Model Description
ESRGAN: ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution
Paper Repo: Implementation of paper.
Installation
pip install bsrgan
BSRGAN Usage
from bsrgan import BSRGAN
model = BSRGAN(weights='kadirnar/RRDB_PSNR_x4', device='cuda:0', hf_model=True)
model.save = True
pred = model.predict(img_path='data/image/test.png')
BibTeX Entry and Citation Info
@inproceedings{zhang2021designing,
title={Designing a Practical Degradation Model for Deep Blind Image Super-Resolution},
author={Zhang, Kai and Liang, Jingyun and Van Gool, Luc and Timofte, Radu},
booktitle={IEEE International Conference on Computer Vision},
pages={4791--4800},
year={2021}
}
@InProceedings{wang2018esrgan,
author = {Wang, Xintao and Yu, Ke and Wu, Shixiang and Gu, Jinjin and Liu, Yihao and Dong, Chao and Qiao, Yu and Loy, Chen Change},
title = {ESRGAN: Enhanced super-resolution generative adversarial networks},
booktitle = {The European Conference on Computer Vision Workshops (ECCVW)},
month = {September},
year = {2018}
}