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2020 | Book

Getting Started Read chapter Read first chapter

Real-Time IoT Imaging with Deep Neural Networks

Using Java on the Raspberry Pi 4

Author: Nicolas Modrzyk

Publisher: Apress

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

This book shows you how to build real-time image processing systems all the way through to house automation. Find out how you can develop a system based on small 32-bit ARM processors that gives you complete control through voice commands.

Real-time image processing systems are utilized in a wide variety of applications, such as in traffic monitoring systems, medical image processing, and biometric security systems. In Real-Time IoT Imaging with Deep Neural Networks, you will learn how to make use of the best DNN models to detect object in images using Java and a wrapper for OpenCV. Take a closer look at how Java scripting works on the Raspberry Pi while preparing your Visual Studio code for remote programming. You will also gain insights on image and video scripting. Author Nicolas Modrzyk shows you how to use the Rhasspy voice platform to add a powerful voice assistant and completely run and control your Raspberry Pi from your computer.

To get your voice intents for house automation ready, you will explore how Java connects to the MQTT and handles parametrized Rhasspy voice commands. With your voice-controlled system ready for operation, you will be able to perform simple tasks such as detecting cats, people, and coffee pots in your selected environment. Privacy and freedom are essential, so priority is given to using open source software and an on-device voice environment where you have full control of your data and video streams. Your voice commands are your own—and just your own.

With recent advancements in the Internet of Things and machine learning, cutting edge image processing systems provide complete process automation. This practical book teaches you to build such a system, giving you complete control with minimal effort.

What You Will Learn:

Show mastery by creating OpenCV filtersExecute a YOLO DNN model for image detectionApply the best Java scripting on Raspberry Pi 4Prepare your setup for real-time remote programmingUse the Rhasspy voice platform for handling voice commands and enhancing your house automation setup

Who This Book Is For:Engineers, and Hobbyists wanting to use their favorite JVM to run Object Detection and Networks on a Raspberry Pi

Table of Contents

Frontmatter
Chapter 1. Getting Started
Abstract
One of the goals of this book is to get you ready with real-time IoT imaging quickly, avoiding a lengthy installation process. Being ready quickly doesn’t mean we are going to take any shortcuts, it means we will get the tooling part out of the way so we can focus on the creation process.
Nicolas Modrzyk
Chapter 2. Object Detection in Video Streams
Abstract
Most of the available how-to guides for working with OpenCV in Java require you to have an insane amount of knowledge before getting started. The good news for you is that with what you have learned up to now with this book, you can get started with OpenCV in Java in seconds.
Nicolas Modrzyk
Chapter 3. Vision on Raspberry Pi 4
Abstract
In Chapters 1 and 2, you saw how to get up and running with computer vision using Java on a regular desktop computer. The setup was a bit manual, but all the different building blocks were freely available, so it was just a matter of putting those blocks together.
Nicolas Modrzyk
Chapter 4. Analyzing Video Streams on the Raspberry Pi
Abstract
In this chapter, you’ll learn how to analyze video streams using concepts taken from functional programming. Specifically, you’ll use the Filter interface and combine it with a Pipeline object and then apply them to the video stream.
Nicolas Modrzyk
Chapter 5. Vision and Home Automation
Abstract
The first four chapters of this book showed you how to bring in video streams of all sorts and analyze them first on a computer and then on the small limited device that is the Raspberry Pi.
Nicolas Modrzyk
Backmatter
Metadata
Title
Real-Time IoT Imaging with Deep Neural Networks
Author
Nicolas Modrzyk
Copyright Year
2020
Publisher
Apress
Electronic ISBN
978-1-4842-5722-7
Print ISBN
978-1-4842-5721-0
DOI
https://doi.org/10.1007/978-1-4842-5722-7

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