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. .. dropdown:: Overview :open: .. list-table:: :header-rows: 0 :widths: 20 60 * - - * - :octicon:`file` Paper - `Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset `_ * - :octicon:`download` Download - `waymo.com/open `_ * - :octicon:`mark-github` Code - `waymo-open-dataset `_ * - :octicon:`law` License - `Waymo Dataset License Agreement for Non-Commercial Use `_ Apache License 2.0 + `Code Specific Licenses `_ * - :octicon:`database` Available splits - ``wod-motion_train``, ``wod-motion_val``, ``wod-motion_test`` Available Modalities ~~~~~~~~~~~~~~~~~~~~ .. list-table:: :header-rows: 1 :widths: 20 5 75 * - **Name** - **Available** - **Description** * - Ego Vehicle - ✓ - State of the ego vehicle, including poses, and vehicle parameters, see :class:`~py123d.datatypes.vehicle_state.EgoStateSE3`. * - Map - (✓) - The HD-Maps are in 3D, but may have artifacts due to polyline to polygon conversion (see below). For more information, see :class:`~py123d.api.MapAPI`. * - Bounding Boxes - ✓ - The bounding boxes are available with the :class:`~py123d.conversion.registry.WODMotionBoxDetectionLabel`. For more information, :class:`~py123d.datatypes.detections.BoxDetectionWrapper`. * - Traffic Lights - ✓ - Traffic lights include the status and the lane id they are associated with, see :class:`~py123d.datatypes.detections.TrafficLightDetectionWrapper`. * - Pinhole Cameras - X - n/a * - Fisheye Cameras - X - n/a * - LiDARs - X - n/a .. dropdown:: Dataset Specific .. autoclass:: py123d.conversion.registry.WODMotionBoxDetectionLabel :members: :no-inherited-members: Download ~~~~~~~~ To download the Waymo Open Dataset - Motion, please visit the `official website `_. .. code-block:: text $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. .. code-block:: bash 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: .. tab-set:: .. tab-item:: PyPI .. code-block:: bash pip install py123d[waymo] .. tab-item:: Source .. code-block:: bash 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: .. code-block:: bash 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: .. code-block:: bibtex @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} }