DOCSLIB.ORG

Raspberry Pi Computer Vision Programming – Second Edition Programming – Second Edition

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Raspberry Pi Computer Vision Programming – Second Edition Programming – Second Edition Raspberry Pi Computer Vision Pajankar Ashwin Edition Second – Programming Vision Computer Pi Raspberry Programming – Second Edition Raspberry Pi is one of the popular on Raspberry Pi, before covering major Raspberry Pi single-board computers of our generation. techniques and algorithms in image All the major image processing and computer processing, manipulation, and computer vision algorithms and operations can be vision. By sequentially working through the implemented easily with OpenCV on steps in each chapter, you'll understand Computer Vision Raspberry Pi. This updated second edition is essential OpenCV features. Later sections packed with cutting-edge examples and new will take you through creating graphical user topics, and covers the latest versions of key interface (GUI) apps with GPIO and OpenCV. technologies such as Python 3, Raspberry Pi, You'll also learn how to use the new computer Programming and OpenCV. This book will equip you with vision library, Mahotas, to perform various the skills required to successfully design and image processing operations. Finally, you'll implement your own OpenCV, Raspberry Pi, explore the Jupyter notebook and how to and Python-based computer vision projects. set up a Windows computer and Ubuntu for computer vision. Second Edition At the start, you'll learn the basics of Python 3, and the fundamentals of single-board By the end of this book, you'll be able to computers and NumPy. Next, you'll discover confi dently build and deploy computer how to install OpenCV 4 for Python 3 vision apps. Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3 Things you will learn: • Set up a Raspberry Pi for computer • Implement low-pass and high-pass vision applications fi lters and understand their applications in image processing • Perform basic image processing with libraries such as NumPy, Matplotlib, • Cover advanced techniques such as and OpenCV histogram equalization and morphological transformations • Demonstrate arithmetical, logical, and other operations on images • Create GUI apps with Python 3 and OpenCV • Work with a USB webcam and the Raspberry Pi Camera Module • Perform machine learning with K-means clustering and image quantization www.packt.com www.packt.com Ashwin Pajankar Raspberry Pi Computer Vision Programming Second Edition Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3 Ashwin Pajankar BIRMINGHAM—MUMBAI Raspberry Pi Computer Vision Programming Second Edition Copyright © 2020 Packt Publishing All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews. Every efort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book. Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information. Commissioning Editor: Sunith Shetty Acquisition Editor: Reshma Raman Senior Editor: Ayaan Hoda Content Development Editor: Nazia Shaikh Technical Editor: Utkarsha S. Kadam Copy Editor: Safs Editing Project Coordinator: Aishwarya Mohan Proofreader: Safs Editing Indexer: Rekha Nair Production Designer: Joshua Misquitta First published: May 2015 Second edition: June 2020 Production reference: 1260620 Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK. ISBN 978-1-80020-721-9 www.packt.com Packt.com Subscribe to our online digital library for full access to over 7,000 books and videos, as well as industry leading tools to help you plan your personal development and advance your career. For more information, please visit our website. Why subscribe? • Spend less time learning and more time coding with practical eBooks and Videos from over 4,000 industry professionals • Improve your learning with Skill Plans built especially for you • Get a free eBook or video every month • Fully searchable for easy access to vital information • Copy and paste, print, and bookmark content Did you know that Packt ofers eBook versions of every book published, with