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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}
}
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