Comments (3)
XuecaiHu
commented on July 23, 2024
Maybe different scale factors have different sizes of the SR images. But all these images are smaller than the HR images. Thus, the pair is (SR,HR(0:h_sr, 0:w_sr,:)), not (SR,HR)
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suke27
commented on July 23, 2024
during training, you need train multi scale at same time, as I try in my side, different scale will interacted on each other. some scale may get best psnr, Meanwhile, some get worse psnr . do you face this problem?
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XuecaiHu
commented on July 23, 2024
no, never
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Related Issues (20)
- Have you debugged it yet？
- Meta-Upscale Module
- meta-upscale
- meta-upscale的输入
- 请问输入矩阵为什么需要mask
- Meta-upscale的实现 HOT 3
- RuntimeError: cuda runtime error (2) HOT 5
- Trying to train Meta-RCAN but failed HOT 2
- Testing directories HOT 3
- rewrite dataloader for more recnt Pytorch
- meta-learning for weight prediction
- dataloader error, help plz~
- Higher PSNR when i use pretrained model?
- 请问怎样运行 geberate_LR_metasr_X1_X4.m 文件？
- Pretrained models
- 如何将MetaUpSampler 改成适用于3d图像的上采样？
- 请问，想改成 针对3d数据，该怎么改？ 比如（batch，C， h, w, d），超分到（batch, C, H, W, D）。 HOT 2
- 你好，能帮忙指点下吗? 改成3d 后 pos_mat_small 维度不是Scale x Scale x Scale x 3的维度？ h_offset这需要改吗？ HOT 3
- 你好，cols = nn.functional.unfold(up_x.permute(0, 2, 3, 1), self.kernel_size, padding=1)，该咋改呀？ HOT 1
- Pre-training model selection for testing
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