Dent detection: Datasets & Models

Manual dent inspection is slow, inconsistent, and depends heavily on operator fatigue and lighting conditions, which makes small dents easy to miss on a fast-moving production line. Automating dent detection with a vision model gives you repeatable, objective results that catch defects earlier, reduce scrap and rework, and prevent damaged parts from reaching customers. In manufacturing and QC environments, this means fewer warranty returns and a documented inspection record for every unit. Builders can flag borderline parts for human review rather than gating the entire line on manual checks.

Detection runs on your existing inspection cameras and integrates into line control systems via standard APIs, so you can automate reject sorting or trigger alerts without new hardware. RF-DETR provides strong accuracy on small and subtle surface defects while remaining practical to deploy at line speed. As you collect more labeled examples, the model scales across new part types and product lines with straightforward retraining.

1. Upload an image: Drop any photo into the widget above to try dent detection for free, right on this page.
2. Preview instant results: The model detects dent, scratch, metal panel, car door, surface defect within seconds and returns an annotated image with structured predictions, so you can immediately see how well it works. Adjust the detection classes and re-run until the results fit your scenario.
3. Like what you see?: With a free Roboflow account, you can deploy this workflow with the Serverless Cloud API, customize it in your workspace, or train RF-DETR on your own images for production accuracy.
4. Get started for free: No code or training data required to begin: upload, review the results, and make it part of your stack in a single click.