| --- |
| license: apache-2.0 |
| tags: |
| - Super-Resolution |
| - computer-vision |
| - ESRGAN |
| - gan |
| --- |
| |
| ### Model Description |
| [ESRGAN](https://arxiv.org/abs/2107.10833): ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution |
|
|
| [Paper Repo](https://github.com/xinntao/ESRGAN): Implementation of paper. |
|
|
| ### Installation |
| ``` |
| pip install bsrgan |
| ``` |
|
|
| ### BSRGAN Usage |
| ```python |
| from bsrgan import BSRGAN |
| |
| model = BSRGAN(weights='kadirnar/RRDB_ESRGAN_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} |
| } |
| ``` |
|
|
