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We have several separate cases.
It is important that the downscaling method will be the correct one (= approximately the one by which the test image was downscaled from the theoretic ground-truth image [that may not exist]).
For the ideal case (= we have prior knowledge that the correct downscaling is bicubic), we just use bicubic downscaling.
For the non-ideal case we use a given input-kernel.
(for unknown kernel we need to first estimate the kernel, for example using our method KernelGAN: https://github.com/sefibk/KernelGAN).
Hi, thank you for sharing the code.
which downsampling method do you use to generate the LR image from the testing image?
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