# utiasSTARS/pykitti

Python tools for working with KITTI data.

Repository: https://github.com/utiasSTARS/pykitti
Canonical: https://ross.abutalabs.com/products/pykitti
Language: Python
License: MIT
License Family: permissive
Topics: kitti-dataset, computer-vision, robotics, python
Last push: 2023-10-16T05:06:19+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3795, "days_push": 1052, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1244, forks 240 (observed 2026-08-28T04:04:06.944616+00:00)

## What it is
pykitti is a minimal Python library for loading and working with the KITTI autonomous driving dataset, supporting raw and odometry benchmark data. It provides access to camera images, velodyne point clouds, IMU/OXTS poses, timestamps, and calibration data as convenient Python objects.

## Use cases
- load KITTI dataset in python
- read KITTI calibration files
- visual odometry with KITTI data
- load velodyne point clouds python
- access KITTI stereo image pairs
- prepare KITTI data for deep learning
- parse KITTI OXTS GPS/IMU poses

## When to choose
- you work with KITTI raw or odometry benchmark datasets in Python
- you need convenient access to calibration, images, point clouds, and poses
- you want generator-based sequential access for odometry or random access for training

## When to avoid
- you need other KITTI benchmarks like tracking, segmentation, or flow
- you work with a different autonomous driving dataset
- you need heavy preprocessing or visualization built in

## Facets
- artifact type: library
- maturity: maintenance
- function: computer-vision, data-science, parser
- domain: robotics, computer-vision, autonomous-vehicles, machine-learning
- platform: python, cross-platform
- tags: kitti-dataset, dataset-loading, calibration, point-clouds, stereo-vision, odometry, velodyne

## Member repositories
- utiasSTARS/pykitti (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:06.944616+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T05:08:17.195187+00:00, confidence not recorded.
  - readme: https://github.com/utiasSTARS/pykitti (fetched 2026-08-28T04:04:06.944616+00:00, sha 868b50bd4c2a)
  - registry_pypi: https://pypi.org/pypi/pykitti/json (fetched 2026-08-29T12:20:00.913798+00:00, sha 3afdcad03c15)
- Data as of 2026-08-30T08:39:29.467469+00:00.