Product detection: Datasets & Models
Product detection identifies and locates retail items on shelves, in carts, or across store imagery using bounding boxes. It powers automated inventory checks, planogram compliance, and checkout systems.
Product detection
This retail product detection workflow locates individual items in images and returns a bounding box and class label for each one, covering packaged goods, bottles, cans, and boxes positioned on shelves or inside shopping carts. It accepts standard inputs such as shelf-mounted cameras, overhead store cameras, mobile phone photos, and checkout imagery, making it suitable for inventory counts, planogram checks, and automated checkout systems.
Try it out
Powered by general detection model
Run on custom image
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Why automate product detection
Manually auditing shelves, counting stock, and verifying planogram compliance across a store or fleet of stores is slow, inconsistent, and expensive in labor. Store associates can't continuously monitor every aisle, and by the time a stockout is noticed, sales are already lost. Automating retail product detection lets teams continuously monitor availability, catch out-of-stocks faster, and free staff from repetitive counting. The same detection pipeline can feed self-checkout, cashierless store concepts, and analytics on shopper behavior.
Key benefits
A trained detection model works with the cameras and phone hardware retailers already have, so there is no need to install specialized sensors. It scales from a single pilot aisle to thousands of locations while producing consistent, structured output that plugs into inventory and analytics systems. We recommend RF-DETR for its strong accuracy on dense, overlapping product scenes and its real-time inference performance.
How to use it
- Upload an image: Drop any photo into the widget above to try product detection for free, right on this page.
- Preview instant results: The model detects bottle, cereal box, can, snack bag, milk carton 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 product 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 product detection, fine-tune it on your own labeled images, then deploy to a Serverless Cloud API endpoint.
Not sure where to start?
Describe your Product Detection project to Roboflow Agent.