Capsule inspection: Datasets & Models

Manual capsule inspection is slow, inconsistent, and difficult to scale to the throughput required in pharma manufacturing, where operator fatigue leads to missed defects and inconsistent reject rates. In a regulated environment, missing a cracked or contaminated capsule carries real compliance and recall risk. Automating with computer vision gives you consistent, repeatable inspection at line speed, with a full audit trail of every unit and defect flagged. It frees skilled operators from repetitive checks and lets you tighten quality thresholds without slowing production.

A detection model catches subtle defects across high volumes with uniform criteria, reducing escaped defects and false rejects while maintaining traceability for quality documentation. It integrates with the cameras and PLCs already on your packaging lines and scales from a single station to plant-wide deployment. Starting from an existing capsule defect dataset and a model like RF-DETR shortens the path from prototype to validated inspection.

1. Upload an image: Drop any photo into the widget above to try capsule inspection for free, right on this page.
2. Preview instant results: The model detects capsule, cracked capsule, dented capsule, discolored capsule, empty capsule 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.
3. 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.
4. 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.