Annotate images with semi-trained modelsįor examples and more information check out the wiki.Advanced selection tools such as, DEXTR, MaskRCNN and Magic Wand.Allow custom metadata for each instance or object.Labeling image segments with any number of labels simultaneously.Annotate disconnect objects as a single instance.Import datasets already annotated in COCO format.
COCO Annotator allows users to annotate images using free-form curves or polygons and provides many additional features were other annotations tool fall short. Generally, objects can be marked by a bounding box, either directly, through a masking tool, or by marking points to define the containing area. Once installed, users can manually define regions in an image and creating a textual description. Several annotation tools are currently available, with most applications as a desktop installation. If you enjoy my work please consider supporting me Note: This video is from v0.1.0 and many new features have been added. Join our growing discord community of ML practitionerĬheckout the video for a basic guide on installing and using COCO Annotator. The annotation process is delivered through an intuitive and customizable interface and provides many tools for creating accurate datasets. 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. 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.
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