# ethz-asl/kalibr

The Kalibr visual-inertial calibration toolbox

Repository: https://github.com/ethz-asl/kalibr
Canonical: https://ross.abutalabs.com/products/kalibr
Language: C++
License: NOASSERTION
License Family: other
Topics: camera, calibration, calibration-toolbox, imu
Last push: 2024-03-30T19:42:29+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": 4479, "days_push": 886, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5680, forks 1599 (observed 2026-08-28T04:09:27.816796+00:00)

## What it is
Kalibr is a visual-inertial calibration toolbox for camera systems and inertial measurement units. It supports multi-camera, camera-IMU, IMU-IMU, and rolling shutter calibration with a wide range of camera models.

## Use cases
- calibrate intrinsics and extrinsics of a multi-camera rig
- spatial and temporal calibration of a camera-IMU system
- calibrate rolling shutter camera parameters
- calibrate multiple IMUs relative to a base IMU
- estimate camera distortion and projection models from calibration targets

## When to choose
- you need accurate camera or IMU calibration for robotics or SLAM research
- you work in a ROS environment and need a proven calibration toolbox
- you need to calibrate non-overlapping multi-camera systems or rolling shutter cameras

## When to avoid
- you need a simple single-camera calibration only (OpenCV may suffice)
- you need a GUI-driven calibration workflow
- you are not working with ROS or Docker-based tooling

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: computer-vision, image-processing, simulation, developer-tools
- domain: robotics, computer-vision, autonomous-vehicles
- platform: cpp, python
- tags: camera-calibration, imu-calibration, visual-inertial, ros, rolling-shutter, sensor-fusion, linux, docker

## Member repositories
- ethz-asl/kalibr (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:27.816796+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 2026-08-29T17:54:15.519115+00:00, confidence not recorded.
  - readme: https://github.com/ethz-asl/kalibr (fetched 2026-08-28T04:09:27.816796+00:00, sha 7e6ec8e99ca9)
- Data as of 2026-08-30T08:39:29.467469+00:00.