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. 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]
Labelbox Labelbox is a data labeling platform for enterprises to easily train expert machine learning applications.[4] It can be used with on-premise data or hosted data. It is agnostic to data type and has an open source labeling frontend[5] with already built interfaces for image classification and segmentation, text, audio and video annotation. Labelbox supports custom built labeling interfaces using a javascript API (labeling-api.js). Additional features include exporting data in JSON/CSV/WKT/COCO/Pascal VOC with auto-generated image masks, project and team management and labeling analytics. Javascript, HTML, CSS, Python Cloud or On-premise, some interfaces are Apache-2.0 [4]
LabelMe Online annotation tool to build image databases for computer vision research. Perl, Javascript, HTML, CSS[6] MIT License [7]
RectLabel An image annotation tool to label images for bounding box object detection and segmentation.[8] macOS Custom License [7][9]
VGG Image Annotator (VIA) VGG Image Annotator (VIA) is an image annotation tool that can be used to define regions in an image and create textual descriptions of those regions.[10] Can be used offline. Supported region shapes: rectangle, circle, ellipse, polygon, point and polyline. Javascript, HTML, CSS[11] BSD-2 clause license [10][12][13]

References[edit]

  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". Retrieved 3 March 2019.
  4. ^ a b "A pickaxe for the AI gold rush, Labelbox sells training data software". TechCrunch. Retrieved 2018-07-31.
  5. ^ "Labelbox labeling interface source". Retrieved 10 March 2018.
  6. ^ "LabelMe Source". Retrieved 26 January 2017.
  7. ^ a b "Reducing the Pain: A Novel Tool for Efficient Ground-Truth Labelling in Images" (PDF). Auckland University of Technology. Retrieved 2018-10-13.
  8. ^ "RectLabel support page". Retrieved 29 March 2017.
  9. ^ "Faster R-CNN-Based Glomerular Detection in Multistained Human Whole Slide Images". The University of Tokyo Hospital. Retrieved 2018-07-04.
  10. ^ a b "VGG Image Annotator (VIA)". www.robots.ox.ac.uk. Retrieved 2019-02-03.
  11. ^ "Visual Geometry Group / via". GitLab. Retrieved 2019-02-05.
  12. ^ "Easy Image Bounding Box Annotation with a Simple Mod to VGG Image Annotator". Puget Systems. Retrieved 2019-02-05.
  13. ^ Loop, Humans in the (2018-10-30). "The best image annotation platforms for computer vision (+ an honest review of each)". Hacker Noon. Retrieved 2019-02-05.