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The project covers common metrics for super-resolution performance evaluation.

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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', 'PSNR-Y', 'SSIM', 'SSIM-Y' 'BRISQUE', 'LPIPS'.

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 pythonThreadPoolExecutor
  • Both RGB and YCbCr color space support
  • One2Many support : Since there are many SR methods that allow multiple predictions for a given low resolution image. In order to simplify the configuration, it is specially designed.

Dependencies

Instructions for use this code

Please ref BLIND IMAGE QUALITY TOOLBOX

Note

  • Please ensure that SR and GT are the same size.

Reference

The code is based on SPSR and BIQT.

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The project covers common metrics for super-resolution performance evaluation.

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