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A web based image annotation tool used to create training data for machine learning. 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 and efficiently storing the annotation and instances information in the well-know COCO format. The annotation process is delivered though an initiative and customizable interface similar to PhotoShop.

Features

COCO Annotator provides many 2D image annotation features that other annotations tool fall short:

• Directly export to COCO format
• Segmentation of objects
• Useful API endpoints to analyze data
• Import datasets already annotated in COCO format
• Allow custom metadata for each instance or object
• Magic wand/select tool

Built With

Thanks to all these wonderful libaries/frameworks:

• Flask - Python web microframework
• Vue - Frontend javascript framework
• RequireJS - File module loader
• Axios - Promise based HTTP client
• PaperJS - Canvas editor library
• Bootstrap - Frontend component library

License

MIT