/answers/how-to-grade-coffee-beans-with-computer-vision/index.md · 42 lines
---
title: "How to grade coffee beans with computer vision"
description: "A camera over a sample tray or a sorting belt takes photos of the beans under even light. A model trained on the business own images, labeled against its own grade sheet, marks likely defects such as black, sour or broken beans, insect damage, shells, husks and foreign material like stones or sticks. It counts flagged beans in each sample so the grader can compare lots quickly, and for roasted beans it can check that color looks even across a batch. Every flag keeps its photo so the grader can see why. A grader reviews the counts and photos, runs the usual cupping and moisture checks, and decides the grade and what is bought, blended or roasted. The model does not replace cupping, moisture tests or official grading, which stay in place, and people make every grade and buying call."
url: https://lidvizion.ai/answers/how-to-grade-coffee-beans-with-computer-vision/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---
[Direct answers](https://lidvizion.ai/answers/)
# How can a coffee importer, mill or roaster use computer vision to check green and roasted beans?
A camera over a sample tray or a sorting belt takes photos of the beans under even light. A model trained on the business own images, labeled against its own grade sheet, marks likely defects such as black, sour or broken beans, insect damage, shells, husks and foreign material like stones or sticks. It counts flagged beans in each sample so the grader can compare lots quickly, and for roasted beans it can check that color looks even across a batch. Every flag keeps its photo so the grader can see why. A grader reviews the counts and photos, runs the usual cupping and moisture checks, and decides the grade and what is bought, blended or roasted. The model does not replace cupping, moisture tests or official grading, which stay in place, and people make every grade and buying call.
## What this means in practice
- Start with sample trays from one origin or product line.
- Label photos from your own samples against your own grade sheet.
- Show defect counts and photos to the grader for each lot.
- Check roast color across batches on the same setup.
- Keep cupping, moisture tests and official grading in place.
## How Lid Vizion approaches it
We start with the business decision and operating context, define ownership and measurable milestones, then use configuration, integrations, automation, or custom software only where each earns its place.
## More on Automation & custom AI
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- [How can a waste hauler or property manager use computer vision to see how full dumpsters and roll-off bins are?](https://lidvizion.ai/answers/how-to-check-dumpster-fill-levels-with-computer-vision/)
- [How can a chocolate or candy maker use computer vision to check pieces on the line?](https://lidvizion.ai/answers/how-to-inspect-chocolate-and-candy-with-computer-vision/)
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