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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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Toc

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

Gesture recognition on Raspberry Pi Pico with Arm Mbed OS

Now that the model is ready, we can deploy it on the Raspberry Pi Pico.

In this recipe, we will build a continuous gesture recognition application with the help of Edge Impulse, Arm Mbed OS, and an algorithm to filter out redundant or spurious classification results.

The following Arduino sketch contains the code that will be referred to in this recipe:

  • 06_gesture_recognition.ino:

https://github.com/PacktPublishing/TinyML-Cookbook/blob/main/Chapter06/ArduinoSketches/06_gesture_recognition.ino.

Getting ready

In this recipe, we will make our Raspberry Pi Pico capable of recognizing gestures with the help of the library that's generated by Edge Impulse for Arduino IDE. In Chapter 4, Voice Controlling LEDs with Edge Impulse, we used a pre-built example to accomplish this. However, here, we will implement the entire program from scratch.

Our goal is to develop a continuous gesture recognition...

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