Wheel detection: Datasets & Models
A computer vision workflow that locates and identifies wheels on vehicles in images and video. Useful for automotive inspection, assembly verification, and inventory tracking.
Wheel detection
This wheel detection workflow uses object detection to locate and identify wheels, tires, and rims on vehicles within images and video frames. It accepts standard camera input from production lines, service bays, or parking areas and returns bounding boxes around each detected wheel along with confidence scores.
Try it out
Powered by general detection model
Run on custom image
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Why automate wheel detection
Manually checking whether every vehicle has the correct number and type of wheels, or scanning inventory of loose rims and tires, is slow and error-prone at scale. Automating wheel detection with computer vision removes the need for a person to eyeball each frame, catching missing or misaligned wheels on an assembly line before they become downstream defects. In automotive settings this means faster inspection cycles, consistent counting, and a searchable record of what was detected and when.
Key benefits
Teams get reliable, repeatable wheel localization that runs on existing cameras and integrates into current assembly, service, or warehouse pipelines. The approach scales from a single inspection station to many parallel feeds without adding headcount, and detection results can feed directly into counting, tracking, or defect-flagging logic. Training on your own imagery with a model like RF-DETR sharpens accuracy for your specific vehicles and lighting conditions.
How to use it
- Upload an image: Drop any photo into the widget above to try wheel detection for free, right on this page.
- Preview instant results: The model detects wheel, tire, rim, hubcap 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 wheel 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 wheel detection, fine-tune it on your own labeled images, then deploy to a Serverless Cloud API endpoint.
Not sure where to start?
Describe your Wheel Detection project to Roboflow Agent.