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

Ran PENet pre-trained model and results do not match Kitti benchmark depth completion page #31

Open
manifischer opened this issue Oct 31, 2021 · 4 comments

Comments

@manifischer
Copy link

Thank you very much for a very interesting paper.
I have run the PENet pre-trained model you've provided in evaluation mode on the cropped image.
in the results the code provided (val.csv under results) I got RMSE=757.197 MAE=209.001, compared to RMSE=730.08 MAE=210.55 as it appears in the Kitti benchmark page.
IIs there a different PENet model that matches the submitted results? or there is something in the parameters that I put wrong (I kept the parameters as is in this repository).
Thanks a lot,
Mani

@JUGGHM
Copy link
Owner

JUGGHM commented Nov 1, 2021

Thanks for your interest! It's the same model as it is benchmarked on test set while validated on val set. You could also refer to this issue.

@manifischer
Copy link
Author

Thanks a lot, missed the issue you referred to

@kingLCH
Copy link

kingLCH commented Sep 5, 2022

how to use penet pre-trained model,why it name is end with .tar
it seems cant be loaded by "checkpoint = torch.load(args.evaluate, map_location=device)"

@JUGGHM
Copy link
Owner

JUGGHM commented Sep 6, 2022

how to use penet pre-trained model,why it name is end with .tar it seems cant be loaded by "checkpoint = torch.load(args.evaluate, map_location=device)"

Thanks for your interest! I am afraid taht it is an inherited bug and you can fix it yourself.

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

3 participants