PDF and ePub fles available? You can upgrade to the eBook version at packt.com and as a print book customer, you are entitled to a discount on the eBook copy. Get in touch with us at [email protected] for more details. At www.packt.com, you can also read a collection of free technical articles, sign up for a range of free newsletters, and receive exclusive discounts and ofers on Packt books and eBooks. Contributors About the author Ashwin Pajankar is a polymath. He is a science popularizer, a programmer, a maker, an author, and a YouTuber. He graduated from IIIT Hyderabad with an MTech in computer science and engineering. He has a keen interest in the promotion of science, technology, engineering, and mathematics (STEM) education. About the reviewers Lentin Joseph is an author, roboticist, and robotics entrepreneur from India. He runs a robotics sofware company called Qbotics Labs in Kochi/Kerala. He has 10 years of experience in the robotics domain, primarily working with the Robot Operating System (ROS), OpenCV, and PCL. He has authored several books on ROS, namely Learning Robotics Using Python First Edition and Second Edition, Mastering ROS for Robotics Programming First Edition and Second Edition, ROS Robotics Projects First Edition and Second Edition, and Robot Operating System for Absolute Beginners. He has masters in Robotics and Automation from Amrita Vishwa Vidapeetham University in India and also worked at the Robotics Institute, CMU, USA. He is also a TEDx speaker. Arush Kakkar is an author, entrepreneur, and a computer vision and deep learning researcher. He is currently the CEO of Agrex.ai, a company started by him. It's a video analytics company utilizing Artifcial Intelligence to analyze human behavior. Te applications include analyzing customer behavior in retail stores, security threats in sensitive installations, thermal vision processing, face recognition, and improving operational efciency. He has authored two books Raspberry Pi By Example and Raspberry Pi: Amazing Products from Scratch both published by Packt Publishing. Arush has extensive experience in using Raspberry Pi to build products that use computer vision to accomplish certain tasks. Packt is searching for authors like you If you're interested in becoming an author for Packt, please visit authors. packtpub.com and apply today. We have worked with thousands of developers and tech professionals, just like you, to help them share their insight with the global tech community. You can make a general application, apply for a specifc hot topic that we are recruiting an author for, or submit your own idea. Table of Contents Preface 1 Introduction to Computer Vision and the Raspberry Pi Understanding computer vision 2 Setting up Raspbian on a OpenCV 3 Raspberry Pi 14 Downloading the necessary software 20 Single-board computers 4 Preparing the microSD card manually 23 The Beagleboard family 6 Booting up the Raspberry Pi for the ASUS Tinkerboard 6 frst time 26 NVIDIA Jetson 7 Connecting various RPi board models Intel boards 7 to the internet 34 Raspberry Pi 8 Updating the RPi 37 Raspberry Pi models 8 Summary 38 OSes for Raspberry Pi 13 2 Preparing the Raspberry Pi for Computer Vision Remotely logging into the RPi Installing OpenCV on an RPi with SSH 40 board 46 Remote desktop access 44 Heatsinks and overclocking RPi 4B 47 Summary 49 ii Table of Contents 3 Introduction to Python Programming Technical requirements 52 The basics of NumPy 62 Understanding Python 3 52 Matplotlib 65 Python on RPi and Raspberry Pi OS 53 RPi GPIO programming with Python 3 IDEs on Raspberry Pi OS 54 Python 3 71 Working with Python 3 in interactive LED programming with GPIO 72 mode 59 Push-button programming with GPIO 80 The basics of Python 3 programming 59 Summary 83 The SciPy ecosystem 62 4 Getting Started with Computer Vision Technical requirements 86 Webcam video recording 103 Exploring image datasets 86 Capturing images with the webcam using Python and OpenCV 103 Working with images using Live videos with the webcam using OpenCV 86 Python and OpenCV 104 Using