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

Use DETR3D to train my own dataset #64

Open
zhangbaoj opened this issue Feb 17, 2023 · 2 comments
Open

Use DETR3D to train my own dataset #64

zhangbaoj opened this issue Feb 17, 2023 · 2 comments

Comments

@zhangbaoj
Copy link

Hello, I want to use the DETR3D algorithm to train on my own dataset. But now I can't label my dataset in the nusences dataset format, only in the kitii format. If I want to use the DETR3D algorithm to train the KITTI dataset, what should I modify. I hope you can give me a hint. Thank you very much.

@JoshuaScheuplein
Copy link

JoshuaScheuplein commented Oct 29, 2023

Hi, I would also be interested in how we can train DETR3D with a customized dataset. In the MMDetecion3D documentation, I read that it is possible to convert a customized dataset to the standard format. However, I don't know how to use this standard format in create_data.py

The doc proposes the following:

Once you prepared the raw data following our instruction, you can directly use the following command to generate training/validation information files.

python tools/create_data.py custom --root-path ./data/custom --out-dir ./data/custom --extra-tag custom

However, there is no option for 'custom' in the corresponding file create_data.py, so could you please clarify this approach a little bit? Thanks in advance!

@reynerliu
Copy link

@zhangbaoj have you solved it? my custom dataset is also KITTI format. And I changed the train config&dataset config to make sure the project can correctly run. And I got the bad result <grad_norm=nan,loss=0>. If you solved this problem,can you give me some advice about it?

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