Overview

Time: ~45 minutes

Scenario

This tutorial uses the simplest work cell (camera + compute) to teach patterns that apply to all Viam applications.

You’re building a quality inspection station for a canning line. Cans move past a camera on a conveyor belt. Your system must:

  1. Detect when a can is present
  2. Classify it as PASS or FAIL (identifying dented cans)
  3. Log results for review and analysis
  4. Provide a monitoring dashboard for operators

Tutorial

In this tutorial you will work through a series of tasks that are common to many robotics applications. The techniques you learn here are applicable regardless of what hardware, software, data, or machine learning models you are working with.

PartTimeWhat you’ll do
Part 1: Vision pipeline~10 minSet up camera, ML model, and vision service
Part 2: Data capture~5 minConfigure automatic image capture and cloud sync
Part 3: Control logic~10 minGenerate module, write inspection logic, test from CLI
Part 4: Deploy a module~10 minDeploy module, configure detection data capture
Part 5: Productize~10 minBuild monitoring dashboard with Teleop
Full section outline

Part 1: Vision pipeline (~10 min)

Part 2: Data capture (~5 min)

Part 3: Control logic (~10 min)

Part 4: Deploy a module (~10 min)

Part 5: Productize (~10 min)

Get started

Begin Part 1: Vision pipeline →