matplotlib to visualize Webcam resolution 105 images 89 FPS of the webcam 106 Drawing geometric shapes with Saving webcam videos 107 OpenCV and NumPy 92 Playing back the video with OpenCV 109 Working with a GUI 95 The Pi camera module 110 Event handling and a primitive Capturing images and videos with the paint application 96 raspistill and raspivid utilities 112 Working with a USB webcam 99 Using picamera with Python 3 113 Capturing images with the webcam 100 Using the RPi camera module and Timelapse photography 100 Python 3 to record videos 116 Summary 116 Table of Contents iii 5 Basics of Image Processing Technical requirements 118 Blending and transitioning Retrieving image properties 118 images 126 Basic operations on images 120 Multiplying images by a Splitting the image into channels 121 constant and one another 130 Adding a
Load more

Recommended publications
  • Cubietruck – Mini PC
    SPRZĘT Cubietruck – mini PC Rynek komputerków jednopłytkowych opartych o procesory ARM zapoczątkowany przez Raspberry Pi rozwija się doskonale. Może nie jak grzyby po deszczu, ale systematycznie pojawiają się nowe rozwiązania: BeagleBoard, Marsboard, Cubieboard, Olinuxino itp. Różnią się one wyposażeniem, wydajnością, dostępnością dokumentacji oraz wsparciem technicznym. Ciekawie rozwija się propozycja Cubieboard. mocujących. Niby nic, ale te trzy kawałki two- org, zapoczątkowana płytką Cubieboard A10 rzywa i paczka tulejek umożliwiają poskładanie Fotografi a 3. Obudowa Cubietruck (opisaną w EP06/2013) i Cubieboard2 zgod- samodzielnego systemu mini-PC wyposażo- ną mechanicznie, ale zbudowaną w oparciu nego w dysk HDD 2,5”, wystarczająco zabez- rolę domowego centrum multimedialnego lub o nowszy, dwurdzeniowy procesor A20, zwięk- pieczając mechanicznie jego elementy. Osłony Linuxowego komputera PC. Jedyne zastrzeżenie szający wydajność Cubie i paletę jej zastosowań w odpowiednich miejscach mają wyfrezowane można mieć do kilku różnokolorowych LED, (fotografi a 1). Najnowsza propozycja to Cubie- otwory umożliwiające korzystanie z GPIO bez bezlitośnie informujących nasze oczy o stanie truck (Cubieboard3), oparty podobnie jak Cu- zdejmowania obudowy. pracy Cubie. bieboard2 (fotografi a 2) o procesor Allwinner Ciekawą propozycją dla osób wykorzy- Cubieboard3 oparty jest o SoC w architektu- A20, lecz mający znacznie bogatsze wyposaże- stujących Cubieboard3 w roli samodzielnego rze ARM7 – Allwinner A20, który w połączeniu nie, co niestety wiąże się z wyższą ceną. Porów- mini-PC, jest pełna obudowa pokazana na fo- ze sporej wielkości dyskiem NAND Flash oraz nanie parametrów poszczególnych komputer- tografi i 3. W swoim wnętrzu mieści swobodnie zwiększoną pamięcią RAM bezproblemowo ków Cubieboard umieszczono w tabeli 1. płytkę Cubieboard3, dysk HDD 2,5” (fotogra- sprawdza się w roli komputera PC pracującego Podobnie jak w przypadku poprzednich fi a 4) i przewody połączeniowe.
    [Show full text]
  • Ultra-Mobile Pcs Where Do They Fit In?
    Ultra-Mobile PCs Where do they fit in? Eric White University of Wisconsin Survey Center International Field Directors and Technologies Conference May, 2009 University of Wisconsin Survey Center www.uwsc.wisc.edu Introduction • What are Ultra-Mobile PCs? • Technical specifications and capabilities • Usability for field data collection • Other uses • Future University of Wisconsin Survey Center What are we talking about? • Netbook? Subnotebook? UMPC? • 5 – 10 inch screen • Keyboard and touchpad • No CD/DVD drive • Lightweight (3 pounds or less) • $300 - $400 Lenovo s10 Asus eee pc Dell Inspiron Mini 9 University of Wisconsin Survey Center Tech Specs OS Windows XP (small Linux contingent) Processor Intel Atom, 1.6GHz Memory 1 – 2 GB SDRAM Hard Drive 16GB solid state or 160GB traditional Display 1024x600 Graphics Integrated Battery 6 cell Li-ion (5 hours) Networking 802.11b/g/n and ethernet Ports USB 2.0, VGA, audio jacks Camera 1.3M pixel Microphone Built-in University of Wisconsin Survey Center In the field? • Not in use • Interviewer concerns • UWSC concerns University of Wisconsin Survey Center Concerns • Interviewer Concerns • Laptop body is too small • Questioned laptop’s ruggedness • Slight concern over keyboard size • UWSC Concerns • Screen size and keyboard size might pose problems for respondents University of Wisconsin Survey Center Current UWSC Laptops in field • Lenovo X60 tablets • 12” screen, 4 lbs • Convertible to tablet • Lenovo R400 • 14” screen, 5 lbs. • Very rugged • Popular with interviewers • Full size keyboards • Much
