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
TagLab Desktop open source interactive software system for facilitating the precise annotation of benthic species in orthophoto of the bottom of the sea. Python [5] GPL [6] [7]
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 [8][9][10][11][12][13]

References
  1. "Intel open-sources CVAT, a toolkit for data labeling". VentureBeat. 2019-03-05. Retrieved 2019-03-09.
  2. "Computer Vision Annotation Tool: A Universal Approach to Data Annotation". software.intel.com. 2019-03-01. Retrieved 2019-03-09.
  3. "Computer Vision Annotation Tool (CVAT) source code on github". GitHub. Retrieved 3 March 2019.
  4. "LabelMe Source". GitHub. Retrieved 26 January 2017.
  5. {"TagLab Source". GitHub. Retrieved 5 July 2023.
  6. 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.
  7. 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.
  8. Tung, Liam. "Free AI developer app: IBM's new tool can label objects in videos for you". ZDNet.
  9. Bornstein, Aaron (Ari) (February 4, 2019). "Using Object Detection for Complex Image Classification Scenarios Part 4". Medium.
  10. Solawetz, Jacob (July 27, 2020). "Getting Started with VoTT Annotation Tool for Computer Vision". Roboflow Blog.
  11. "Best Open Source Annotation Tools for Computer Vision". www.sicara.ai.
  12. "Beyond Sentiment Analysis: Object Detection with ML.NET". September 20, 2020.
  13. "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.
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