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Hi~
Thanks for your great work!
I have a small question about the LPIPS evaluation.
Actually, you do the LPIPS evaluation with evaluate_lpips() in: https://github.com/phizaz/diffae/blob/master/experiment.py#L606. The function evaluate_lpips() is defined in: https://github.com/phizaz/diffae/blob/master/metrics.py#L44.
evaluate_lpips()
Then in evaluate_lpips(), I track the input imgs with the following paths:
imgs
I find that, finally, in p_mean_variance(), you pass x (which equals imgs and is the original image) directly into model.forward() (See: https://github.com/phizaz/diffae/blob/master/diffusion/base.py#L307).
p_mean_variance()
x
model.forward()
Here I am confused, since we should input x_T instead of x (the original image) into model.forward() for evaluation.
x_T
Could you please explain it for me?
Thanks in advance.
The text was updated successfully, but these errors were encountered:
Hi! Thanks for your discovery. I have the same confusion. And may I ask if you have resolved it?
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Hi~
Thanks for your great work!
I have a small question about the LPIPS evaluation.
Actually, you do the LPIPS evaluation with
evaluate_lpips()
in: https://github.com/phizaz/diffae/blob/master/experiment.py#L606. The functionevaluate_lpips()
is defined in:https://github.com/phizaz/diffae/blob/master/metrics.py#L44.
Then in
evaluate_lpips()
, I track the inputimgs
with the following paths:I find that, finally, in
p_mean_variance()
, you passx
(which equalsimgs
and is the original image) directly intomodel.forward()
(See: https://github.com/phizaz/diffae/blob/master/diffusion/base.py#L307).Here I am confused, since we should input
x_T
instead ofx
(the original image) intomodel.forward()
for evaluation.Could you please explain it for me?
Thanks in advance.
The text was updated successfully, but these errors were encountered: