Build an Appearance Inspection System with Computer Vision
Blog post from Roboflow
James Gallagher's guide, published on Roboflow's blog, outlines the process of building an appearance inspection system using computer vision, specifically for identifying visual defects such as scratches on metal. The guide details a step-by-step process that includes creating a project in Roboflow, collecting and labeling data, training a model, and deploying it using Roboflow Inference. Users begin by setting up a project in Roboflow, collecting representative data from their manufacturing facilities, and labeling this data to train a model using bounding boxes. After generating a dataset version and training the model with Roboflow, the guide explains how to deploy the model and integrate it with business logic to manage defective products or alert managers. This comprehensive approach allows users to adapt the system for various types of visual defects across different materials.
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