V7

V7 is for computer vision teams that need to create and manage labeled datasets for training or evaluating AI models. Its Darwin workspace organizes image and video data into datasets and annotation workflows, where teams can label objects with bounding boxes, polygons, tags, keypoints, and other annotation types. Annotators can use Auto-Annotate and model-assisted labeling to generate or refine labels, while review steps help teams check annotation quality. V7 also supports training certain vision models or connecting an external model to a workflow. For medical imaging projects, it handles DICOM and NIfTI files. Teams can import and export data and annotations, including through V7’s Python tools, making it suited to projects that need a shared labeling workflow alongside existing machine-learning pipelines.

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