LPIPS with Alex net returns Nan #33
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
@francois-rozet could you look at the changes? |
|
Hello @ilpoli, thank you for your PR! I made |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
LPIPS with Alex net returns Nan
The issue is caused by some of the feature layers might zero and it leads to Nan during their normalization. Original implementation uses small epsilon to avoid the issue https://github.com/richzhang/PerceptualSimilarity/blob/31bc1271ae6f13b7e281b9959ac24a5e8f2ed522/lpips/__init__.py#L13
I've verified that results, after changes, are the same as in the original lib (PerceptualSimilarity).
Here are pictures that lead to Nan measure (I hope GitHub attaches images without additional compressing if so, I'll send them in zip):
