Real-Time Iot Imaging with Deep Neural Networks: Using Java on the Raspberry Pi 4
暫譯: 即時物聯網影像處理與深度神經網絡:在 Raspberry Pi 4 上使用 Java
Modrzyk, Nicolas
- 出版商: Apress
- 出版日期: 2020-03-11
- 售價: $1,520
- 貴賓價: 9.5 折 $1,444
- 語言: 英文
- 頁數: 224
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1484257219
- ISBN-13: 9781484257210
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相關分類:
Java 程式語言、Raspberry Pi、物聯網 IoT
海外代購書籍(需單獨結帳)
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商品描述
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 filters
- Execute a YOLO DNN model for image detection
- Apply the best Java scripting on Raspberry Pi 4
- Prepare your setup for real-time remote programming
- Use 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
商品描述(中文翻譯)
這本書教你如何構建從即時影像處理系統到家庭自動化的完整系統。了解如何開發基於小型 32 位元 ARM 處理器的系統,讓你能夠透過語音指令完全控制。
即時影像處理系統被廣泛應用於各種應用中,例如交通監控系統、醫療影像處理和生物識別安全系統。在《Real-Time IoT Imaging with Deep Neural Networks》中,你將學習如何利用最佳的深度神經網絡(DNN)模型來使用 Java 和 OpenCV 的包裝器檢測影像中的物體。深入了解 Java 腳本在 Raspberry Pi 上的運作,同時為遠端編程準備你的 Visual Studio Code。你還將獲得影像和視頻腳本的見解。作者 Nicolas Modrzyk 向你展示如何使用 Rhasspy 語音平台來添加強大的語音助手,並完全從你的電腦上運行和控制你的 Raspberry Pi。
為了準備你的家庭自動化語音意圖,你將探索 Java 如何連接到 MQTT 並處理參數化的 Rhasspy 語音指令。當你的語音控制系統準備好運行時,你將能夠在選定的環境中執行簡單的任務,例如檢測貓、人物和咖啡壺。隱私和自由至關重要,因此優先考慮使用開源軟體和設備上的語音環境,讓你完全控制自己的數據和視頻流。你的語音指令是你自己的——而且僅僅是你自己的。
隨著物聯網和機器學習的最新進展,尖端的影像處理系統提供了完整的過程自動化。這本實用的書教你如何構建這樣的系統,讓你以最小的努力獲得完全的控制。
你將學到的內容:
- 通過創建 OpenCV 濾鏡來展示你的精通
- 執行 YOLO DNN 模型進行影像檢測
- 在 Raspberry Pi 4 上應用最佳的 Java 腳本
- 為即時遠端編程準備你的設置
- 使用 Rhasspy 語音平台處理語音指令並增強你的家庭自動化設置
這本書適合的對象:工程師和希望使用他們喜愛的 JVM 在 Raspberry Pi 上運行物體檢測和網絡的愛好者。
作者簡介
Nicolas Modrzyk has over 15 years of IT experience in Asia, Europe, and the United States. He is currently the CTO of an international consulting company in Tokyo, Japan. An author of four other published books, he mostly focuses on the Clojure language and expressive code. When not bringing new ideas to customers, he spends time with his two fantastic daughters Mei and Manon, and playing live music internationally.
作者簡介(中文翻譯)
尼古拉斯·莫德日克(Nicolas Modrzyk)在亞洲、歐洲和美國擁有超過15年的IT經驗。他目前是位於日本東京的一家國際顧問公司的首席技術官(CTO)。作為四本已出版書籍的作者,他主要專注於Clojure語言和表達性程式碼。當他不在為客戶帶來新想法時,他會花時間陪伴他的兩位出色女兒梅(Mei)和馬農(Manon),並在國際上演奏現場音樂。