AuraSR GigaGAN 4x Upscaler Local (Windows), Cloud (RunPod, Massed Compute, Kaggle) 1-Click Installers and Batch Processing App (Patreon)

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AuraSR is a 600M parameter upsampler model derived from the GigaGAN paper. It works super fast and uses a very limited VRAM below 5 GB. It is deterministic upscaler. It works perfect in some images but fails in some images so it is worth to give it a shot.

GitHub official repo : https://github.com/fal-ai/aura-sr

I have developed 1-click installers and a batch upscaler App.

Check the screenshots and examples below

Windows Requirements

• Python 3.10, FFmpeg, Cuda 11.8, C++ tools and Git

• If it doesn't work make sure to below tutorial and install everything exactly as shown in this below tutorial

• https://youtu.be/-NjNy7afOQ0

How to Install and Use on Windows

• Extract the attached GigaGAN_Upscaler_v1.zip into a folder like c:/giga_upscale

• Then double click and install with Windows_Install.bat file

• It will generate an isolated virtual environment venv folder and install requirements

• Then double click and start the Gradio App with Windows_Start_App.bat file

• When first time running it will download models into your Hugging Face cache folder

• Hugging Face cache folder setup explained below

• https://www.patreon.com/posts/108419878

• All upscaled images will be saved into outputs folder automatically with same name and plus numbering if necessary

• You can also batch upscale a folder

How to Install and Use on Cloud

• Follow Massed Compute and RunPod instructions

• Usage is same as on Windows

• For Kaggle start a Kaggle notebook, import our Kaggle notebook and follow the instructions

App Screenshots and Examples