Egg crack detection: Datasets & Models
Automated inspection of eggs on a production line to identify cracked, broken, or otherwise damaged shells using computer vision. Flags defective eggs in real time so they can be removed before packaging.
Egg crack detection
This egg crack detection workflow runs object detection on images or video frames from cameras positioned over grading, sorting, and packaging lines. It identifies eggs with hairline cracks, broken shells, and leaks, separating them from intact eggs so defective units can be flagged and removed before packaging.
Try it out
Powered by general detection model
Run on custom image
Drop an image here or click to upload
Why automate egg crack detection
Manual egg crack detection relies on candling stations and human inspectors who fatigue quickly, work inconsistently, and cannot keep pace with high-throughput food and beverage operations. A missed crack can contaminate a carton, trigger recalls, and create food safety liabilities, while over-rejection wastes good product. Automating with computer vision brings consistent, objective inspection to every egg on the line, running continuously without fatigue. Detection results can drive automatic diverters and feed quality data back into your traceability systems.
Key benefits
Teams get repeatable, round-the-clock inspection that reduces escaped defects and unnecessary waste while documenting quality for audits and compliance. The model runs on existing line cameras and standard inspection hardware, so it integrates with current grading and packaging infrastructure. As volumes grow or new SKUs are added, the same detection pipeline scales across multiple lines and facilities.
How to use it
- Upload an image: Drop any photo into the widget above to try egg crack detection for free, right on this page.
- Preview instant results: The model detects cracked egg, intact egg, broken shell, egg 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 egg crack 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 egg crack detection, fine-tune it on your own labeled images, then deploy to a Serverless Cloud API endpoint.
Not sure where to start?
Describe your Egg Crack Detection project to Roboflow Agent.