Labelme vs LabelU

Labelme is an AI-powered desktop annotation tool for creating image training datasets, aimed at researchers, engineers, and teams. Annotation options include polygons, rectangles, oriented rectangles, circles, lines, points, masks, and rich attributes. Local model support includes SAM, SAM2, SAM3, EfficientSAM, and YOLO-World. SAM3 accepts box and text prompts; SAM2 and EfficientSAM support point prompts, while YOLO-World returns bounding boxes. The maker says images, annotations, and exports stay on the user’s machine, without cloud processing or telemetry. Model weights are downloaded on first use; afterward, annotation and AI assistance can work offline, including in air-gapped setups using transferred models or the offline pack. Pro adds conversion and dataset tools, with exports including YOLO, YOLO-OBB, Pascal VOC, masks, visualizations, and statistics. The application is GPL-3.0, while the Pro toolkit is closed source. It runs on Apple Silicon macOS, 64-bit Windows, and 64-bit Linux; Intel Macs are supported only through v7.0.4. Starter costs $49, paid once, Pro $79, paid once, and Pro (Lifetime) $249, paid once.

LabelU has no write-up on Specifiction yet; its figures are above.