COCO Annotator vs Keylabs
COCO Annotator
github.comKeylabs
keylabs.aiSide by side
| Figure | COCO Annotator | Keylabs |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | Yes |
| Open source | Yes | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 4 |
| Spec score · AI Image Annotation Tools | 9.0 (#2) | 8.1 (#8) |
| Deployment | The documentation provides production and development Docker builds, and describes the production build as stable and suitable for a large user base. | Keylabs says it can be deployed in the cloud or on customer hardware, including a fully on-premise option for enterprises without internet access. |
| Support | The project invites users to join its Discord community of machine-learning practitioners. | The pricing page lists customer support hours per month as a plan feature but does not show the hour amounts in its text. |
Plans
Keylabs
- Startup$1, paid once
- Pro$2.10, paid once
- Business$2.30, paid once
- EnterprisePriced on request
In their own words
COCO Annotator
COCO Annotator is a web-based tool for creating image annotations used in training data for 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 an image segment, and custom metadata. Users can import existing COCO datasets and export annotations in COCO format. Assisted options include DEXTR, MaskRCNN, Magic Wand, semi-trained model annotation, and Google Images dataset generation. The software includes user authentication and a REST API, with a Swagger interface at localhost:5000/api. It is self-hosted on Linux or Windows, and Docker with docker-compose is required because Docker is the only supported installation method. Documentation covers development and production builds, 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 browser-to-site communication and invites users to its Discord community. It is listed as free under an MIT-licensed plan.