Super-Resolution Performance Evaluation Code
The project covers common metrics for super-resolution performance evaluation.
Metrics support
The scripts will calculate the values of the following evaluation metrics:
'MA'
,
'NIQE'
,
'PI'
, 'PSNR'
,
'BRISQUE'
,
'SSIM'
, 'MSE'
, 'RMSE'
, 'MAE'
,
'LPIPS'
.
Note that the 'SSIM'
values are calculated by ssim.m
, the matlab code including the suggested downsampling process available in this link.
Highlights
- Breakpoint continuation support : The program can continue from where it was last interrupted by using
.xlsx
file - Parallel computing support : The Programs can be re-scaled to take advantage of multi-core performance by using python
ThreadPoolExecutor
- Both RGB and YCbCr color space support
Dependencies
- Python 3
- PyTorch >= 1.0
- Matlab
Instructions for use this code
Please ref BLIND IMAGE QUALITY TOOLBOX
Reference
The code is based on SPSR and BIQT.