Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Meaning of GT saliency scores #16

Closed
QinghongLin opened this issue Aug 14, 2022 · 1 comment
Closed

Meaning of GT saliency scores #16

QinghongLin opened this issue Aug 14, 2022 · 1 comment

Comments

@QinghongLin
Copy link

Thank you for your great work and open-source code.

I have an issue with the GT saliency scores (only localized 2-sec clips), can you please explain briefly?
besides, how Predicted saliency scores (for all 2-sec clip) corresponds to the previous term?

Thanks!

Best,
Kevin

Build models...
Loading feature extractors...
Loading CLIP models
Loading trained Moment-DETR model...
Run prediction...
------------------------------idx0
>> query: Chef makes pizza and cuts it up.
>> video_path: run_on_video/example/RoripwjYFp8_60.0_210.0.mp4
>> GT moments: [[106, 122]]
>> Predicted moments ([start_in_seconds, end_in_seconds, score]): [
    [49.967, 64.9129, 0.9421], 
    [66.4396, 81.0731, 0.9271], 
    [105.9434, 122.0372, 0.9234], 
    [93.2057, 103.3713, 0.2222], 
    ..., 
    [45.3834, 52.2183, 0.0005]
   ]
>> GT saliency scores (only localized 2-sec clips):  # what it means?
    [[2, 3, 3], [2, 3, 3], ...]
>> Predicted saliency scores (for all 2-sec clip):  # how this correspond to the GT saliency scores?
    [-0.9258, -0.8115, -0.7598, ..., 0.0739, 0.1068]  
@QinghongLin
Copy link
Author

Thanks, I have found the answers here.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant