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

Pytorch version training. #33

Open
lymdove opened this issue Sep 13, 2022 · 4 comments
Open

Pytorch version training. #33

lymdove opened this issue Sep 13, 2022 · 4 comments
Labels
good first issue Good for newcomers

Comments

@lymdove
Copy link

lymdove commented Sep 13, 2022

Thanks for your great work!
I want to compare my lopp closure method with Overlap, but I have problem with running the work. I use the pytorch version, and I already generate depth, intensity, normal data. I want to compute a score for every pair, but I have no model weights. So I want to train one, but I can not find which file could generate the 'overlaps/train_set.npz'. Could you help me, or could you provide a pre-model. Thanks.

@Chen-Xieyuanli
Copy link
Member

@BIT-MJY could you please provide the pre-trained model using PyTorch?

@lymdove you may also have a look at our novel overlaptransformer: https://github.com/haomo-ai/OverlapTransformer
It is implemented using PyTorch, and the pre-trained model was given.

@Chen-Xieyuanli Chen-Xieyuanli added the good first issue Good for newcomers label Oct 24, 2022
@surajiitd
Copy link

@BIT-MJY could you please provide the pre-trained model using PyTorch?

@surajiitd
Copy link

@lymdove demo/demo4_gen_gt_files.py can generate the train_set.npz file in data/{seq_num}/ground_truth/train_set.npz

@laebe
Copy link
Member

laebe commented Jul 16, 2024

I'm not sure, because I was not involved in the pytorch version. But my guess is that the pytorch version uses the input which can be generated by the non-pytorch version (as stated above e.g. with demo4)

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

No branches or pull requests

4 participants