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Hi,
I downloaded the TSN (RGB) checkpoint to test it. After looking at the configuration attributes I saw that the mean and the std values for data pre-processing were actually the same. It is on purpose ?
If I do: ckpt = torch.load("path/to/tosn_rgb.ckpt", map_location=lambda storage, loc: storage) cfg = OmegaConf.create(ckpt["hyper_parameters"]) OmegaConf.set_struct(cfg, False) cfg.data._root_gulp_dir = os.getcwd() print(cfg.data.preprocessing.mean) print(cfg.data.preprocessing.std)
Then I have: 'mean': [0.485, 0.456, 0.406] 'std': [0.485, 0.456, 0.406]
Actually after looking at the checkpoints of TRN and TMN I saw that they also have this problem.
Thanks.
The text was updated successfully, but these errors were encountered:
Hi @bguetarni,
This has been rectified in d58e695 and the models have also been updated, you should find that if you redownload them (same URLs as before), then the std property will be correct.
Thanks again for raising the issue!
Hi @bguetarni,
It turns out I was mistaken and I did in fact train these models with the same mean and std, see #8 for more details. I've reverted the checkpoints to their original variants.
Hi,
I downloaded the TSN (RGB) checkpoint to test it. After looking at the configuration attributes I saw that the mean and the std values for data pre-processing were actually the same. It is on purpose ?
If I do:
ckpt = torch.load("path/to/tosn_rgb.ckpt", map_location=lambda storage, loc: storage)
cfg = OmegaConf.create(ckpt["hyper_parameters"])
OmegaConf.set_struct(cfg, False)
cfg.data._root_gulp_dir = os.getcwd()
print(cfg.data.preprocessing.mean)
print(cfg.data.preprocessing.std)
Then I have:
'mean': [0.485, 0.456, 0.406]
'std': [0.485, 0.456, 0.406]
Actually after looking at the checkpoints of TRN and TMN I saw that they also have this problem.
Thanks.
The text was updated successfully, but these errors were encountered: