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 to prepare the DAIR-V2X data for training? #2

Open
linleyzoe opened this issue Oct 18, 2022 · 8 comments
Open

How to prepare the DAIR-V2X data for training? #2

linleyzoe opened this issue Oct 18, 2022 · 8 comments

Comments

@linleyzoe
Copy link

Hi, thanks for your inspiring work!

There seems no instructions for converting the raw DAIR-V2X to the specific training format, which is referred as root_dir: "/GPFS/rhome/quanhaoli/workspace/dataset/my_dair_v2x/v2x_c/cooperative-vehicle-infrastructure/train.json" in the config file.

Any advice would be greatly appreciated!

@goodgamemaker
Copy link

Do you know how to do with it? I also have some questions!

@suuhou
Copy link

suuhou commented Nov 7, 2022

hello, you can find split_data.json files(train.json, val.json) in this zip file https://github.com/yifanlu0227/CoAlign.

Actually, you can also find it on the official github page of dair-v2x.
https://github.com/AIR-THU/DAIR-V2X/blob/main/data/split_datas/cooperative-split-data.json
In this case, you can use the following code to see how they split the dataset into training and validation sets:

info_json_path = r"E:\python_work_d\project_samples\DAIR-V2X-main\data\split_datas"
info_name = "cooperative-split-data.json"
with open(os.path.join(info_json_path, info_name), 'rb') as f:
    split_data = json.load(f)
split_info = split_data["cooperative_split"]["train"]
for i in range(10):
    print(split_info[i])

Then, to prepare the dataset for model training, following these steps:

  1. Download the dair-v2x(cooperative-vehicle-infrastructure )dataset and the new annotation data as mentioned in the github homepage of where2comm
  2. Organize your dataset file into the following structure: https://github.com/AIR-THU/DAIR-V2X/tree/main/data
  3. Replace the lidar annotation data of the collaborative and the vehicle side with the new annotation data downloaded in step 1. (you will also find the train.json file and the val.json file in this zip )
  4. Change data path in the yaml file to your own path (data_dir, root_dir...)

@CatOneTwo
Copy link

Can you run this program normally?

@suuhou
Copy link

suuhou commented Nov 15, 2022

yes,can't u?

@CatOneTwo
Copy link

yes, I can run the code now. But how to set communication volume like papers?

@goodgamemaker
Copy link

yes, I can run the code now. But how to set communication volume like papers?
Have you solved this problem? Do you use image in the code or only use point cloud?Thank you!

@goodgamemaker
Copy link

And how does his communication round K reflect

@W-E-A
Copy link

W-E-A commented Nov 23, 2023

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

5 participants