How can a warehouse, yard or store use computer vision to count stock from photos or video instead of counting by hand?

---
title: "How to count inventory with computer vision"
description: "Start with one area and one kind of item that is counted often, such as pallets in a racking aisle, cases on a shelf or vehicles in a yard, and fix where and how images are captured, from a fixed camera, a phone walk-through or a scheduled drone or vehicle pass. Computer vision detects and counts the items in each image, matches each count to a location, and compares it with what the stock system expects. Differences above an agreed tolerance go to a person to check before any stock record is changed, and images the model is unsure about are reviewed and used to improve it."
url: https://lidvizion.ai/answers/how-to-count-inventory-with-computer-vision/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---

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

# How can a warehouse, yard or store use computer vision to count stock from photos or video instead of counting by hand?

Start with one area and one kind of item that is counted often, such as pallets in a racking aisle, cases on a shelf or vehicles in a yard, and fix where and how images are captured, from a fixed camera, a phone walk-through or a scheduled drone or vehicle pass. Computer vision detects and counts the items in each image, matches each count to a location, and compares it with what the stock system expects. Differences above an agreed tolerance go to a person to check before any stock record is changed, and images the model is unsure about are reviewed and used to improve it.

## What this means in practice

- Start with one area and one item type that is counted often.
- Fix where and how images are captured.
- Count items per location and compare with the stock system.
- Send differences above tolerance to a person before records change.
- Review uncertain images and use them to improve the model.

## 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 Computer vision

- [How can a stadium, arena or event venue use its existing cameras to spot crowding and queues early without identifying anyone?](https://lidvizion.ai/answers/how-to-monitor-crowd-flow-with-computer-vision/)
- [How can a city, county or utility use cameras on vehicles that already drive the routes to find potholes, damaged signs and other street defects sooner?](https://lidvizion.ai/answers/how-to-find-road-and-street-defects-with-computer-vision/)
- [How can a team, venue or event organizer use computer vision to report where sponsor logos appeared in footage without logging screen time by hand?](https://lidvizion.ai/answers/how-to-measure-sponsor-exposure-with-computer-vision/)

[Compare services](https://lidvizion.ai/services/) · [Use a planning tool](https://lidvizion.ai/tools/) · [Explore workflow use cases](https://lidvizion.ai/use-cases/) · [More direct answers](https://lidvizion.ai/answers/)

Talk it through

## Have a version of this question inside your company?

Bring the decision, the constraints, and what a good outcome looks like.

[Talk through the decision](https://lidvizion.ai/contact/?need=milestone-delivery&from=%2Fanswers%2Fhow-to-count-inventory-with-computer-vision%2F#write) · [Book a call](https://calendar.app.google/bB26LdA9e2gmGFp69)