---
title: "How to inspect socks and hosiery with computer vision"
description: "A camera station looks at each sock or stocking on a board or form after knitting, toe closing and boarding, and flags holes, dropped stitches, runs, open toes, uneven length, wrong colors or patterns and pairs that do not match for a person to check. Each flag is saved with a photo and the machine and batch, so repeat problems point back to a knitting head or yarn lot. A quality lead decides every pass or rework, and the usual size, stretch and wash tests stay in place."
url: https://lidvizion.ai/answers/how-to-inspect-socks-and-hosiery-with-computer-vision/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---

[Direct answers](https://lidvizion.ai/answers/)

# How can a sock or hosiery maker use computer vision to inspect finished pairs?

A camera station looks at each sock or stocking on a board or form after knitting, toe closing and boarding, and flags holes, dropped stitches, runs, open toes, uneven length, wrong colors or patterns and pairs that do not match for a person to check. Each flag is saved with a photo and the machine and batch, so repeat problems point back to a knitting head or yarn lot. A quality lead decides every pass or rework, and the usual size, stretch and wash tests stay in place.

## What this means in practice

- A camera and backlight take pictures of each sock or stocking while it sits on a board or form, after knitting, toe closing or boarding, so holes and thin spots show up clearly.
- The model is trained on the clients own styles and yarns. It flags holes, dropped stitches, runs, open or crooked toe seams, uneven length or heel spots, wrong colors or patterns, loose threads, and left and right pieces that do not match.
- Each flag is saved with a photo, the knitting machine, the batch and the time, so the team can see if one machine, needle or yarn lot keeps causing the same problem.
- A quality lead checks every flagged piece and decides whether it ships, gets fixed or is pulled. The camera points at the product, not at workers, and any people caught in view are blurred.
- Start with one machine group and one style, compare the camera flags with what the inspectors find for a few weeks, and keep the existing size, stretch, wash and label tests 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 pottery or dinnerware maker use computer vision to inspect plates, bowls and mugs?](https://lidvizion.ai/answers/how-to-inspect-ceramic-dinnerware-with-computer-vision/)
- [How can a garment or trim maker use computer vision to inspect zippers, buttons and snaps?](https://lidvizion.ai/answers/how-to-inspect-zippers-and-garment-trims-with-computer-vision/)

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