nuscenes-devkit
The official devkit of the nuScenes dataset (www.nuscenes.org).
Decision gist · record as of 2026-08-14
Yes, if you are working with the nuScenes dataset or benchmarking autonomous driving perception systems. The package is actively maintained, has low install friction, and is the official toolkit for the dataset. However, verify that the non-commercial license restriction aligns with your use case before committing to production work.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires the nuScenes dataset to be downloaded and extracted to a local directory (e.g., /data/sets/nuscenes); the devkit alone is not functional without dataset files.
- Low friction installation with a pure-Python wheel.
- The package is actively maintained with a recent release (Aug 2025) and supports current Python versions (3.9, 3.12).
License · maintenance · safety
apache-2.0 (noncommercial) — Licensed under Apache 2.0 but marked as non-commercial use only. Commercial use of this devkit requires separate licensing; verify terms before deploying in production systems.
last release 2025-08-28 (351 days) · last repo commit 2026-08-06 · 2,789 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 174,059 downloads/mo, #10,292 on PyPI
Alternatives
Verify before relying
pip install nuscenes-devkit
from nuscenes.nuscenes import NuScenes
ns = NuScenes(version='v1.0-mini', dataroot='/data/sets/nuscenes')
ns.render_sample(ns.sample[0]['token'])- Whether the non-commercial license restriction applies only to the devkit code or also to derivative works built with it
- Dataset download and storage requirements beyond the devkit itself
- Performance characteristics when working with full-scale nuScenes data
What it is and what it does
The nuScenes devkit is the official toolkit for working with the nuScenes autonomous driving dataset. It provides Python APIs to load, visualize, and evaluate predictions against multi-sensor data (lidar, radar, camera) collected from autonomous vehicles. The package handles 3D object detection, multi-object tracking, trajectory prediction, and semantic/panoptic segmentation of point clouds.
The devkit depends on standard scientific Python libraries (numpy, scipy, scikit-learn, matplotlib, opencv-python-headless) plus specialized tools like pyquaternion for 3D rotations, Shapely for geometry, and pycocotools for evaluation metrics. It's designed to work with downloaded nuScenes dataset splits (train, val, test, mini) organized in a specific folder structure, and provides tutorials and evaluation code for benchmark challenges.
Use it for
- Evaluate 3D object detection models on the nuScenes benchmark dataset
- Develop and test autonomous driving perception algorithms using standardized multi-sensor data
- Analyze lidar point cloud semantic segmentation with panoptic labels
- Implement trajectory prediction models using the nuScenes prediction challenge framework
- Visualize and debug sensor fusion pipelines with synchronized camera, lidar, and radar data
- Benchmark tracking algorithms against ground-truth annotations across 40,000+ keyframes
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are working with the nuScenes dataset or benchmarking autonomous driving perception systems.
The package is actively maintained, has low install friction, and is the official toolkit for the dataset. However, verify that the non-commercial license restriction aligns with your use case before committing to production work.
Install
nuscenes-devkit on PyPI
Before you install
Low friction installation with a pure-Python wheel. The package is actively maintained with a recent release (Aug 2025) and supports current Python versions (3.9, 3.12). Repository shows steady activity with 2789 stars.
Requires the nuScenes dataset to be downloaded and extracted to a local directory (e.g., /data/sets/nuscenes); the devkit alone is not functional without dataset files.
License in practice
Licensed under Apache 2.0 but marked as non-commercial use only. Commercial use of this devkit requires separate licensing; verify terms before deploying in production systems.
Quickstart
pip install nuscenes-devkit
from nuscenes.nuscenes import NuScenes
ns = NuScenes(version='v1.0-mini', dataroot='/data/sets/nuscenes')
ns.render_sample(ns.sample[0]['token'])Verify before relying
- Whether the non-commercial license restriction applies only to the devkit code or also to derivative works built with it
- Dataset download and storage requirements beyond the devkit itself
- Performance characteristics when working with full-scale nuScenes data
Package facts
| License | apache-2.0 noncommercial |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 14 packagescachetoolsdescartesfirematplotlibnumpyopencv-python-headlessPillowpyquaternionscikit-learnscipyShapelytqdmparameterizedpycocotools |
| Maintenance | Actively maintained 351 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 174,059 / month, #10,292 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: Free for non-commercial useOperating System :: OS IndependentProgramming Language :: Python :: 3.12Programming Language :: Python :: 3.9 |
Evidence: nuscenes_devkit-1.2.0-py3-none-any.whl
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