Pipe and Tubes Quality Inspection with Roboflow
Blog post from Roboflow
The advancement of automated tube and pipe defect detection can be achieved by training Roboflow's RF-DETR model on labeled pipe imagery to identify holes, cracks, and ruptures, which are persistent threats to pipeline integrity. This process integrates with a Roboflow Workflow to assign a PASS, REVIEW, or FAIL verdict to each image, with low-confidence detections being directed to human review. The tutorial outlines the workflow, starting with capturing an image that runs through a custom-trained RF-DETR model at a low confidence threshold, followed by a separate filter block that applies the real inspection threshold, ensuring no defects are missed due to threshold settings. The model is trained on a diverse dataset encompassing various damage types under different conditions, and the workflow is designed to adapt to new defect types with additional training data. This approach enhances pipeline inspection reliability by logging each inspection to Vision Events, allowing continuous improvement of the model without altering the workflow structure.
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