fast-computer-vision
A computer vision application to track ArUco markers.
https://github.com/fast-digital-exhibit-design/fast-computer-vision
Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
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✓codemeta.json file
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○Scientific vocabulary similarity
Low similarity (13.7%) to scientific vocabulary
Repository
A computer vision application to track ArUco markers.
Basic Info
- Host: GitHub
- Owner: FAST-Digital-Exhibit-Design
- License: gpl-3.0
- Language: C++
- Default Branch: main
- Size: 105 KB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 1
Metadata Files
README.md
FAST Computer Vision
A computer vision application to track ArUco markers.
What is FAST?
Flexible, Accessible Strategies for Timely Digital Exhibit Design
Museums play a critical role in engaging their communities around urgent issues that emerge in the public sphere. However, typical exhibit development timelines can stretch for years, and "what's new" can change swiftly before an exhibition is even launched. What if museums could stay agile and dynamic, changing out content as community needs shift, science progresses, and the world changes? What if timely exhibit offerings could be not just efficiently produced, but accessible and welcoming to all visitors? This vision of efficiency and accessibility is at the center of FAST.
For more information about FAST, please see:
- FAST Booklet, an introduction and explanation of the FAST project
- FAST Toolkit, a portal for all assets and documentation published from the FAST project
System Requirements
Runtime Requirements
- Microsoft Windows 10 or 11
- Microsoft Visual C++ 2015-2022 Redistributable (x64)
- Teledyne FLIR machine vision camera
Additional hardware is required to operate some FAST user experiences. See FAST production documentation for more details.
Build Requirements
- Qt 6.5.0
- OpenCV 4.6.0
- FLIR Spinnaker C++ SDK 2.5.0
- Microsoft Visual C++ Compiler 16.11 (MSVC2019 64-bit)
Installation
- Download the most recent version of the application from Releases
- Extract the ZIP file where you want the application installed
- Open fast-computer-vision.exe to run the application
Documentation
See the User Manual
Contributions
This repo is only maintained with bug fixes and Pull Requests are not accepted at this time. If you'd like to contribute, please post questions and comments about using FAST Computer Vision to Discussions and report bugs using Issues.
Citation
If you reference this software in a publication, please cite it as follows:
APA
Museum of Science, Boston. FAST Computer Vision [Computer software]. https://github.com/FAST-Digital-Exhibit-Design/FAST-Computer-Vision
BibTeX
@software{Museum_of_Science_FAST_Computer_Vision,
author = {{Museum of Science, Boston}},
license = {GPL-3.0-only},
title = {{FAST Computer Vision}},
url = {https://github.com/FAST-Digital-Exhibit-Design/FAST-Computer-Vision}
}
Notices
Copyright (C) 2024 Museum of Science, Boston https://www.mos.org/
This program was developed through a grant to the Museum of Science, Boston from the Institute of Museum and Library Services under Award
MG-249646-OMS-21. For more information about this grant, see
https://www.imls.gov/grants/awarded/mg-249646-oms-21.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
A copy of the GNU General Public License is provided in the LICENSES folder. For more information about this license, see https://www.gnu.org/licenses/gpl-3.0.html.
SPDX-License-Identifier: GPL-3.0-only
A portion of the User Manual documentation redistributes parameter descriptions from the OpenCV ArUco module documentation licensed under the Apache License, Version 2.0. A copy of the Apache License, Version 2.0 is provided in the LICENSES folder. For more information about this license, see http://www.apache.org/licenses/LICENSE-2.0.
SPDX-License-Identifier: Apache-2.0
Third party copyrights and trademarks are property of their respective owners.
The Qt Framework
This program was developed using The Qt Framework with the Qt Community Open Source License under the terms of the GNU General Public License as published by the Free Software Foundation. A copy of the Qt source code is available at https://github.com/FAST-Digital-Exhibit-Design/FAST-Qt and a copy of the GNU General Public License is provided in the LICENSES folder. For more information about this license, see https://www.gnu.org/licenses/gpl-3.0.html.
The Qt Company Ltd and its subsidiaries is the owner of Qt trademarks worldwide. The Qt Framework is Copyright (C) 2008-2024 The Qt Company Ltd.
OpenCV
This program was developed using OpenCV (Open Source Computer Vision Library) under the terms of the Apache License, Version 2.0 as published by the The Apache Software Foundation. A copy of the Apache License, Version 2.0 is provided in the LICENSES folder. For more information about this license, see http://www.apache.org/licenses/LICENSE-2.0.
OpenCV is the owner of OpenCV trademarks in the United States. OpenCV is Copyright (C) 2024 OpenCV team.
FLIR Spinnaker SDK
This program was developed using the FLIR Spinnaker SDK under the terms of the FLIR Spinnaker SDK License Agreement.
Teledyne FLIR LLC is the owner of FLIR Spinnaker SDK trademarks in the United States. FLIR Spinnaker SDK is Copyright (C) 2001-2024 Teledyne FLIR LLC.
Owner
- Name: FAST Digital Exhibit Design, Museum of Science
- Login: FAST-Digital-Exhibit-Design
- Kind: organization
- Repositories: 1
- Profile: https://github.com/FAST-Digital-Exhibit-Design
Citation (CITATION.cff)
cff-version: 1.2.0
title: FAST Computer Vision
message: >-
If you reference this software in a publication, please
cite it as below.
type: software
authors:
- name: Museum of Science, Boston
website: 'https://www.mos.org'
repository-code: >-
https://github.com/FAST-Digital-Exhibit-Design/FAST-Computer-Vision
abstract: >-
A computer vision application to track ArUco markers.
license: GPL-3.0-only