    [Show full text]
  • Development Boards This Product Is Rohs Compliant
    Development Boards This product is RoHS compliant. PANDABOARD DEVELOPMENT PLATFORM Features: • Core Logic: OMAP4460 applications Processor • Interface: (1) General Purpose Expansion Header • Wireless Connectivity: 802.11 b/g/n (WiLink™ 6.0) • Memory: 1GB DDR2 RAM (I2C, GPMC, USB, MMC, DSS, ETM) • Debug options: JTAG, UART/RS-232, 1 GPIO button NTL • Full Size SD/MMC card port • Camera Expansion Header • Graphics APIs: OpenGL ES v2.0, OpenGL ES v1.1, • 10/100 Ethernet • Display Connectors: HDMI v1.3, DVI-D. LCD Expansion OpenVGv1.1, and EGL v1.3 • USB: (1) USB 2.0 OTG port, (2) USB 2.0 High-speed port • Audio Connectors: 3.5" In/Out, HDMI audio out For quantities greater than listed, call for quote. MOUSER Pandaboard Price Description STOCK NO. Part No. Each 595-PANDABOARD UEVM4430G-01-00-00 Pandaboard ARM Cortex-A9 MPCore 1GHz OMAP4430 SoC Platform 179.00 595-PANDABOARD-ES UEVM4460G-02-01-00 Pandaboard ARM Cortex-A9 MPCore 1GHz OMAP4460 SoC Platform 185.00 Embedded Modules Embedded BEAGLEBOARD SOC PLATFORMS BeagleBoard.org develops low-cost, fan-less single-board computers based on low-power Texas Instruments processors featuring the ARM Cortex-A8 core with all of the expandability of today's desktop machines, but without the bulk, expense, or noise. BeagleBoard.org provides an open source development platform for A B the creation of high-performance embedded designs. Beagleboard C4 Features: Beagleboard xM Features: Beaglebone Features: • Over 1,200 Dhrystone MIPS using the superscalar • Over 2,000 Dhrystone MIPS using the Super-scalar
    [Show full text]
  • Performance Analysis and Optimization Opportunities for NVIDIA Automotive Gpus
    Performance Analysis and Optimization Opportunities for NVIDIA Automotive GPUs Hamid Tabani∗, Fabio Mazzocchetti∗y, Pedro Benedicte∗y, Jaume Abella∗ and Francisco J. Cazorla∗ ∗ Barcelona Supercomputing Center y Universitat Politecnica` de Catalunya Abstract—Advanced Driver Assistance Systems (ADAS) and products such as Renesas R-Car H3 [1], NVIDIA Jetson Autonomous Driving (AD) bring unprecedented performance TX2 [20] and NVIDIA Jetson Xavier [35], [27] have already requirements for automotive systems. Graphic Processing Unit reached the market building upon GPU technology inherited (GPU) based platforms have been deployed with the aim of meeting these requirements, being NVIDIA Jetson TX2 and from the high-performance domain. Automotive GPUs have its high-performance successor, NVIDIA AGX Xavier, relevant inherited designs devised for the high-performance domain representatives. However, to what extent high-performance GPU with the aim of reducing costs in the design, verification and configurations are appropriate for ADAS and AD workloads validation process for chip manufacturers. remains as an open question. Unfortunately, reusability of high-performance hardware This paper analyzes this concern and provides valuable does not consider GPUs efficiency in the automotive domain insights on this question by modeling two recent automotive NVIDIA GPU-based platforms, namely TX2 and AGX Xavier. In and, to the best of our knowledge, the design space for GPUs, particular, our work assesses their microarchitectural parameters where resources are sized with the aim of optimizing specific against relevant benchmarks, identifying GPU setups delivering goals such as performance, has not been yet thoroughly increased performance within a similar cost envelope, or decreas- performed for the automotive domain. ing hardware costs while preserving original performance levels.
