How to Deploy a YOLOv8 Model to a Raspberry Pi

James Gallagher's guide provides a detailed walkthrough on deploying a YOLOv8 computer vision model to a Raspberry Pi using the Roboflow platform. The process begins with gathering and annotating a dataset, such as the Retail Coolers dataset from Roboflow Universe, which is used to detect empty spaces on shelves. The guide covers project creation in Roboflow, data uploading, and generating a dataset version for model training. It further explains training a YOLOv8 model and deploying it using Roboflow's hosted GPU or custom weights. On the Raspberry Pi, Docker is utilized to run a Roboflow inference server, enabling the model to operate locally without an internet connection after the initial download. The tutorial illustrates how to set up the Raspberry Pi for edge inference with cameras, making it a versatile tool for various applications, from retail monitoring to wildlife observation.