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TinyML Cookbook

You're reading from   TinyML Cookbook Combine machine learning with microcontrollers to solve real-world problems

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781837637362
Length 664 pages
Edition 2nd Edition
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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 (16) Chapters Close

Preface 1. Getting Ready to Unlock ML on Microcontrollers FREE CHAPTER 2. Unleashing Your Creativity with Microcontrollers 3. Building a Weather Station with TensorFlow Lite for Microcontrollers 4. Using Edge Impulse and the Arduino Nano to Control LEDs with Voice Commands 5. Recognizing Music Genres with TensorFlow and the Raspberry Pi Pico – Part 1 6. Recognizing Music Genres with TensorFlow and the Raspberry Pi Pico – Part 2 7. Detecting Objects with Edge Impulse Using FOMO on the Raspberry Pi Pico 8. Classifying Desk Objects with TensorFlow and the Arduino Nano 9. Building a Gesture-Based Interface for YouTube Playback with Edge Impulse and the Raspberry Pi Pico 10. Deploying a CIFAR-10 Model for Memory-Constrained Devices with the Zephyr OS on QEMU 11. Running ML Models on Arduino and the Arm Ethos-U55 microNPU Using Apache TVM 12. Enabling Compelling tinyML Solutions with On-Device Learning and scikit-learn on the Arduino Nano and Raspberry Pi Pico 13. Conclusion
14. Other Books You May Enjoy
15. Index

Classifying Desk Objects with TensorFlow and the Arduino Nano

Convolutional neural networks (CNNs) have gained popularity because of their ability to unlock challenging computer vision tasks such as image classification, object recognition, scene understanding, and pose estimation, once considered impossible to solve. Nowadays, many modern camera applications are powered by these deep learning algorithms, and we just need to open the camera app on a smartphone to see them in action. However, computer vision tasks are not restricted to smartphones or cloud-based systems. In fact, these algorithms can now be accelerated in microcontrollers, albeit with their limited computational capabilities.

In this chapter, we will see the benefit of adding sight to our tiny devices by classifying two desk objects with the OV7670 camera module, in conjunction with the Arduino Nano.

In the first part, we will learn how to acquire images from the OV7670 camera module. Then, we...

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