explaingit

musabali314/calibon

Analysis updated 2026-05-18

3TypeScriptAudience · developerComplexity · 3/5Setup · moderate

TLDR

A browser based, step by step tool that calibrates a camera from checkerboard photos for robotics and computer vision use.

Mindmap

mindmap
  root((CalibON))
    What it does
      Detects checkerboard corners
      Runs camera calibration
      Shows reprojection error
    Tech stack
      React
      TypeScript
      FastAPI
      OpenCV
    Use cases
      Robot camera setup
      Vision pipeline calibration
      Export to ROS
    Audience
      Robotics developers
      Vision engineers
    Limitations
      Checkerboard only
      No project persistence yet

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Upload checkerboard photos and calibrate a robot or vision camera without writing OpenCV code by hand.

USE CASE 2

Check reprojection error and per-frame quality before trusting a camera's calibration.

USE CASE 3

Export a calibrated camera model to ROS camera_info or Kalibr format for use in other software.

USE CASE 4

Run the whole calibration workflow locally instead of using the hosted version.

What is it built with?

TypeScriptReactViteThree.jsPythonFastAPIOpenCVNumPy

How does it compare?

musabali314/calibon000madz000/payload-test-api-route-handleraliansari22/pdfclear
Stars333
LanguageTypeScriptTypeScriptTypeScript
Setup difficultymoderateeasyeasy
Complexity3/52/52/5
Audiencedeveloperdevelopergeneral

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Local development needs both Node.js/npm and a Python 3.11+ virtual environment running side by side.

In plain English

CalibON is a browser based tool for calibrating cameras, aimed at people working on robotics and computer vision projects. Camera calibration is the process of figuring out exactly how a camera distorts an image, so that measurements and 3D positions calculated from its photos can be corrected and trusted. CalibON walks a user through that process step by step instead of requiring them to write calibration code by hand. The workflow has five stages. First you set up the project by choosing a camera model, image resolution, and the size and layout of the checkerboard pattern used for calibration. Next you upload a set of photos of that checkerboard taken from different angles and distances. CalibON then detects the checkerboard corners in each photo using OpenCV, refines their positions, and shows quality metrics so you can accept or reject individual images. After that, it estimates the camera's internal properties and distortion using the accepted images. Finally, it shows the results, including how much error remains, per photo diagnostics, a preview of the corrected image, and files you can download. Under the hood, the frontend is built with React, TypeScript, and Vite, with Three.js used for the interactive visuals on the landing page. The backend is a Python FastAPI service that uses OpenCV and NumPy to do the actual calibration math. There is a hosted version at calibon.vercel.app that sends uploaded images to a backend for temporary processing, and the project also supports running both the frontend and backend on your own computer for local development, which requires Node.js, npm, and Python 3.11 or newer. Calibration results can be exported in several formats, including a general OpenCV JSON format, a ROS camera_info YAML file, and a Kalibr compatible file, so the calibrated camera model can be used in other robotics or vision software. Right now CalibON only supports the standard checkerboard pattern and a basic pinhole camera model. Support for other calibration patterns, fisheye lenses, webcam capture, and saving projects between browser sessions are all listed as planned future work. The project does not yet include a license file.

Copy-paste prompts

Prompt 1
Help me set up CalibON locally with a Python backend and React frontend.
Prompt 2
Explain what checkerboard inner corners mean and how to configure them in CalibON.
Prompt 3
Show me how to interpret CalibON's reprojection error and per-frame diagnostics.
Prompt 4
Walk me through exporting a CalibON calibration result to ROS camera_info format.

Frequently asked questions

What is calibon?

A browser based, step by step tool that calibrates a camera from checkerboard photos for robotics and computer vision use.

What language is calibon written in?

Mainly TypeScript. The stack also includes TypeScript, React, Vite.

How hard is calibon to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is calibon for?

Mainly developer.

Open on GitHub → Explain another repo

This repo across BitVibe Labs

Verify against the repo before relying on details.