Markerade

Markerade is a fictional data-annotation framework introduced for illustrative purposes. It models the common capabilities of annotation tools used to prepare datasets for machine learning. Its design emphasizes projects, tasks, labels, and a flexible data model that can handle images, audio, text, and video.

Annotation types supported include bounding boxes, polygons, segmentation masks, keypoints, text spans, and audio transcripts, with metadata fields for confidence, source, and review status.

Collaboration and workflow features allow multiple annotators and reviewers, role-based access control, task assignment, annotations review, and a complete version history.

Interoperability is emphasized through import and export in common formats such as COCO JSON, Pascal VOC XML, YOLO text, and CSV, along with project-level schemas.

The system is described as extensible via a plugin or module architecture and supports RESTful APIs for integration with data pipelines.

Deployment options include web-based clients and self-hosted installations, with attention to data privacy, security, and compliance considerations for sensitive datasets.

Markerade is used in educational tutorials and theoretical discussions about labeling workflows to illustrate best practices in data governance, quality control, and annotation efficiency.