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.
You can download installers and advanced batch App from below link:
https://www.patreon.com/posts/110060645
Check the screenshots and examples below
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
Download zip file from : https://www.patreon.com/posts/110060645
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
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
Furkan Gözükara
2024-09-04 14:48:51 +0000 UTCFossil Bluff
2024-09-04 14:27:49 +0000 UTC