Comments (2)
sefibk
commented on August 11, 2024
You referred to this also in a different issue - please keep them in a single place!
Regarding the code - I will have to check if it happens to me too! please verify the packages (torch etc.) are identical to requirements.txt before I look into this.
Practically - not how the values in your array are negligible in the boundaries, hence you can simply crop them and you will get an almost IDENTICAL result for the image you are downscaling. That is simply what I did in the paper.
I may have a bug in the code that doesn't crop - but it should!
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qlawliet
commented on August 11, 2024
But in your paper the kernel size should be 13x13.
I look forward to your answer! Thanks!
Hello, I have encountered the same problem as you. May I ask how you finally solve it to make the output kernel size consistent with that in the paper?
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Related Issues (20)
- X4 kernel specs in DIV2KRK HOT 1
- It seems like a bug?
- UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize HOT 5
- RuntimeError: cuDNN error: CUDNN_STATUS_BAD_PARAM HOT 2
- network parameter asking HOT 6
- Why do you swap axis? HOT 2
- why not directly save the params of Generator for downscaling? why not non-linear? HOT 3
- Question about the DownScaleLoss HOT 1
- About DIV2KRK HOT 1
- about Generator and Discriminator output size HOT 5
- Questions about generator networks HOT 2
- How do you generate such an image？ HOT 8
- How do you visualize the ".mat" files HOT 3
- There was a problem with training in another data set HOT 1
- How to gain the PSNR and SSIM HOT 2
- What's the meaning of "input-dir" and "input_img_path"
- Is your training data set the same as your test set HOT 2
- Why there needs flip orperation when calculate the kernel ? HOT 1
- No file .mat HOT 1
- ValueError: shapes (512,512,1) and (3,) not aligned: 1 (dim 2) != 3 (dim 0) HOT 2
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