SuperAnnotate vs VGG Image Annotator

SuperAnnotate is infrastructure for AI teams building, evaluating, and improving datasets until they are ready for training. It handles RL environments, RLHF, image, video, audio, LiDAR, and custom modalities. Model-assisted workflows can pre-label data, judge rubrics, score pass rates, and route items between models and human experts. Teams can configure workflows, roles, quality gates, dashboards, and project or contributor analytics. Annotation types include classification, key points, bounding boxes, polygons, polylines, tiled imagery, cuboids, and skeletons. The platform offers a Python SDK and API, team collaboration, and integrations with AWS, Google Cloud, Azure, Snowflake, Databricks, and custom storage. External storage connections are read-only and do not automatically import new files. It runs through web, macOS, Windows, and API access. SuperAnnotate was founded in 2018 and is headquartered in Silicon Valley. Pricing is paid and available on request.

VGG Image Annotator (VIA) is a suite of lightweight browser tools for manually annotating images, audio, and video. The applications are distributed as single HTML files, allowing offline use without installation or setup. VIA3 handles images, video, audio, and shared or collaborative projects. VIA2 works with image files, does not support shared projects, and remains maintained. Annotation shapes include rectangles, circles, ellipses, points, polygons, and polylines. Projects can import or export annotations as CSV or JSON, while scripts support COCO and Web Annotation formats; a Python package converts VIA projects to COCO. Shared work can use a free public Version File Store maintained by the Visual Geometry Group, or a user-run VFS. VIA is built with HTML, CSS, and JavaScript without external libraries and released under the two-clause BSD license for academic and commercial use. Downloads include ZIP archives and standalone HTML files for versions 2 and 3. The makers provide a guide, FAQ, and email contacts.