Comments (4)
@Ironteen You may check the correctness of your data. Torch 1.8 may also cause abnormal performance.
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@Ironteen You may check the correctness of your data. Torch 1.8 may also cause abnormal performance.
Thanks, I get the right results with torch 1.7. Is torch 1.9 or higher not available?
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@Ironteen Only torch 1.8 has this problem from my experience.
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I am using 1.7.1+cu101, and I got the following which is lower than the paper result.
# psnr: 31.0627 Best: 31.0627 @ HAT_x4_SR_baseline_Set5 iter
# ssim: 0.9060 Best: 0.9060 @ HAT_x4_SR_baseline_Set5 iter
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Related Issues (20)
- RuntimeError: NCCL invalid usage HOT 1
- Having problem while Training on low resolution images
- How to use the package in Mac with M1/M2 chip
- How you calculate macs and params?
- Inquiry on HAT Application for Same-Size Super Resolution HOT 5
- How to modify basicsr code and apply to HAT model? HOT 2
- Can't Reproduce the Results of SRx3
- How can I calculate PSNR&SSIM with only LR images in HAT_SRX4_ImageNet-LR.yml?Thank you!
- Does the Real-HAT have a small version like HAT-S? HOT 6
- Half precision (fp16) Training and Inference of the HAT models HOT 3
- TypeError: calculate_psnr() missing 1 required positional argument: 'img2' HOT 2
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- How to limit the range of the super-resolved image HOT 2
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- Value of RPI in hat_arch.py value
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- About test datasets prepare
- About HAT is an attention module or a module that directly for image super-resolution .
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