Bottle and can recognition for vending: Datasets & Models
A computer vision classifier that identifies bottles and cans in vending machine dispensers and camera feeds. It recognizes specific beverage products to power inventory tracking and automated checkout.
Bottle and can recognition for vending
This workflow performs vending product detection by classifying an image of a beverage container and returning its product class, identifying both bottle and can formats along with specific SKUs. It takes a cropped or full-frame image from a vending machine dispenser or smart cooler camera and outputs the recognized product to support inventory tracking and automated checkout.
Try it out
Powered by general detection model
Run on custom image
Drop an image here or click to upload
Why automate bottle and can recognition for vending
Retail tech teams building smart vending and grab-and-go units otherwise rely on manual audits, weight sensors, or barcode scans that miss items and slow down transactions. A vision classifier reads the actual product on the shelf, so it can confirm what was dispensed, flag when a slot is empty or misstocked, and match purchases to inventory without extra hardware. This cuts down on stockouts, shrink disputes, and the labor of route drivers checking each machine by hand. For unattended retail, automated recognition is what makes a frictionless checkout experience reliable at scale.
Key benefits
Accurate bottle and can recognition lets operators automate inventory counts, purchase verification, and restock alerts across a fleet of machines. Because it works with the cameras already inside vending units, deployment does not require ripping out existing infrastructure, and a single trained model scales to thousands of endpoints. Faster, more consistent product detection means fewer manual audits and better on-shelf availability.
How to use it
- Upload an image: Drop any photo into the widget above to try bottle and can recognition for vending for free, right on this page.
- Preview instant results: The model detects plastic bottle, aluminum can, glass bottle, juice box, energy drink can 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 Classification (ViT) 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 bottle and can recognition for vending
When you're ready to build a production model for bottle and can recognition for vending, we recommend training Classification (ViT). Unlike the ready-to-use model in the demo above, you fine-tune it on your own labeled images for higher accuracy, then deploy to a Serverless Cloud API endpoint.
Not sure where to start?
Describe your Bottle and Can Recognition for Vending project to Roboflow Agent.