Datasaur vs Labelme

Datasaur is a web-based platform for labeling data and coordinating labeling teams. Data Studio handles span, textual or row classification, document classification, OCR, bounding boxes, audio, and conversational labeling. LLM Labs adds sandbox experimentation, knowledge bases, human rating and ranking, and automated evaluation. The Models catalog contains over 200 base models and supports Amazon SageMaker JumpStart, Amazon Bedrock, Azure OpenAI, OpenAI, and Google Vertex AI. Integrations include OCR, language-processing, machine-learning, and cloud-storage services such as Amazon Textract, spaCy, Hugging Face, AWS S3, Google Cloud Storage, and Azure Blob Storage. The API supports webhook import and export, project creation and export, OAuth 2.0, and GraphQL; OAuth credentials are available only on Growth and Enterprise plans. Self-hosting is available with Kubernetes and Helm Chart or Docker. Datasaur states that it maintains SOC 2 Type 2, GDPR, and HIPAA compliance, with encryption at rest and in transit. Free includes one user, 5,000 labels per year, and 100MB storage. Paid plans start at $5,000/yr, and a 14-day trial is listed.

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.