Real-Time IoT Imaging with Deep Neural Networks - Using Java on the Raspberry Pi 4

Table of Contents
About the Author
About the Technical Reviewer
Acknowledgments
Introduction
Chapter 1: Getting Started
	Visual Studio Code Primer
	Running Your First Java Application
	Importing Core Java Packages
	Debugging Lesson
		Add a Breakpoint
		Execute the Code Step-by-Step
		Resume Execution
		Watch an Expression
		Change a Variable Value
		Wrapping Things Up
Chapter 2: Object Detection in Video Streams
	Going Sepia: OpenCV Java Primer
		A Few Files to Make Things Easier…
	OpenCV Primer 2: Loading, Resizing, and Adding Pictures
		Simple Addition
		Weighted Addition
	Back to Sepia
	Finding Marcel: Detecting Objects Primer
		Finding Cat Faces in Pictures Using a Classifier
			What Is a Feature?
			Where in the World Is Marcel?
		Finding Cat Faces in Pictures Using the Yolo Neural Network
Chapter 3: Vision on Raspberry Pi 4
	Bringing the Raspberry to Life
		Shopping
		Downloading the OS
		Creating the Bootable SD Card
		Connecting the Cables
		First Boot
		Finding Your Raspberry Using nmap
		Setting Up SSH Easily
	Setting Up Visual Code Studio for Remote Use
		Setting Up the Java OpenJDK
		Alternative to Setting Up the Java SDK
		Checking Out the OpenCV/Java Template
			Performing a Git Clone
			Downloading the Zip File
			Using Maven
		Installing the Visual Code Java Extension Pack Remotely
		Running the First OpenCV Example
	Running on Linux or a VM with AWS Instead
	Capturing a Video Live Stream
	Playing a Video
Chapter 4: Analyzing Video Streams on the Raspberry Pi
	Overview of Applying Filters
	Applying Basic Filters
		Gray Filter
		Edge Preserving Filter
		Canny
		Debugging (Again)
		Combining Filters
	Applying Instagram-like Filters
		Color Map
		Thresh
		Sepia
		Cartoon
		Pencil Effect
	Performing Object Detection
		Removing the Background
		Detecting by Contours
		Detecting by Color
		Detecting by Haar
		Transparent Overlay on Detection
		Detecting by Template Matching
		Detecting by Yolo
Chapter 5: Vision and Home Automation
	Rhasspy Message Flow
	MQTT Message Queues
		Installing Mosquitto
		Comparison of Other MQTT Brokers
		MQTT Messages on the Command Line
	MQTT Messaging in Java
		Dependencies Setup
		Sending a Basic MQTT Message
		Simulating a Rhasspy Message
		JSON Fun
		Listening to MQTT Basic Messages
		Listening to MQTT JSON Messages
	Voice and Rhasspy Setup
		Preparing the Speaker
		Installing Docker
		Installing Rhasspy with Docker
		Starting the Rhasspy Console
		The Rhasspy Console
		First Voice Command
			First Command, Full Sentence
			Speech Section and Trying Your Intent
			Fine-Tuned Intents
				Optional Words
				Adding Alternatives
				Making Intents with Slots More Readable
				Defining Reusable Slots
		Settings: Get That Intent in the Queue
		Settings: Wake-Up Word
		Creating the Highlight Intent
	Voice and Real-Time Object Detection
		Simple Setup: Origami + Voice
		Origami Real-Time Video Analysis Setup
			Creating the Yolo Filter
			Running the Video Analysis Alone
	Integrating with Voice
Index