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)

Converting QQVGA images from YCbCr422 to RGB888

When compiling the previous sketch on Arduino, you may have noticed the Low memory available, stability may occur warning in the Arduino IDE output log.

The Arduino IDE returns this warning because the QVGA image with the RGB565 color format needs a buffer of 153.6 KB, which is roughly 60% of the SRAM available in the microcontroller.

In this recipe, we will show how to acquire an image at a lower resolution and use the YCbCr422 color format to prevent image quality degradation.

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

  • 03_camera_capture_qqvga_ycbcr422.ino:

https://github.com/PacktPublishing/TinyML-Cookbook/blob/main/Chapter05/ArduinoSketches/03_camera_capture_qqvga_ycbcr422.ino

Getting ready

The main ingredients to reduce the image size are behind the resolution and color format.

Images are well known for requiring big chunks of memory, which might be a problem when...