AuraSR
GAN-based Super-Resolution for upscaling generated images, a variation of the GigaGAN paper for image-conditioned upscaling. Torch implementation is based on the unofficial lucidrains/gigagan-pytorch repository.
Model source
- Kind
- Other
- File size
- 2.30 GB
- Version
- vRevision 8b70681
- Updated
- Oct 11, 2026
- Downloads
- 166
- Source
- Hugging Face
Source description
AuraSR
aurasr example
GAN-based Super-Resolution for upscaling generated images, a variation of the GigaGAN paper for image-conditioned upscaling. Torch implementation is based on the unofficial lucidrains/gigagan-pytorch repository.
Usage
$ pip install aura-sr
from aura_sr import AuraSR
aura_sr = AuraSR.from_pretrained("fal-ai/AuraSR")
import requests
from io import BytesIO
from PIL import Image
def load_image_from_url(url):
response = requests.get(url)
image_data = BytesIO(response.content)
return Image.open(image_data)
image = load_image_from_url("https://mingukkang.github.io/GigaGAN/static/images/iguana_output.jpg").resize((256, 256))
upscaled_image = aura_sr.upscale_4x(image)
Sources
1 source
Sources
1 sourceVerified Aug 15
Model artifacts
2 artifacts
Model artifacts
2 artifactsSource excerpts
2 excerpts
Source excerpts
2 excerpts--- license: cc tags: - art - pytorch - super-resolution --- # AuraSR  GAN-based Super-Resolution for upscaling generated images, a variation of the [GigaGAN](https://mingukkang.github.io/GigaGAN/) paper for image-conditioned upscaling. Torch implementation is based on the unofficial [lucidrains/gigagan-pytorch](https://github.com/lucidrains/gigagan-pytorch) repository. ## Usage ```bash $ pip install aura-sr ``` ```python from aura_sr import AuraSR aura_sr = AuraSR.from_pretrained("fal-ai/AuraSR") ``` ```python import requests from io import BytesIO from PIL import Image def load_image_from_url(url): response = requests.get(url) image_data = BytesIO(response.content) return Image.open(image_data) image = load_image_from_url("https://mingukkang.github.io/GigaGAN/static/images/iguana_output.jpg").resize((256, 256)) upscaled_image = aura_sr.upscale_4x(image) ```
Source context: 166 downloads · 308 likes · Library transformers · Repo fal/AuraSR
