py123d 0.2.0

123D: A Unified Library for Multi-Modal Autonomous Driving Data.

123D: A Unified Library for Multi-Modal Autonomous Driving Data

Video | Documentation

One library for autonomous driving datasets. 123D converts raw data from Argoverse 2, nuScenes, nuPlan, KITTI-360, PandaSet, and Waymo into a fast, unified Apache Arrow format, and then gives you a single API to read cameras, lidar, HD maps, and labels across all of them.

Features

• Unified API: Read cameras, lidar, maps, and labels through a single interface, regardless of the source dataset.
• Apache Arrow storage: columnar, memory-mapped, zero-copy reads. Fast and memory efficient.
• Multiple sensor codecs: MP4/JPEG/PNG for cameras; LAZ/Draco/Arrow IPC for lidar.
• Built-in visualization: interactive 3D viewer (Viser), and matplotlib plotting.
• No sensor data duplication: By default, converted logs reference original camera and lidar files via relative paths. No need to store sensor data twice.
• Hydra-based conversion CLI: YAML configs to manage your data pipelines.

Viewer

Supported Datasets

Dataset	Cameras	LiDARs	Map	3D Boxes	Traffic Lights
Argoverse 2 - Sensor	9	2	✓	✓	✗
nuScenes	6	1	✓	✓	✗
nuPlan	8	5	✓	✓	✓
KITTI-360	4	1	✓	✓	✗
PandaSet	6	2	✗	✓	✗
Waymo Open - Perception	5	5	✓	✓	✗
Waymo Open - Motion	✗	✗	✓	✓	✓
CARLA / LEAD	config.	config.	✓	✓	✓
NVIDIA Physical AI AV (experimental)	7	1	✗	✓	✗

Changelog

v0.2.0 (2026-04-14)

• Transferred repository to KE:SAI.

• Aligned ego and agent dynamics to a unified global/ego-frame convention, with velocity/acceleration inference in LogWriter from poses for EgoState and BoxDetectionsSE3 (#119, #120).

• Improved OpenDRIVE maps: 3D road-edge lifting, lane-boundary reconstruction, and cleaner map-metadata location handling (#121).

• Parser and visualization fixes: NuScenes interpolated parser defaults to 10 Hz sync with camera-pose interpolation; PandaSet extrinsic/undistortion fixes; viser fixes (#117); new matplotlib camera-rig and lidar-reprojection utilities.

No breaking changes to the public API, Arrow schema, or CLI entry points.

v0.1.0 (2026-03-22)

• Asynchronous (native-rate) data storage: modalities are now written at their original capture rate, not just at the a frame-wise rate.
• New parser architecture with BaseLogParser.iter_modalities_async for native-rate iteration alongside the existing synchronized path.
• Added NVIDIA Physical AI AV dataset support (experimental).
• Added standalone OpenDRIVE / CARLA map parser.
• Refactored conversion/ module into parser/ with consistent naming across all dataset parsers.
• Refactored Viser 3D viewer. Adds more control and dark mode.
• Added LaneType, IntersectionType, StopZoneType to map data structure.
• Replaced Waymo heavy dependencies with lightweight protobufs.
• Various fixes to camera-to-global transforms across all datasets.

v0.0.9 (2026-02-09)

• Added Waymo Open Motion Dataset support.
• Replaced gpkg map implementation with Arrow-based format for improved performance.
• Added sensor names and timestamps to camera and Lidar data across all datasets.
• Added ego-to-camera transforms in static metadata.
• Implemented geometry builders for PoseSE2/PoseSE3 from arbitrary rotation/translation representations.
• Added support for loading merged point clouds in API.
• Improved map querying speed and OpenDrive lane connectivity handling.
• Added recommended conversion options to dataset YAML configuration files.
• Fixed PandaSet static extrinsics and KITTI-360 timestamp handling.
• Fixed memory issues when converting large datasets (e.g., nuPlan).

v0.0.8 (2025-11-21)

• Release of package and documentation.
• Demo data for tutorials.

Citation

@software{Contributors123D,
  title   = {123D: A Unified Library for Multi-Modal Autonomous Driving Data},
  author  = {123D Contributors},
  year    = {2026},
  url     = {https://github.com/kesai-labs/py123d},
  license = {Apache-2.0}
}

License

123D is released under the Apache License 2.0.