I'm trying to download the tbv dataset and it seems there are two instructions to do so. Do these two methods produce the same result?

One here:

1. https://github.com/argoai/argoverse2-api/blob/main/DOWNLOAD.md s5cmd --no-sign-request cp s3://argoai-argoverse/av2/tbv/* target-directory

And another here: 2. https://github.com/argoai/argoverse2-api/blob/main/src/av2/datasets/tbv/README.md SHARD_DIR={DESIRED PATH FOR TAR.GZ files} s5cmd cp s3://argoai-argoverse/av2/tars/tbv/*.tar.gz ${SHARD_DIR}

When I try 1, I get an error "s5cmd is hitting the max open file limit allowed by your OS. Either increase the open file limit or try to decrease the number of workers with '-numworkers' parameter'.

When I try 2, I get an error "Error session: fetching region failed: NoCredentialProviders: no valid providers in chain. Deprecated."

1. probably downloads half of the dataset, while 2. doesn't initiate the download. I will probably continue with 1, but 2. probably is faster. I'm using Linux Ubuntu 18.04.

The Submission Guidelines have nothing about the submission format, could you give more details? Or could you provide a submission sample? Thank you very much!

Hi folks,

I am trying to run my model in Argoverse 2.0, which was previously trained using 1.1 and its corresponding API. Nevertheless, after installing and cloning the API, in order to check the tutorials, dataloaders etc, this api looks quite smaller than Argoverse 1.1. and the organization also seems to be different (e.g. where are the csvs with the trajectories?). Where could I see all the required documentation?

Thanks for your excellent work! I would like to know how to do the evaluation of 3D object detection on validation split. And I notice there is PR about this. When will the stable version be released? I am looking forward to it!

Hi, thank you for providing the outstanding dataset.

I am particularly interested in the motion dataset, and have a question that is it possible to extract the route of the self-driving vehicles in each scenario?

Hi! I am about to make a submission to the motion forecasting challenge (https://eval.ai/challenge/1719/my-submissions) but got an error "KeyError(1)" from Stderr File. Is there any way to get a detailed error message?

Hi, I get the following error running code ArgoverseStaticMap.from_json(static_map_path) with certain map files: ValueError: 'UNKNOWN' is not a valid LaneMarkType The version of av2 is 0.2.0. When I check the LaneMarkType class while running, I notice that it does not have the member "UNKNOWN", which exists in the github code. Could you please check and fix it in the released version?

Hi guys,

Do you know if some GNN based baseline methods are going to be implemented in the tutorial? Similar than NN and LSTM for Argoverse 1.0 API, in order to know how to deal with the vectorized map.

Hi!

I was going through Argoverse 1 dataset and found this file: https://github.com/argoai/argoverse-api/blob/7c4952d4d080b5b173c25e187c46d3293245a67b/demo_usage/cuboids_to_bboxes.py#L105 that can render 3D bounding boxes on images as per README. Is there a similar function call in the av2 APIs as well? Alternatively, is there a documentation around how to do this?

Thank you!

Hello, Thanks for your great contributions. I found an error when parsing map data. For example for log_map_archive_f75d80d6-a1c8-4a0b-915a-7dc304d122b0.json:

Traceback (most recent call last): File "map_test.py", line 28, in avm = ArgoverseStaticMap.from_json(Path(dataroot)) File "/Users/wangmingkun/opt/anaconda3/envs/argo2/lib/python3.8/site-packages/av2/map/map_api.py", line 328, in from_json vector_lane_segments = {ls["id"]: LaneSegment.from_dict(ls) for ls in vector_data["lane_segments"].values()} File "/Users/wangmingkun/opt/anaconda3/envs/argo2/lib/python3.8/site-packages/av2/map/map_api.py", line 328, in vector_lane_segments = {ls["id"]: LaneSegment.from_dict(ls) for ls in vector_data["lane_segments"].values()} File "/Users/wangmingkun/opt/anaconda3/envs/argo2/lib/python3.8/site-packages/av2/map/lane_segment.py", line 110, in from_dict left_mark_type=LaneMarkType(json_data["left_lane_mark_type"]), File "/Users/wangmingkun/opt/anaconda3/envs/argo2/lib/python3.8/enum.py", line 339, in call return cls.new(cls, value) File "/Users/wangmingkun/opt/anaconda3/envs/argo2/lib/python3.8/enum.py", line 663, in new raise ve_exc ValueError: 'UNKNOWN' is not a valid LaneMarkType

