Intrusion detection: Datasets & Models

Manual monitoring of dozens of security camera feeds is tedious, error-prone, and expensive to staff around the clock, and human attention degrades quickly during long, uneventful shifts. Automating intrusion detection with computer vision means every frame is analyzed consistently, alerts fire the moment an unauthorized person or vehicle enters a protected area, and operators only review flagged events instead of hours of empty footage. For security and surveillance teams, that translates to faster response times, fewer missed breaches, and a searchable record of who or what entered a zone and when.

Because the model runs on the RTSP and IP camera infrastructure you already have, there is no need to rip and replace existing hardware to add automated perimeter monitoring. RF-DETR delivers reliable detection across day, night, and crowded scenes, and the same pipeline scales from a single gate to hundreds of cameras across multiple sites. Reduced false alarms and instant zone-based alerts let a lean security team cover far more ground than manual watch-standing allows.

1. Upload an image: Drop any photo into the widget above to try intrusion detection for free, right on this page.
2. Preview instant results: The model detects person, vehicle, backpack, ladder, fence 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.