How to Monitor a Video with Computer Vision

James Gallagher's guide from the Roboflow Blog explains how to utilize computer vision to monitor videos for various scenarios by using custom logic with an aluminum can detection model. The guide demonstrates the setup process, including preparing a model using Autodistill and Roboflow Universe, running inference with Roboflow Inference powered by Docker, and installing necessary dependencies. It provides Python code to initialize video monitoring and detection logic, allowing for scenarios such as detecting when no objects are visible, when anomalous objects appear, or when too many objects are present. Examples are given in the context of a bottling plant, illustrating how to maintain production continuity by monitoring the assembly line. The guide also offers options for integrating alert systems, like recording predictions, triggering alarms, or sending notifications to quality assurance managers, ultimately equipping readers with the tools needed to apply computer vision in practical, industrial settings.