Labellerr vs Labelme

Labellerr is a data labeling and annotation platform for AI and machine-learning teams preparing training data. Projects can use images, videos, PDFs, text, and audio. Annotation options include bounding boxes, polygons, polylines, keypoints, dots, classification, segmentation, and object detection. Automated labeling includes prompt-based and model-assisted methods, plus active learning; the company also states native support for Meta’s SAM, SAM 2, and SAM 3. A Python SDK can manage datasets and workflows in ML pipelines. Annotated data can be exported in formats such as COCO JSON, YOLO, Pascal VOC XML, CSV, and custom formats. Remote storage options include AWS S3, Google Cloud Storage, and Azure Blob; integrations with Vertex AI, SageMaker, and Azure ML are add-ons for applicable plans. Stated security measures include Auth0 authentication, TLS 1.2 or higher in transit, and AES-256 encryption. The free Researcher plan includes 2,500 data credits, one seat, one workspace, and up to 10 projects. Pro costs $9,999 a year, and unused data credits do not roll into the next payment cycle.

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.