List of manual image annotation tools
Manual image annotation is the process of manually defining regions in an image and creating a textual description of those regions. Such annotations can for instance be used to train machine learning algorithms for computer vision applications.
This is a list of computer software which can be used for manual annotation of images.
Software | Description | Platform | License | References |
---|---|---|---|---|
Computer Vision Annotation Tool (CVAT) | Computer Vision Annotation Tool (CVAT) is a free, open source, web-based annotation tool which helps to label video and images for computer vision algorithms. CVAT has many powerful features: interpolation of bounding boxes between key frames, automatic annotation using TensorFlow OD API and deep learning models in Intel OpenVINO IR format, shortcuts for most of critical actions, dashboard with a list of annotation tasks, LDAP and basic authorizations, etc. It was created for and used by a professional data annotation team. UX and UI were optimized especially for computer vision annotation tasks. | JavaScript, HTML, CSS, Python, Django | MIT License | [1][2][3] |
LabelMe | Online annotation tool to build image databases for computer vision research. | Perl, JavaScript, HTML, CSS[4] | MIT License | |
Encord | Encord is an automated annotation platform for AI-assisted image annotation, video annotation, and dataset management.
| Python, JavaScript, HTML, CSS[5] | Apache-2.0 License | |
TagLab | Desktop open source interactive software system for facilitating the precise annotation of benthic species in orthophoto of the bottom of the sea. | Python [6] | GPL | [7] [8] |
VoTT (Visual Object Tagging Tool) | Free and open source electron app for image annotation and labeling developed by Microsoft. | TypeScript/Electron (Windows, Linux, macOS) | MIT License | [9][10][11][12][13] |
References
[edit]- ^ "Intel open-sources CVAT, a toolkit for data labeling". VentureBeat. 2019-03-05. Retrieved 2019-03-09.
- ^ "Computer Vision Annotation Tool: A Universal Approach to Data Annotation". software.intel.com. 2019-03-01. Retrieved 2019-03-09.
- ^ "Computer Vision Annotation Tool (CVAT) source code on github". GitHub. Retrieved 3 March 2019.
- ^ "LabelMe Source". GitHub. Retrieved 26 January 2017.
- ^ "Encord Source". Documentation. Retrieved 26 January 2017.
- ^ "TagLab Source". GitHub. Retrieved 5 July 2023.
- ^ Pavoni, Gaia; Corsini, Massimiliano; Ponchio, Federico; Muntoni, Alessandro; Edwards, Clinton; Pedersen, Nicole; Sandin, Stuart; Cignoni, Paolo (2022). "TagLab: AI-assisted annotation for the fast and accurate semantic segmentation of coral reef orthoimages". Journal of Field Robotics. 39 (3): 246–262. doi:10.1002/rob.22049. S2CID 244648241.
- ^ Costa, Bryan; Sweeney, Edward; Mendez, Arnold (October 2022). "Leveraging Artificial Intelligence to Annotate Marine Benthic Species and Habitats". Noaa Technical Memorandum Nos Nccos. 306. doi:10.25923/7kgv-ba52.
- ^ Tung, Liam. "Free AI developer app: IBM's new tool can label objects in videos for you". ZDNet.
- ^ Solawetz, Jacob (July 27, 2020). "Getting Started with VoTT Annotation Tool for Computer Vision". Roboflow Blog.
- ^ "Best Open Source Annotation Tools for Computer Vision". www.sicara.ai.
- ^ "Beyond Sentiment Analysis: Object Detection with ML.NET". September 20, 2020.
- ^ "GitHub - microsoft/VoTT: Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos". November 15, 2020 – via GitHub.