grajat90/ResampleGAN
cd ResampleGAN && git init
git remote add origin git@github.com:grajat90/ResampleGAN.git
git pull origin

About

A GAN model to perform super-resolution - convert low quality image to high quality by filling missing data

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published