V7 Darwin review
A broad annotation platform for teams building computer-vision and medical-imaging datasets.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
V7 Darwin is a web-based data-labeling platform for teams creating machine-learning datasets from images, video, medical imaging, microscopy, documents, and other visual data. It is suited to AI teams, research groups, and enterprise organizations that need structured annotation, review workflows, dataset management, and export options. Annotation types include polygons, bounding boxes, tags, skeletons, keypoints, lines, ellipses, masks, attributes, text, directional vectors, and instance IDs. Supported imagery includes common image files, DICOM, microscopy formats, and NIfTI files.
Pricing is organized around a Custom plan with a custom platform fee, user licenses, and volume-based data processing charges. A free plan is available, while the published pricing information directs prospective customers to a demo for the full suite. The platform connects with AWS, Google Cloud, Microsoft Azure, TensorFlow, and PyTorch, and provides API and SDK access for dataset and annotation management. Exports include Darwin JSON, Darwin XML, COCO, CVAT, YOLO, Semantic PNG, Instance PNG, Pascal VOC, and NIfTI.
Its strongest fit is for projects where annotation depth and workflow control matter. Auto-Annotate and SAM support AI-assisted labeling, while keyframe-based interpolation addresses video and DICOM workflows. Model-in-the-loop processing, external model integration, conditional review logic, role-based assignments, and real-time collaboration support teams with multiple stages of quality control. Teams seeking a focused, simple labeling utility may find this scope unnecessary; teams handling medical or video imagery and needing broad formats, review stages, and integration points should consider V7 Darwin.
V7 Darwin pros and cons
- Where it wins
- Supports many annotation types, including masks, skeletons, keypoints, and polygons
- AI-assisted labeling, model-in-the-loop workflows, and external model integration
- Video and DICOM interpolation plus multi-stage review and collaboration
- Where it doesn't
- Paid pricing uses custom platform fees, user licenses, and volume-based charges
- Its broad workflow may be more than teams needing simple image labeling
- The platform is web-based and API-accessible rather than open source
V7 Darwin fact sheet, pricing and score →
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