COCO Annotator

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Score7.1

Rank#2 of 24

PriceFree

Free planYes

Runs onAPI, Linux, Self-hosted, Web, Windows

Summary

COCO Annotator is a web-based tool for preparing image datasets used in image localization and object detection. It supports bounding boxes, polygons, segmentation masks, keypoints, and points, along with disconnected shapes treated as one instance, multiple labels on a segment, and custom metadata. Users can import datasets annotated in COCO format and export annotations directly to that format. Assisted annotation options include DEXTR, MaskRCNN, Magic Wand, semi-trained model annotation, and Google Images dataset generation. The tool includes user authentication and a REST API with a Swagger interface at localhost:5000/api. It is self-hosted, with Linux and Windows listed among its platforms. Docker and docker-compose are required: Docker is the only supported installation method. Deployment documentation covers development and production builds, and guidance for centralized datasets and external access. The server uses Flask, Eventlet, and Gunicorn, while long-running requests go to RabbitMQ workers. The project recommends HTTPS to encrypt communication between the browser and site. The software is free under the listed MIT-licensed plan.

Who it is for

COCO Annotator suits teams preparing labeled image data for object detection or localization. It is for users comfortable running a self-hosted service with Docker and docker-compose.

What is good

Exports and imports datasets in COCO format.
Supports segmentation, keypoints, and custom metadata.
Assisted annotation tools are included.
REST API and user authentication are available.

What to know first

Docker and docker-compose are required.
Docker is the only supported installation method.
HTTPS is strongly recommended for deployment.

Verdict

COCO Annotator brings a broad set of annotation types and assisted tools to a self-hosted workflow. Its Docker-only installation requirement is important to weigh before adopting it.

COCO Annotator plans and pricing

All plans

MIT-licensed software Free self-hosted · Docker required github.com · 1 Oct 2026

Compared on AI image annotation tools

Free plan: Yesgithub.com
Annotation types: bounding boxes, polygons, segmentation masks, keypoints, pointsgithub.com
AI-assisted labeling: Yesgithub.com
Export formats: COCO JSONgithub.com
API access: Yesgithub.com
Deployment: self-hostedgithub.com

Facts

Purpose: COCO Annotator is a web-based image annotation tool for creating training data for image localization and object detection.github.com · 1 Oct 2026
Annotation formats: It directly exports annotations to COCO format and imports datasets already annotated in COCO format.github.com · 1 Oct 2026
Annotation features: It supports object segmentation, keypoints, disconnected objects as one instance, multiple labels per image segment, and custom metadata.github.com · 1 Oct 2026
Assisted tools: It includes DEXTR, MaskRCNN, Magic Wand, semi-trained model annotation, and Google Images dataset generation.github.com · 1 Oct 2026
REST API: The API uses resource-oriented REST URLs, HTTP response codes, and mostly JSON responses, with a Swagger interface at localhost:5000/api.github.com · 1 Oct 2026
Authentication: The feature list includes a user authentication system.github.com · 1 Oct 2026
Installation: Docker and docker-compose are required because Docker is currently the only supported installation method.github.com · 1 Oct 2026
Scaling: The dedicated-server guidance describes centralized datasets and external access for outsourcing, with a recommended basic instance of 2GB RAM and 2 CPU cores.github.com · 1 Oct 2026
Transport security: The deployment guide strongly recommends HTTPS because it encrypts communication between the browser and website.github.com · 1 Oct 2026
Architecture: The web server uses Flask, Eventlet, and Gunicorn, while long-running requests are passed to workers through RabbitMQ.github.com · 1 Oct 2026
Data storage: Docker volumes store database-generated data and are described as compatible with both Linux and Windows containers.github.com · 1 Oct 2026
Support: The project invites users to join its Discord community of machine-learning practitioners.github.com · 1 Oct 2026
Security posture: The GitHub repository reports that no SECURITY.md security policy is detected and that there are no published security advisories.github.com · 1 Oct 2026