A Weekend AI Project: Object Detection with YOLO on PC and Raspberry Pi

Running the Latest YOLO v10 Model on Different Hardware

YOLO Objects Detection, Image by author

Computer vision can be an important part of ML apps of different scales, from $20,000 Tesla Bots or self-driving cars to smart doorbells and vacuum cleaners. It is also a challenging task because, compared to a cloud infrastructure, on “real” edge devices, the hardware specs are often much more constrained.

YOLO (You Only Look Once) is a popular object detection library; its first version was made in 2015. YOLO is particularly interesting for embedded devices because it can run almost anywhere; there are not only Python but also C++ (ONNX and OpenVINO) and Rust versions available. A year ago, I tested YOLO v8 on a Raspberry Pi 4. Nowadays, many things have changed — a new Raspberry Pi 5 became available, and a newer YOLO v10 was released. So I expect a new model on new hardware to work faster and more precisely.

The code presented in this article is cross-platform, so readers who don’t have a Raspberry Pi can run it on a Windows, Linux, or OS X computer as well.

Without further ado, let’s see how it works!

Raspberry Pi

For someone who may have never heard about the Raspberry Pi, let’s make a short…