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TinyML Cookbook

You're reading from   TinyML Cookbook Combine artificial intelligence and ultra-low-power embedded devices to make the world smarter

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801814973
Length 344 pages
Edition 1st Edition
Tools
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Author (1):
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Gian Marco Iodice Gian Marco Iodice
Author Profile Icon Gian Marco Iodice
Gian Marco Iodice
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Table of Contents (10) Chapters Close

Preface 1. Chapter 1: Getting Started with TinyML 2. Chapter 2: Prototyping with Microcontrollers FREE CHAPTER 3. Chapter 3: Building a Weather Station with TensorFlow Lite for Microcontrollers 4. Chapter 4: Voice Controlling LEDs with Edge Impulse 5. Chapter 5: Indoor Scene Classification with TensorFlow Lite for Microcontrollers and the Arduino Nano 6. Chapter 6: Building a Gesture-Based Interface for YouTube Playback 7. Chapter 7: Running a Tiny CIFAR-10 Model on a Virtual Platform with the Zephyr OS 8. Chapter 8: Toward the Next TinyML Generation with microNPU 9. Other Books You May Enjoy

Chapter 7: Running a Tiny CIFAR-10 Model on a Virtual Platform with the Zephyr OS

Prototyping a TinyML application directly on a physical device is really fun because we can instantly see our ideas at work in something that looks and feels like the real thing. However, before any application comes to life, we need to ensure that the models work as expected and, possibly, among different devices. Testing and debugging applications directly on microcontroller boards often requires a lot of development time. The main reason for this is the necessity to upload a program into a device for every change in code. However, virtual platforms can come in handy to make testing more straightforward and faster.

In this chapter, we will build an image classification application with TensorFlow Lite for Microcontrollers (TFLu) for an emulated Arm Cortex-M3 microcontroller. We will start by installing the Zephyr OS, the primary framework used in this chapter to accomplish our task. Next, we will...

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