Pipeline leak detection: Datasets & Models

Manual pipeline inspection across remote right-of-way corridors is slow, expensive, and dependent on inspectors spotting subtle leaks over thousands of miles of infrastructure. Automating detection with computer vision lets energy and utilities operators triage drone and camera footage at scale, surface probable leaks for human review, and shorten the window between a failure starting and being addressed. This reduces environmental risk, regulatory exposure, and product loss while freeing inspectors to focus on confirmed incidents.

A detection model integrates directly with existing drone fleets, CCTV, and inspection video pipelines, so teams can layer automated leak flagging onto infrastructure they already operate. RF-DETR offers strong accuracy on small and visually ambiguous targets like early-stage seepage and vapor, and the workflow scales from a single site to network-wide monitoring without adding proportional headcount.

1. Upload an image: Drop any photo into the widget above to try pipeline leak detection for free, right on this page.
2. Preview instant results: The model detects oil spill, gas plume, pipe corrosion, fluid leak, damaged pipe 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.