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

How can I train from scratch? #4

Open
Rogerlv51 opened this issue Jul 5, 2023 · 3 comments
Open

How can I train from scratch? #4

Rogerlv51 opened this issue Jul 5, 2023 · 3 comments

Comments

@Rogerlv51
Copy link

Rogerlv51 commented Jul 5, 2023

hello, thank for your outstanding work! I wonder how can I train from scratch by using SemanticKITTI datasets? Hope your reply, thank u. @Sangminhong

@Sangminhong
Copy link
Owner

hello, thank for your outstanding work! I wonder how can I train from scratch by using SemanticKITTI datasets? Hope your reply, thank u. @Sangminhong
You can try this command.
CUDA_VISIBLE_DEVICES=0 python main.py --experiment_id {experiment id} --dataset_name {SemanticKITTI} --class_name {car}

If it still doesn't works, please tell me the detailed issue you have. Thank you

@Rogerlv51
Copy link
Author

Thanks for your reply! However, when I building the virtual environment, i have met this problems:
Pip subprocess error:
ERROR: Could not find a version that satisfies the requirement chamfer-3d==0.0.0 (from versions: none)
ERROR: No matching distribution found for chamfer-3d==0.0.0

failed

CondaEnvException: Pip failed

I just used your command: conda env create -f environment.yml --name ACL_SPC @Sangminhong

@Sangminhong
Copy link
Owner

Thanks for your reply! However, when I building the virtual environment, i have met this problems: Pip subprocess error: ERROR: Could not find a version that satisfies the requirement chamfer-3d==0.0.0 (from versions: none) ERROR: No matching distribution found for chamfer-3d==0.0.0

failed

CondaEnvException: Pip failed

I just used your command: conda env create -f environment.yml --name ACL_SPC @Sangminhong

Sorry that the environment.yml file did not work for you. Since every computer has different settings, it is difficult to make environment.yml that works for everyone. In this case you can download the packages by yourself which is not very difficult. If you still have problems, please feel free to ask.

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

2 participants