In this guide, we will be exploring how to set up *YOLO object detection* with the *Raspberry Pi AI HAT*, and more importantly, learning how to apply this in your *Python projects*. We will be taking a look at how to *install* the required *hardware and firmware* as well as how to set up and use the object detection *Python pipelines*. The result of this guide will have you equipped with an understanding of this whole setup, as well as three different *example scripts* we have written. One will "do something" when an object is detected, another when a certain number of objects are detected, and the last when an object is detected in a certain location.
💡❓ If you have any questions about this content or want to share a project you're working on head over to our *maker forum:* _http://coreelec.io/forum_
0:00 What we will be doing 0:30 What you will need 1:00 Installing the AI HAT 1:54 Installing firmware and Python pipelines 3:37 Looking at the file structure and pipeline 4:49 Running object recognition demo 6:29 Exploring the Python demo script 8:23 Project code 1: detecting objects 13:19 Disabling FPS shell reading 13:58 Project code 2: counting objects 16:03 Project code 3: object position 18:08 Wrap up
🌏🦘 *Core Electronics* is located in the heart of Newcastle, Australia. We're powered by makers, for makers. Drop by if you are looking for: