Skip to content

Latest commit

 

History

History
142 lines (108 loc) · 5.72 KB

README.md

File metadata and controls

142 lines (108 loc) · 5.72 KB
Raw

Features • Wiki • Getting Started • Issues • License

COCO Annotator is a web-based image annotation tool designed for versatility and efficiently label images to create training data for image localization and object detection. It provides many distinct features including the ability to label an image segment (or part of a segment), track object instances, labeling objects with disconnected visible parts, efficiently storing and export annotations in the well-known COCO format. The annotation process is delivered through an intuitive and customizable interface and provides many tools for creating accurate datasets.


Join our growing discord community of ML practitioner


Image annotations using COCO Annotator

Checkout the video for a basic guide on installing and using COCO Annotator.


Note: This video is from v0.1.0 and many new features have been added.


If you enjoy my work please consider supporting me


Features

Several annotation tools are currently available, with most applications as a desktop installation. Once installed, users can manually define regions in an image and creating a textual description. Generally, objects can be marked by a bounding box, either directly, through a masking tool, or by marking points to define the containing area. COCO Annotator allows users to annotate images using free-form curves or polygons and provides many additional features were other annotations tool fall short.

  • Directly export to COCO format
  • Segmentation of objects
  • Ability to add key points
  • Useful API endpoints to analyze data
  • Import datasets already annotated in COCO format
  • Annotate disconnect objects as a single instance
  • Labeling image segments with any number of labels simultaneously
  • Allow custom metadata for each instance or object
  • Advanced selection tools such as, DEXTR, MaskRCNN and Magic Wand
  • Annotate images with semi-trained models
  • Generate datasets using google images
  • User authentication system

For examples and more information check out the wiki.

Demo

Login Information
Username: admin
Password: password

https://annotator.justinbrooks.ca/

Backers

If you enjoy the development of coco-annotator or are looking for an enterprise annotation tool, consider checking out DataTorch.

https://datatorch.io · [email protected] · Next generation of coco-annotator

Built With

Thanks to all these wonderful libaries/frameworks:

Backend

  • Flask - Python web microframework
  • MongoDB - Cross-platform document-oriented database
  • MongoEngine - Python object data mapper for MongoDB

Frontend

  • Vue - JavaScript framework for building user interfaces
  • Axios - Promise based HTTP client
  • PaperJS - HTML canvas vector graphics library
  • Bootstrap - Frontend component library

License

MIT

Citation

  @MISC{cocoannotator,
    author = {Justin Brooks},
    title = {{COCO Annotator}},
    howpublished = "\url{https://github.com/jsbroks/coco-annotator/}",
    year = {2019},
  }