In your map_tutorial.ipynb, I encountered some issues: from av2.datasets.sensor_dataset.av2_sensor_dataloader import AV2SensorDataLoader should be from av2.datasets.sensor.av2_sensor_dataloader import AV2SensorDataLoader

Each instance of ArgoverseStaticMap.from_json() should be ArgoverseStaticMap.from_map_dir()

And then args should be like

from pathlib import Path args = SimpleNamespace(**{"dataroot": Path(dataroot), "log_id": Path(log_id)})

PR Summary

Testing

In order to ensure this PR works as intended, it is:

• [ ] unit tested.
• [ ] other or not applicable (additional detail/rationale required)

Compliance with Standards

As the author, I certify that this PR conforms to the following standards:

• [ ] Code changes conform to PEP8 and docstrings conform to the Google Python style guide.
• [ ] A well-written summary explains what was done and why it was done.
• [ ] The PR is adequately tested and the testing details and links to external results are included.

Hi, I'm trying to download av2 motion-forecasting datasets. Following instructions given by Download, I install s5cmd and try commands below, and this is what I got:

>> s5cmd --no-sign-request cp s3://argoai-argoverse/av2/motion-forecasting/* /data/Argoverse2Datasets/sensor/
zsh: no matches found: s3://argoai-argoverse/av2/motion-forecasting/*
>> s5cmd --no-sign-request cp s3://argoai-argoverse/av2/* /data/zhouxinning/Argoverse2Datasets/
zsh: no matches found: s3://argoai-argoverse/av2/*

I just wondering that have you changed the path to the dataset?

Dear all:

When I run the 'generate_sensor_dataset_visualizations.py' file, it alway report the error that: No such file or directory. I check the difference and found that the error path is '/.../argv2/SensorDataset/sensor/SensorDataset_val/5589de60-1727-3e3f-9423-33437fc5da4b/sensors/lidar/315967919259399000.feather' and the true path is '/.../argv2/SensorDataset/sensor/val/5589de60-1727-3e3f-9423-33437fc5da4b/sensors/lidar/315967919259399000.feather'. Is any parameter in the program that needs to be debugged or something else? Hoping for your reply and thanks so much.

PR Summary

Testing

In order to ensure this PR works as intended, it is:

• [ ] unit tested.
• [ ] other or not applicable (additional detail/rationale required)

Compliance with Standards

As the author, I certify that this PR conforms to the following standards:

• [ ] Code changes conform to PEP8 and docstrings conform to the Google Python style guide.
• [ ] A well-written summary explains what was done and why it was done.
• [ ] The PR is adequately tested and the testing details and links to external results are included.

Hey everyone,

I had a look into the motion forecasting dataset and there seems to be an issue with the trajectories of the focal agent. According to the paper, the focal agent should always be observed over the full 11 seconds, which then corresponds to 110 observations: "Within each scenario, we mark a single track as the “focal agent". Focal tracks are guaranteed to be fully observed throughout the duration of the scenario and have been specifically selected to maximize interesting interactions with map features and other nearby actors (see Section 3.3.2)"

However, this is not the case for some scenarios (~3% of the scenarios). One example: Scenario '0215552f-6951-47e5-8cf6-3d1351d28957' of the validation set has a trajectory with only 104 observations.

Can you reproduce my problem? Is this intended or can we expect this to be fixed in the near future?

Looking forward hearing from you!

Best regards

SchDevel