X AnyLabeling

Rather than requiring annotators to draw bounding boxes and polygons manually around every object, X-AnyLabeling enables click-based segmentation (click a point on an object to get an accurate polygon mask), text-prompted detection (describe what to detect in natural language), and automated pre-labeling that generates annotations across entire datasets for human review.

The tool supports all major annotation formats YOLO, COCO JSON, Pascal VOC XML, LabelMe JSON and exports directly into formats compatible with common training frameworks.

Annotators can switch between different AI assistance modes depending on task complexity: using automated detection for common object classes with high recall, click-based segmentation for irregular shapes, and manual polygon editing for cases where AI assistance requires correction.

The combination reduces annotation time significantly compared to fully manual workflows while maintaining the accuracy that training data quality requires.

X-AnyLabeling is open-source under the GPL-3.0 license and runs as a desktop application on Windows, macOS, and Linux.

It is designed for computer vision teams at companies, research institutions, and annotation service providers who need efficient labeling workflows for object detection, instance segmentation, keypoint detection, and image classification tasks.

The integration of continuously improving foundation models means the tool's auto-annotation quality improves as new models are added, without requiring changes to annotation workflows.