aura-sr 0.0.1

GAN-based Super-Resolution for real-world images, a variation of the GigaGAN paper.

AuraSR

GAN-based Super-Resolution for real-world 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()

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)