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How to Train a Custom YOLOv5 Model to Detect Objects

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25 Nov 2022CPOL13 min read 19.3K   501   9  
In this article, I will discuss what I experienced while creating a custom model for the detection of backyard pests. You can download the resulting critters.pt file.
This article outlines the process of creating a custom model for object detection using YOLOv5 architecture. It covers setting up the training environment, obtaining a large annotated dataset, training the model, and using the custom model in CodeProject.AI Server. The article presents observations and improvements to achieve higher accuracy in object detection.

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)


Written By
Software Developer (Senior) CodeProject
Canada Canada
As Senior Architect, Matthew is responsible for the Architecture, Design, and Coding of the CodeProject software as well as Manager of the Infrastructure that runs the web site.

Matthew works on improving the performance and experience of the Code Project site for users, clients, and administrators.

Matthew has more years of software development, QA and architecture experience under his belt than he likes to admit. He graduated from the University of Waterloo with a B.Sc. in Electrical Engineering. He started out developing micro-processor based hardware and software including compilers and operating systems.
His current focus is on .NET web development including jQuery, Webforms, MVC, AJAX, and patterns and practices for creating better websites.
He is the author of the Munq IOC, the fastest ASP.NET focused IOC Container.
His non-programming passions include golf, pool, curling, reading and building stuff for the house.

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