Comments (8)
Thanks for your attention.
If you want to test on GOPRO dataset, please make sure that it uses the pretrained model named "CDVD_TSP_GOPRO.pt".
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Thanks for your attention.
If you want to test on GOPRO dataset, please make sure that it uses the pretrained model named "CDVD_TSP_GOPRO.pt".
Thanks for your reply: )!For GOPRO dataset, I'm sure I use "CDVD_TSP_GOPRO.pt", and for DVD dataset, I use "CDVD_TSP_DVD_Convergent.pt" which also cannot obtain the reported results.
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I just re-downloaded the GOPRO test dataset and the pretrained model from the given link "https://drive.google.com/drive/folders/1lw_1jITafEQ9DvMys_S6aYwtNApYKWsz?usp=sharing".
And, I ran the commands:
cd ./code
python inference.py --default_data GOPRO
Then, I got the same results reported in the paper.
So, please make sure that you followed the "https://github.com/csbhr/CDVD-TSP#quick-test" steps in the README.
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I just re-downloaded the GOPRO test dataset and the pretrained model from the given link "https://drive.google.com/drive/folders/1lw_1jITafEQ9DvMys_S6aYwtNApYKWsz?usp=sharing".
And, I ran the commands:
cd ./code
python inference.py --default_data GOPROThen, I got the same results reported in the paper.
So, please make sure that you followed the "https://github.com/csbhr/CDVD-TSP#quick-test" steps in the README.
Thanks for your efforts!
I use the below command to test the performance previously:
python main.py --dir_data ../dataset/GOPRO/train --dir_data_test ../dataset/GOPRO/test --epochs 1 --batch_size 8 --test_only --pre_train ../pretrain_models/CDVD_TSP_GOPRO.pt
And following your last reply, I have retested the performance on the two datasets again using the quick-test commands you recommend. But I still can't obtain the reported performance (only about 28.+dB).
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You can try to re-download the codes, test datasets and pretrained models.
Then run the commands again:
cd ./code
python inference.py --default_data GOPRO
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Here is the inference log on GOPRO dataset, that I tested last night.
https://drive.google.com/file/d/1nMDERzlZRgkszPZcl8kIlFTf0CPQj824/view?usp=sharing
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You can try to re-download the codes, test datasets and pretrained models.
Then run the commands again:
cd ./code
python inference.py --default_data GOPRO
I re-download the codes and re-test the performance again. Finally obtain the results:
Total AVG-PSNR=28.565, AVG-SSIM=0.8746
So it seems a little strange. Whether you modify the codes after releasing the work or use another pretrained model to test?
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Again, I downloaded the codes, pre-trained models and test dataset.
I did not modify anything, just ran the commands:
cd ./code
python inference.py --default_data GOPRO
Then, I got the same results reported in the paper.
Please check whether there is something wrong with your operation.
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