TrainVision is a mobile-first platform for collecting machine learning datasets in the real world. Instead of gathering images and annotating them later on desktops, teams can capture images, add annotations, and automatically collect metadata (GPS, time, device) directly from their phones. The platform is offline-first, allowing users to collect and annotate data even in environments where internet access is limited or unreliable—such as farms, fields, or remote research locations. Data is stored locally and automatically syncs to the cloud when connectivity becomes available. Because the tool lives on mobile devices, organizations can collect data at scale through distributed teams. Students, field workers, technicians, or researchers can capture and annotate data naturally during their daily activities—while walking through a campus, inspecting equipment, or working in the field. This enables massive, continuous dataset collection that would be difficult or expensive with traditional desktop-based workflows. Collected datasets appear in a web dashboard, where organizations manage projects, review data, and export datasets in standard formats (COCO/YOLO) for use in any ML pipeline or platform.
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