# DPSR
**Repository Path**: wangchsoft/DPSR
## Basic Information
- **Project Name**: DPSR
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-11-09
- **Last Updated**: 2020-12-19
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# DPSR
# Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels (CVPR, 2019)
- Related work: [DPIR](https://github.com/cszn/DPIR)
# Training and testing codes for the super-resolver prior ([PyTorch](https://github.com/cszn/KAIR))
- [main_train_dpsr.py](https://github.com/cszn/KAIR/blob/master/main_train_dpsr.py)
- [main_test_dpsr.py](https://github.com/cszn/KAIR/blob/master/main_test_dpsr.py)
***
The left is the blurry LR image. The right is the super-resolved image by DPSRGAN with scale factor 4.
Run [demo_test_dpsr.py](demo_test_dpsr.py) to produce the following results.
***
Super-resolved images of LR image [chip.png](testsets/real_imgs/LR/chip.png) by DPSR with scale factors 2, 3 and 4.
Run [demo_test_dpsr_real.py](demo_test_dpsr_real.py) to produce the following results.
LR
x2
x3
x4
# Requirements and Dependencies
- Spyder (Python 3.6)
- PyTorch 0.4.1
- Windows 10
# Citation
```BibTex
@inproceedings{zhang2019deep,
title={Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels},
author={Zhang, Kai and Zuo, Wangmeng and Zhang, Lei},
booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
pages={1671--1681},
year={2019}
}
```