AuraSR v2

--- license: apache-2.0 tags: - art - pytorch - super-resolution pipeline_tag: image-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) ```

Source context: 5 downloads · 0 likes · Pipeline image-to-image · Repo research101/AuraSR-v2

Source context: 6 downloads · 0 likes · Pipeline image-to-image · Repo research101/AuraSR-v2