Retail Object Detection with RF-DETR

The guide outlines the development of an automated beverage shelf-monitoring system using Roboflow Workflows, focusing on detecting Coca-Cola, Fanta, and Sprite bottles on retail shelves. It employs an RF-DETR model to identify and count these bottles, with a Custom Python block assessing the counts against set targets to prioritize restocking. Gemini 2.5 Pro generates inspection summaries from annotated images, enabling staff to quickly identify which shelves need attention. The system addresses common retail challenges such as in-store execution errors that lead to out-of-stock events, by providing a continuous monitoring solution that reduces manual checks and helps prioritize replenishment actions. The workflow's flexibility allows for adjustments in detection, replenishment logic, and summary creation, making it adaptable for broader store deployment through fixed cameras and integration with platforms like Slack for task management.

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