Book Image

TinyML Cookbook

By : Gian Marco Iodice
Book Image

TinyML Cookbook

By: Gian Marco Iodice

Overview of this book

This book explores TinyML, a fast-growing field at the unique intersection of machine learning and embedded systems to make AI ubiquitous with extremely low-powered devices such as microcontrollers. The TinyML Cookbook starts with a practical introduction to this multidisciplinary field to get you up to speed with some of the fundamentals for deploying intelligent applications on Arduino Nano 33 BLE Sense and Raspberry Pi Pico. As you progress, you’ll tackle various problems that you may encounter while prototyping microcontrollers, such as controlling the LED state with GPIO and a push-button, supplying power to microcontrollers with batteries, and more. Next, you’ll cover recipes relating to temperature, humidity, and the three “V” sensors (Voice, Vision, and Vibration) to gain the necessary skills to implement end-to-end smart applications in different scenarios. Later, you’ll learn best practices for building tiny models for memory-constrained microcontrollers. Finally, you’ll explore two of the most recent technologies, microTVM and microNPU that will help you step up your TinyML game. By the end of this book, you’ll be well-versed with best practices and machine learning frameworks to develop ML apps easily on microcontrollers and have a clear understanding of the key aspects to consider during the development phase.
Table of Contents (10 chapters)

Preparing the skeleton of the TFLu project

Only a few steps are separating us from the completion of this project. Now that we have the input test image, we can leave Colab's environment and focus on the application with the Zephyr OS.

In this recipe, we will prepare the skeleton of the TFLu project from the pre-built TFLu hello_world sample available in the Zephyr SDK.

The following C files contain the code referred to in this recipe:

  • main.c, main_functions.cc, and main_functions.h:

https://github.com/PacktPublishing/TinyML-Cookbook/blob/main/Chapter07/ZephyrProject/Skeleton

Getting ready

This section aims to provide the basis for starting a new TFLu project with the Zephyr OS from scratch.

The easiest way to create a project is to copy and edit one of the pre-built samples for TFLu. The samples are available in the ~/zephyrproject/zephyr/samples/modules/tflite-micro folder. At the time of writing, there are two ready-to-use examples:

  • hello_world...