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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 dont have a Raspberry Pi can run it on a Windows, Linux, or OS X computer as well.

Without further ado, lets see how it works!

For someone who may have never heard about the Raspberry Pi, lets make a short

Read more here:

A Weekend AI Project: Object Detection with YOLO on PC and Raspberry Pi | by Dmitrii Eliuseev | Jul, 2024 - Towards Data Science