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I used the pre-trained RCAN_BIX2 to train RCAB_BIX3 or RCAB_BIX4, as written in your TrainRCAN_scripts.sh .
However, the training loss is too large. If I use pre-trained RCAB_BIX2 to train RCAB_BIX3 …
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From the paper I found RCAN+ has improved a large margin compared with RCAN, so how to evaluate? Thanks a lot for your work.
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https://github.com/wayne391/Image-Super-Resolution/blob/master/src/models/RCAN.py
Just change
`optimizer = torch.optim.Adam(model.parameters(), lr=1e-4, amsgrad=False)`
to
`optimizer = adabound.…
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Sorry to bother you. I try to reproduce the experiment，when I run the test
python main.py --data_test MyImage --scale 2 --model RCAN --n_resgroups 10 --n_resblocks 20 --n_feats 64 --pre_train ../mode…
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Hi, @daitao
Sorry to disturb, I think you have made an error in your SAN paper.
RCAN have less parameters than SAN that RCAN contains ```15.44M``` and SAN contains ```15.7M```.
(This value is repo…
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Hello,thanks for sharing the source code and experimental results.
I want to train a model with my own dataset, but there exist some problems in the process of training, hoping you can give some sugg…
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Thank you for your wonderful work !
Recently I have trained a model with my own datasets, but when I test it ,there seems to be something wrong I can't understand. The error is described as below:
…
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Hi,
When I try to reproduct RCAN, I use ```CUDA_VISIBLE_DEVICES=1 nohup python main.py --model RCAN --save RCAN --scale 2 --save_results --n_resgroups 10 --n_resblocks 20 --patch_size 96 --chop --te…
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Thanks for your great job. I feel confused about the test results when train RCAN model. I use "CUDA_VISIBLE_DEVICES=1 python main.py --model RCAN --save RCAN_G10R20_X2 --scale 2 --save_results --epoc…
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Hi, thanks for sharing your code with us. When I utilize your pretrained model, the code does not work. It said that 'DataLossError (see above for traceback): Unable to open table file ./model/RCAN_X2…