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.
Fonte do modelo
- Tipo
- Other
- Tamanho do arquivo
- 2,30 GB
- Versão
- vRevision 8b70681
- Atualizado
- 11 de out. de 2026
- Downloads
- 166
- Fonte
- Hugging Face
Descrição da fonte
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)
Fontes
1 fonte
Fontes
1 fonteVerificado 15 de ago.
Artefatos de modelo
2 artefatos
Artefatos de modelo
2 artefatosTrechos de fonte
2 trechos
Trechos de fonte
2 trechos--- 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
