List of manual image annotation tools

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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.

SoftwareDescriptionPlatformLicenseReferences
Computer Vision Annotation Tool (CVAT)Computer Vision Annotation Tool (CVAT) is an 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]

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. ↑ "Best Open Source Annotation Tools for Computer Vision". www.sicara.ai.
  10. ↑ "Beyond Sentiment Analysis: Object Detection with ML.NET". September 20, 2020.
  11. ↑ "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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