SR replication results mismatch reported values on certain datasets
Thank you very much for your marvelous SR work and opensourcing! When training HAT for classic SISR results, I found a slight mismatch of results:
| SRx2 | Set5 | Set14 | B100 | Urban100 | M109 |
|---|---|---|---|---|---|
| Reported | 38.63/0.9630 | 34.86/0.9274 | 32.62/0.9053 | 34.45/0.9466 | 40.26/0.9809 |
| Replication | 38.61/0.9630 | 34.77/0.9266 | 32.61/0.9053 | 34.45/0.9465 | 40.23/0.9806 |
| SRx4 | Set5 | Set14 | B100 | Urban100 | M109 |
|---|---|---|---|---|---|
| Reported | 33.04/0.9056 | 29.23/0.7973 | 28.00/0.7517 | 27.97/0.8368 | 32.48/0.9292 |
| Replication | 33.00/0.9053 | 29.18/0.7967 | 27.99/0.7515 | 27.97/0.8368 | 32.44/0.9292 |
The replication is done with standard training from scratch setting, i.e. using config train_HAT_SRx2_from_scratch.yml and train_HAT_SRx4_from_scratch.yml.
While replications on other datasets yield similar results to reported values in the paper, I am a bit puzzled by the mismatch of Set14 and Manga109 datasets. I am wondering about the cause of the mismatch: is that a normal fluctuation? Or there might be an inconsistency with test dataset versions? Thanks again!
@sairights Hi, I also met reproduce problems. What's your training settings?
#49
@yumath I used the official code of HAT and the official train-from-scratch setting on DF2K. I also mod2/3/4 for test images, which is what #49 suggests. I think this might be some fluctuation.
@sairights maybe fluctuation about hyper-parameters: iter_num and batch_size? https://github.com/XPixelGroup/HAT/issues/26#issuecomment-1288154862
@yumath Well I used 8 GPUs and kept iter_num and batch_size identically the same with the official setting. Really weird to see that there exists a large gap on Set14 between replications and reported values...