How to Build an Edge Vision System for Weld Inspection

Weld quality is crucial for structural integrity across various industries, and historically, inspection has relied on manual spot-checks that are susceptible to human error and inefficiencies. The introduction of computer vision into this domain offers an automated, high-precision inspection system capable of achieving complete inspection coverage with consistent results. This guide outlines the development of a simple object detection system using a two-layer approach: a high-speed RF-DETR model for weld location and initial classification, and a Gemini multimodal model for deeper analysis of detected defects. By leveraging Roboflow's platform for dataset management and model training, users can create a robust system that distinguishes between critical welding defects and provides real-time feedback to prevent faulty parts from progressing further in the production line. This integration of RF-DETR and Gemini enables the creation of a vision agent that is both fast and precise, transforming traditional quality control processes into a data-driven approach.

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