Automate End of Line Inspection
Blog post from Roboflow
Roboflow’s webinar demonstrates an edge-based computer vision system for end-of-line inspection that identifies missing components on a carburetor assembly before shipment. Using side and overhead cameras, a rotating pedestal, RF-DETR Seg instance segmentation, and labels for both present components and expected missing-part locations, the system detects items such as screws, nuts, valves, and identifying marks while helping operators locate problems. The model was trained on 680 varied images with augmentations and annotation assistance from SAM 3 and prior custom models, emphasizing realistic camera, lighting, and component-view conditions. Roboflow Workflows combines preprocessing, segmentation, ByteTrack tracking, stabilization, counts, and visual overlays into an HMI that displays camera feeds and alerts that clear when components are reinstalled. Deployed locally on an NVIDIA Jetson through Roboflow Inference, the demonstrated application processes two camera views at roughly 8 to 9 frames per second, avoiding cloud latency and supporting on-site image processing.
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