Waymo Open Dataset - Motion¶
The Waymo Open Dataset (WOD) is a collective term for publicly available datasets from Waymo.
Warning
The WOD-Motion dataset is not fully supported yet. You might encounter issues. This documentation is incomplete.
Overview
Paper |
Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset |
Download |
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Code |
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License |
Waymo Dataset License Agreement for Non-Commercial Use Apache License 2.0 + Code Specific Licenses |
Available splits |
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Available Modalities¶
Name |
Available |
Description |
|---|---|---|
Ego Vehicle |
✓ |
State of the ego vehicle, including poses, and vehicle parameters, see |
Map |
(✓) |
The HD-Maps are in 3D, but may have artifacts due to polyline to polygon conversion (see below). For more information, see |
Bounding Boxes |
✓ |
The bounding boxes are available with the |
Traffic Lights |
✓ |
Traffic lights include the status and the lane id they are associated with, see |
Pinhole Cameras |
X |
n/a |
Fisheye Cameras |
X |
n/a |
LiDARs |
X |
n/a |
Dataset Specific
- class py123d.conversion.registry.WODMotionBoxDetectionLabel[source]¶
Semantic labels if bounding box detections in the WOD-Motion dataset, see [1].
References
- TYPE_UNSET = 0¶
- TYPE_VEHICLE = 1¶
- TYPE_PEDESTRIAN = 2¶
- TYPE_CYCLIST = 3¶
- TYPE_OTHER = 4¶
Download¶
To download the Waymo Open Dataset - Motion, please visit the official website.
$WOD_MOTION_DATA_ROOT
├── testing/
| ├── ...
| ├── ...
| └── ...
├── training/
| ├── ...
| ├── ...
| └── ...
└── validation/
├── ...
├── ...
└── ...
You can add the dataset root directory to the environment variable WOD_MOTION_DATA_ROOT for easier access.
export WOD_MOTION_DATA_ROOT=/path/to/wod_motion_data_root
Optionally, you can adjust the py123d/script/config/common/default_dataset_paths.yaml accordingly.
Installation¶
The Waymo Open Dataset requires additional dependencies that are included as optional dependencies in py123d. You can install them via:
pip install py123d[waymo]
pip install -e .[waymo]
These dependencies are notoriously difficult to install due to compatibility issues. We recommend using a dedicated conda environment for this purpose. Using uv can significantly speed up the installation. Here is an example of how to set it up:
conda create -n py123d_waymo python=3.10
conda activate py123d_waymo
uv pip install -e .[waymo]
# If something goes wrong: conda deactivate; conda remove -n py123d_waymo --all
You only need the Waymo Open Dataset specific dependencies if you convert the dataset or read from the raw TFRecord files.
After conversion, you may use any other py123d installation.
Dataset Specific Issues¶
Map: The HD-Map in Waymo has bugs …
Citation¶
If you use this dataset in your research, please cite:
@inproceedings{Ettinger2021ICCV,
title={Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset},
author={Ettinger, Scott and Cheng, Shuyang and Caine, Benjamin and Liu, Chenxi and Zhao, Hang and Pradhan, Sabeek and Chai, Yuning and Sapp, Ben and Qi, Charles R and Zhou, Yin and others},
booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
pages={9710--9719},
year={2021}
}