kylevedder / zeroflow Goto Github PK

Hi, Kyleverdder,

Nice work! thank you for releasing the code.
Can you please provide a simple demo that takes as input two point clouds and outputs the flow?

Thank you.

Is there a way to set up the environment and run the demo on argoverse without a Docker setup? For example, could I have a list of the environment dependencies and build instructions so that I can run it normally?

Hello,
I downloaded WOD version 1.4.2 linked here but map features seem to be missing from this data. I specifically downloaded files from the path waymo_open_dataset_v_1_4_2/individual_files/* . When running rasterize_heightmap.py, I get AttributeError: map_features. Please let me know if I am using the wrong data.

in the getting start ,I need the link https://github.com/nchodosh/argoverse2-sf to compute ground truth flows ,but it's 404.how can i generate the flows?

Thanks for your work and open source,

When I read the code following, I'm wondering why set a assert here for z index must be 0? since Voxelization is 3D, z should not be 0?

Thank you for your work.

Following the README and GETTING_STARTED document, I created the train and val supervision labels, and my dataset folder structure follows this:

|-argoverse2
    |-train
    |-train_sceneflow
    |-test
    |-val
    |-val_sceneflow

I mounted the folder to the container correctly as shown below:

root@Max-laptop-debian:/efs# ls
argoverse2
root@Max-laptop-debian:/efs# cd argoverse2/
root@Max-laptop-debian:/efs/argoverse2# ls
test  train  train_sceneflow  val  val_sceneflow

However, when I try to train the model using

python train_pl.py ./configs/fastflow3d/argo/nsfp_distilatation_speed_scaled_updated.py

I always got the num_samples=0 error below

Traceback (most recent call last):
  File "/project/train_pl.py", line 189, in <module>
    main()
  File "/project/train_pl.py", line 146, in main
    train_dataloader = make_train_dataloader(cfg)
  File "/project/train_pl.py", line 68, in make_train_dataloader
    return torch.utils.data.DataLoader(train_dataset,
  File "/miniconda/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 353, in __init__
    sampler = RandomSampler(dataset, generator=generator)  # type: ignore[arg-type]
  File "/miniconda/lib/python3.10/site-packages/torch/utils/data/sampler.py", line 107, in __init__
    raise ValueError("num_samples should be a positive integer "
ValueError: num_samples should be a positive integer value, but got num_samples=0

The paths inside nsfp_distilatation_speed_scaled_updated.py are:

train_sequence_dir = "/efs/argoverse2/train/"
train_flow_dir = "/efs/argoverse2/train_sceneflow/"

test_sequence_dir = "/efs/argoverse2/val/"
test_flow_dir = "/efs/argoverse2/val_sceneflow/"

I believe the problem is that the train path in the config file is incorrect. However, I am unable to find additional information in the document to solve my question. Would you mind pointing out what's wrong with it?