Open HoYoung-City opened 5 months ago
Hi, thanks for raising this question!
The reported numbers in our paper came from the evaluation in train.py
, which means we used alexnet
for LPIPS.
Meanwhile, we didn't use metrics.py
but kept it in the repo, thinking it might be helpful in some use cases. Therefore, there can be some inconsistency.
BTW, did you get consistent numerical results from metric.py
as those from train.py
after moving to alexnet
?
I used alexnet
in metric.py
, but I got different numerical results.
I haven't found the exact cause yet. It could be my mistake.
Thank you for your reply.
Hi! I noticed an inconsistency in the calculation of the Metric in train.py. The
lpips()
function is used without specifying the net_type option, as seen here: https://github.com/ShenhanQian/GaussianAvatars/blob/f649a11bae59a1622500345b21641781f01fbab7/train.py#L296Then, the default net_type for 'lpips()' is set to 'alex': https://github.com/ShenhanQian/GaussianAvatars/blob/f649a11bae59a1622500345b21641781f01fbab7/lpipsPyTorch/__init__.py#L8
On the other hand, in metrics.py, the net_type for lpips() is set to 'vgg': https://github.com/ShenhanQian/GaussianAvatars/blob/f649a11bae59a1622500345b21641781f01fbab7/metrics.py#L74
This discrepancy could explain why there are differences in the values. I believe that using 'alex' might be the more appropriate option, as it is closer to the results presented in the paper.
Could you please confirm this?
Thank you for looking into this.