Weapon detection: Datasets & Models

Manual monitoring of security cameras is expensive, fatiguing, and error-prone, an operator watching dozens of feeds will inevitably miss a brief moment when a firearm becomes visible. Automating weapon detection with computer vision gives security and surveillance teams a consistent, always-on layer that flags potential threats in seconds and routes them to the right people. This shortens response time in schools, transit hubs, retail sites, and public venues where every second matters. It also lets a small team cover far more cameras than they could review by hand.

Detection runs on the cameras and video infrastructure you already have, so there is no need to rip and replace hardware. The workflow scales from a single entrance camera to hundreds of feeds, and detections integrate with existing alerting, access control, and incident-management systems. Using RF-DETR as the recommended model, you get strong accuracy on small and partially hidden objects while keeping latency low enough for live monitoring.

1. Upload an image: Drop any photo into the widget above to try weapon detection for free, right on this page.
2. Preview instant results: The model detects handgun, rifle, knife, shotgun 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.