    [Show full text]
  • A Low-Cost Deep Neural Network-Based Autonomous Car
    DeepPicar: A Low-cost Deep Neural Network-based Autonomous Car Michael G. Bechtely, Elise McEllhineyy, Minje Kim?, Heechul Yuny y University of Kansas, USA. fmbechtel, elisemmc, [email protected] ? Indiana University, USA. [email protected] Abstract—We present DeepPicar, a low-cost deep neural net- task may be directly linked to the safety of the vehicle. This work based autonomous car platform. DeepPicar is a small scale requires a high computing capacity as well as the means to replication of a real self-driving car called DAVE-2 by NVIDIA. guaranteeing the timings. On the other hand, the computing DAVE-2 uses a deep convolutional neural network (CNN), which takes images from a front-facing camera as input and produces hardware platform must also satisfy cost, size, weight, and car steering angles as output. DeepPicar uses the same net- power constraints, which require a highly efficient computing work architecture—9 layers, 27 million connections and 250K platform. These two conflicting requirements complicate the parameters—and can drive itself in real-time using a web camera platform selection process as observed in [25]. and a Raspberry Pi 3 quad-core platform. Using DeepPicar, we To understand what kind of computing hardware is needed analyze the Pi 3’s computing capabilities to support end-to-end deep learning based real-time control of autonomous vehicles. for AI workloads, we need a testbed and realistic workloads. We also systematically compare other contemporary embedded While using a real car-based testbed would be most ideal, it computing platforms using the DeepPicar’s CNN-based real-time is not only highly expensive, but also poses serious safety control workload.
    [Show full text]
  • Openbricks Embedded Linux Framework - User Manual I
    OpenBricks Embedded Linux Framework - User Manual i OpenBricks Embedded Linux Framework - User Manual OpenBricks Embedded Linux Framework - User Manual ii Contents 1 OpenBricks Introduction 1 1.1 What is it ?......................................................1 1.2 Who is it for ?.....................................................1 1.3 Which hardware is supported ?............................................1 1.4 What does the software offer ?............................................1 1.5 Who’s using it ?....................................................1 2 List of supported features 2 2.1 Key Features.....................................................2 2.2 Applicative Toolkits..................................................2 2.3 Graphic Extensions..................................................2 2.4 Video Extensions...................................................3 2.5 Audio Extensions...................................................3 2.6 Media Players.....................................................3 2.7 Key Audio/Video Profiles...............................................3 2.8 Networking Features.................................................3 2.9 Supported Filesystems................................................4 2.10 Toolchain Features..................................................4 3 OpenBricks Supported Platforms 5 3.1 Supported Hardware Architectures..........................................5 3.2 Available Platforms..................................................5 3.3 Certified Platforms..................................................7
    [Show full text]
  • Cubieboard Cubieboard2 Cubietruck Beaglebone Black
    Raspberry Pi (Model B rev.2) Cubieboard Cubieboard2 Cubietruck Beaglebone Black 1 Ghz (OC) ARM® Cortex-A6 1 Ghz ARM® Cortex-A8 1 Ghz ARM® Cortex-A7 Dual Core 1 Ghz ARM® Cortex-A7 Dual Core 1 Ghz ARM® Cortex-A8 CPU ARM1176JZF-F Allwinner A10 C8096CA Allwinner A20 Allwinner A20 AM335x GPU/FPU VideoCore IV Mali-400 (CedarX, OpenGL) Mali-400MP2 (CedarX, OpenGL) Mali-400MP2 (CedarX, OpenGL) SGX350 3D / NEON FPU accelerator RAM 512 MB 1 GB DDR3 2 GB 2 GB 512 MB DDR3 Storage micro SD/SDHC 4 GB NAND Flash, micro SD/SDHC, SATA 4 GB NAND Flash, micro SD/SDHC, SATA 4 GB NAND Flash, micro SD/SDHC, SATA 2.0 2GB eMMC Power micro USB (5V/1A) 3.5 W DC 5v/2A DC 5v/2A DC 5v/2.5A DC 5V/500mA Video RCA Composite Video, HDMI 1.4 HDMI HDMI HDMI/VGA microHDMI Audio 3.5 mm Headphone Jack 3.5 mm Headphone Jack / Line In 3.5 mm Headphone Jack 3.5 mm Headphone Jack, SPDIF Network 10/100 Mbps 10/100 Mbps 10/100 Mbps 10/100/1000 Mbps, Wifi, Bluetooth 10/100 Mbps 2x46 PIN GPIO I/O ports 26 PIN GPIO, 2x Ribon 2x48 PIN GPIO, 4PIN Serial, 1IR 2x48 PIN GPIO, 4PIN Serial, 1IR 1x 54 PIN GPIO (Arduino Shield Compatible) USB ports 2x USB 2.0 2x USB 2.0 2x USB 2.0, 1 mini USB OTG 2x USB 2.0, 1 mini USB OTG 1x USB 2.0 Linux (Raspbian, Debian, Fedora, Arch, Gentoo, Kali), Andoid, Angstrom, Ubuntu, Fedora, Gentoo.
