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---
license: apache-2.0
tags:
- art
- pytorch
- super-resolution
pipeline_tag: text-to-image
---
# AuraSR-v2
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/AuraSR-v2")
```
```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_overlapped(image)
``` |