qubvidcalib
Video Calibration App.Made with love from HRI Team Queens University Belfast
Science Score: 67.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.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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○Scientific vocabulary similarity
Low similarity (14.1%) to scientific vocabulary
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
Statistics
- Stars: 2
- Watchers: 2
- Forks: 1
- Open Issues: 0
- Releases: 1
Metadata Files
README.md
CalibraVision - Camera Calibration Toolbox

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
- Clone the repository: ```bash git clone https://github.com/exponentialR/QUBVidCalib.git
Navigate to the project directory: ````bash cd QUBVidCalib
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
- 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:
- Calibrate Only: Perform only the calibration step.
- Correct Only: Perform only the correction step.
- 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
- Twitter: 0ffxo
- Repositories: 3
- Profile: https://github.com/exponentialR
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
GitHub Events
Total
- Release event: 1
- Watch event: 2
- Delete event: 1
- Push event: 3
- Pull request event: 1
- Fork event: 1
- Create event: 1
Last Year
- Release event: 1
- Watch event: 2
- Delete event: 1
- Push event: 3
- Pull request event: 1
- Fork event: 1
- Create event: 1