qubvidcalib

Video Calibration App.Made with love from HRI Team Queens University Belfast

https://github.com/exponentialr/qubvidcalib

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 4 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
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  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (14.1%) to scientific vocabulary
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Repository

Video Calibration App.Made with love from HRI Team Queens University Belfast

Basic Info
  • Host: GitHub
  • Owner: exponentialR
  • License: other
  • Language: Python
  • Default Branch: master
  • Size: 391 KB
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  • Forks: 1
  • Open Issues: 0
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Created over 2 years ago · Last pushed 11 months ago
Metadata Files
Readme License Citation

README.md

DOI

CalibraVision - Camera Calibration Toolbox

CameraCalibration-tool.png

Read about Calibration here

Introduction   |   Features   |   Experimental Features   |   Prerequisites   |   Installation   |   Usage   |   Loading Configuration   |   Starting Calibration or Correction   |   Screenshots   |   Video Guide   |   Development Status   |   Contributing   |   License   |   Acknowledgements

Introduction

The CalibraVision offers a sophisticated yet user-friendly toolkit for camera calibration and video correction, integrating advanced pattern recognition and calibration techniques to enhance the accuracy and efficiency of the calibration process.

Features

Dynamic Pattern Generation: Support for Charuco and Checker patterns, customizable according to user needs.

Enhanced Calibration Options: Including 'Calibrate Only', 'Self-Calibrate & Correct', 'Correct Only', and 'Single Calib and Multiple Video Correction'.

Real-time display of corrected and uncorrected video streams

Ability to save calibration parameters for future use

Easy-to-use graphical interface with intuitive controls

Option to load custom calibration files

Extensive logging to monitor calibration and correction processes

Prerequisites

To be installed using requirements.txt - Python 3.x - Tkinter - OpenCV - NumPy - configparser

Installation

  1. Clone the repository: ```bash git clone https://github.com/exponentialR/QUBVidCalib.git
  2. Navigate to the project directory: ````bash cd QUBVidCalib

  3. Create a Python environment and install dependencies:

  • On Linux:

    ````bash python3 -m venv calibra source calibra/bin/activate pip install -r requirements.txt

  • On Windows: ````bash python -m venv calibra .\calibra\Scripts\activate pip install -r requirements.txt

  • On Mac: ````bash python3 -m venv calibra source calibra/bin/activate pip install -r requirements.txt

  1. Starting the app ```bash cd src python3 main.py

Usage

Loading Configuration

Loading Configuration On application start, the GUI loads existing configurations from settings.ini if available. Users have the option to manually set the following parameters:

  • Calibration Type: Chaurco or Checkerboard
  • Project Repository: Set the directory for saving project files.
  • Project Name: Assign a unique name for the calibration session.
  • Video Files: Specify the target videos for calibration or correction.
  • Calibration Board Dimensions: Input the dimensions of the used calibration board.
  • Frame Interval: Determine the frame capture rate for calibration.
  • Number of Frames to Save: Set how many frames are saved during calibration.
  • Dictionary Type: if using charuco, Choose the marker dictionary type for pattern detection.

Starting Calibration or Correction

The main window offers three options:

  1. Calibrate Only: Perform only the calibration step.
  2. Correct Only: Perform only the correction step.
  3. Calibrate and Correct: Perform both calibration and correction. Once started, the application provides real-time logging and status updates. The corrected video and calibration parameters can be saved for future use.

Calibration Pattern Generation

An additional feature, "Generate Calibration Pattern," is now available for creating custom calibration patterns. Users can define the pattern type, dimensions, and other parameters for printing, and recommended paper size will be atop the pattern.

Experimental Features

  • Play/Pause controls for video review (In Development)
  • Slider for video navigation (In Development)

Development Status

  • Chessboard Pattern: Integration for Chessboard calibration patterns is now complete and available.
  • Pattern Generation: Users can generate custom calibration patterns directly within the application.

Contributing

Feel free to fork this repository and submit a pull request if you have some features or fixes to contribute. For more information, please read the CONTRIBUTING.md guide.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

TODO

Enhancements to the embedded Video Player for a richer user experience.

Citation

If you find this project useful, please consider citing it using the following BibTeX entry: ```bibtex

@misc{adebayoexponentialrqubvidcalib2024, title = {{exponentialR}/{QUBVidCalib}: {V1}.0}, shorttitle = {{exponentialR}/{QUBVidCalib}}, url = {https://zenodo.org/records/13956034}, abstract = {publication release}, urldate = {2024-10-19}, publisher = {Zenodo}, author = {Adebayo, Samuel}, month = oct, year = {2024}, doi = {10.5281/zenodo.13956034}, }

Owner

  • Name: Samuel Adebayo
  • Login: exponentialR
  • Kind: user
  • Location: Belfast

PhD Student @QUBelfast Most of my repositories are private

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use QUBVidCalib in your research or development pipeline, please cite it as below:"
title: "QUBVidCalib: Video Calibration and Correction Toolbox"
authors:
  - family-names: Adebayo
    given-names: Samuel
    orcid: https://orcid.org/0000-0002-8592-1196
date-released: 2024-10-19
version: "1.0.0"
doi: 10.5281/zenodo.13956034
repository-code: https://github.com/exponentialR/QUBVidCalib
license: MIT

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