readme: ---
  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}
  }
  ```
  