Image Annotation Tool

This paper has described the design and build of a secure, web-based Image Annotation Tool developed in partnership with Vasundhara Geo Technologies Pvt. Ltd. The system covers the full annotation lifecycle — signing in, creating and managing projects, uploading GeoTIFF images, drawing bounding-box annotations, organising images into datasets, and exporting labelled data — on top of a three-layer architecture combining React.js, Django REST Framework, and PostgreSQL. By supporting intranet deployment, four-tier role-based access control, GeoTIFF ingestion, and standard export formats, it closes gaps that the surveyed tools each leave open in different ways. Every module described here is built and has been tested end to end. The fifteen-minute turnaround for ten images demonstrates that the workflow is practically efficient, not just functionally complete, and both YOLO and COCO exports have been verified against the tools that would actually consume them. Table 1's comparison shows that the combination of features delivered here isn't matched by any single existing platform. Because the system is modular, adding the planned AI-assisted labelling and collaboration features later should be straightforward rather than requiring a redesign.

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