Package detection: Datasets & Models
Detects packages, parcels, and boxes in images and video streams from warehouse and logistics environments. Locates each package with a bounding box so downstream systems can count, track, or route items.
Package detection
This package detection workflow runs an object detection model on images and video streams from warehouse and logistics environments, identifying parcels, boxes, and envelopes in each frame. It returns a bounding box for every detected package so downstream systems can count, track, sort, or route items automatically.
Try it out
Powered by general detection model
Run on custom image
Drop an image here or click to upload
Why automate package detection
Manually counting parcels, confirming they were loaded, or checking for packages left on a conveyor is slow, error-prone, and does not scale during peak volume. Automating package detection with a vision model lets a warehouse verify item counts at each handoff, flag missed or misplaced parcels, and monitor dock activity around the clock without adding headcount. Because detection runs on frames from cameras you already have, you get an auditable record of what was seen and when. That translates into fewer lost items, faster dispute resolution, and tighter throughput visibility.
Key benefits
Teams gain automated, consistent parcel counting and location data that integrates with existing camera infrastructure, WMS, and sortation control systems. The detection model can be deployed at the edge on the dock or in the cloud and scales from a single conveyor to an entire distribution network. RF-DETR is a strong recommended starting point for reliable package detection across varied lighting, box sizes, and occlusion conditions.
How to use it
- Upload an image: Drop any photo into the widget above to try package detection for free, right on this page.
- Preview instant results: The model detects package, cardboard box, envelope, pallet, shipping label 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 package 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 package detection, fine-tune it on your own labeled images, then deploy to a Serverless Cloud API endpoint.
Not sure where to start?
Describe your Package Detection project to Roboflow Agent.