Glove detection: Datasets & Models
Glove detection uses computer vision to verify that workers are wearing safety gloves on construction and infrastructure sites. It flags bare hands in real time from standard camera feeds.
Glove detection
This detection workflow analyzes images or video frames from standard site cameras to locate workers' hands and classify each as gloved or ungloved. Built on a safety gloves dataset spanning varied lighting, camera angles, and construction backgrounds, it outputs bounding boxes that flag bare hands for real-time PPE compliance checks.
Try it out
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Why automate glove detection
Manually monitoring PPE compliance on a busy construction or infrastructure site is tedious, inconsistent, and impossible to sustain across every worker and every shift. A supervisor cannot watch every entry point or work zone at once, and paper checklists capture only a moment in time. Automating glove detection with computer vision gives you continuous, objective coverage that catches missing hand protection before it leads to lacerations, chemical burns, or a failed audit. This turns safety enforcement from a reactive after-incident process into a proactive one.
Key benefits
Teams can run detection on existing camera infrastructure without new hardware, and RF-DETR delivers the accuracy needed to separate gloved from bare hands even in cluttered, motion-heavy scenes. The system scales from a single checkpoint to an entire site or portfolio of sites, and its outputs plug directly into alerting, access control, or compliance reporting pipelines. The result is measurable, documented PPE adherence with far less manual oversight.
How to use it
- Upload an image: Drop any photo into the widget above to try glove detection for free, right on this page.
- Preview instant results: The model detects safety glove, bare hand, worker hand, work glove 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 glove 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 glove detection, fine-tune it on your own labeled images, then deploy to a Serverless Cloud API endpoint.
Not sure where to start?
Describe your Glove Detection project to Roboflow Agent.