Worker detection: Datasets & Models
Worker detection uses computer vision to locate and count people on construction sites from camera feeds and images. It identifies workers in real time to support safety monitoring, access control, and site awareness.
Worker detection
This detection workflow performs construction worker detection by locating each person present on a job site and placing a bounding box around them for counting and tracking. It accepts images and video from fixed CCTV cameras, drone footage, body-worn cameras, and mobile devices, and handles variable lighting, weather, and crowded scenes.
Try it out
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Why automate worker detection
Manually watching camera feeds or walking a site to track where crews are working is slow, error-prone, and impossible to scale across large infrastructure projects with dozens of cameras. Automating worker detection gives you a continuous, objective record of who is present in restricted or hazardous zones without adding staff. Teams use it to trigger alerts when a person enters an exclusion area near heavy machinery, verify muster counts during evacuations, and audit access after incidents. The result is faster response and a documented safety trail instead of guesswork.
Key benefits
Detection runs on the RTSP and IP cameras already installed across most construction sites, so you can deploy without new hardware. The RF-DETR architecture delivers accurate detection in dense, occluded scenes and scales from a single trailer camera to a multi-site deployment. Real-time worker counts and zone alerts reduce manual monitoring and give safety managers measurable, timestamped data.
How to use it
- Upload an image: Drop any photo into the widget above to try worker detection for free, right on this page.
- Preview instant results: The model detects worker, hard hat, safety vest, person, excavator 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.
- 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.
- 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.
Recommended model for worker detection
RF-DETR is state of the art for real-time object detection, instance segmentation, and keypoint detection, with higher accuracy and lower latency than comparable models, and it's Apache 2.0 licensed. When you're ready to build a production model for worker detection, fine-tune it on your own labeled images, then deploy to a Serverless Cloud API endpoint.
Not sure where to start?
Describe your Worker Detection project to Roboflow Agent.