    [Show full text]
  • Procurement of Electric-Electronic
    REQUEST FOR QUOTATION (RFQ) Procurement of Electric-Electronic Laboratory Equipment and Supplies for Adana and Mersin Innovation Centers Adana ve Mersin Yenilik Merkezleri için Elektrik-Elektronik Laboratuvarları Ekipman ve Sarf Malzemeleri Alım İhalesi Please enter Name, Address & Contact Details of your Firm DATE: February 10, 2020 Lütfen Firma Adı, Adresi ve İrtibat Bilgilerini buraya giriniz TARİH: 10 Şubat 2020 REFERENCE: UNDP-TUR-RFQ(MC1)-2020/07 Dear Sir / Madam: Sayın İlgili: We kindly request you to submit your Teklife Davet Ek 1’deki Teknik Şartnamede ve Ek quotation for “Procurement of Electric-Electronic 2’de yer alan Malzeme Listesi’nde detayları verilmiş Laboratory Equipment and Supplies for Adana and olan “Adana ve Mersin Yenilik Merkezleri için Mersin Innovation Centers”, as detailed in Technical Elektrik-Elektronik Laboratuvarları Ekipman ve Sarf Specifications and Supplies List provided as Annex Malzemeleri Alım İhalesi” için teklifinizi sunmanızı 1 and Annex 2 (respectively) of this RFQ. When rica ederiz. preparing your quotation, please be guided by the forms attached hereto as ANNEX 1, ANNEX 2 and Teklifinizi lütfen EK 1, EK 2 ve EK 3’de sunulmuş ANNEX 3. formların rehberliğinde hazırlayınız. Quotations shall be submitted on or before 27 Teklifler aşağıda belirtilen adrese, 27 Şubat 2020, February 2020, 14:00 hrs. Turkey Local Time, via Türkiye saati ile 14:00’a kadar elden, e-posta veya hand delivery, e-mail or courier mail to the address kargo yolu ile teslim edilmelidir: below: United Nations Development Programme Birleşmiş Milletler Kalkınma Programı (UNDP) (UNDP) Yıldız Kule, Yukarı Dikmen Mahallesi, Turan Güneş Yıldız Kule, Yukarı Dikmen Mahallesi, Turan Bulvarı, No:106, 06550, Çankaya, Ankara/Türkiye Güneş Bulvarı, No:106, 06550, Çankaya, İlgili Kişi: Ümit ALSAÇ Ankara/Turkey Satın Alma Yetkilisi, UNDP Attn: Mr.
    [Show full text]
  • WLAN Hacking Workshop
    WLAN Hacking Workshop Oz Krakowski – [email protected] Luciano Coelho – [email protected] Agenda What is “OpenLink™”? Workshop intro Board setup Getting WLAN to work on BeagleBoard The OpenLink Challenge Wrap-up – Demo – Ubuntu – Prizes – What’s next What is “OpenLink™”? An open source initiative Wireless connectivity technologies – Wi-Fi™ – Bluetooth® – FM – Roadmap: • Bluetooth Low Energy • ANT • Zigbee® • NFC What is “OpenLink™”? Open link drivers available today Part of mainline Linux kernel Easily attach to open source development platform such as BeagleBoard and PandaBoard What is “OpenLink™”? Website – OpenLink.org – Community – News – Projects – Support – Platforms – Resources … And more to come… Workshop Outline Short hands-on demo Learn how to connect to an AP from the CLI Your chance to get your own BeagleBoard with a WLAN daughter card! Board Setup Pre-requisite: minicom (or another terminal app) Insert the micro-SD card Connect the USB-serial adapter Connect the USB cable (power supply) Serial Console Start minicom – minicom -s -o • /dev/ttyUSB0 • 115200 8N1 • No HW/SW flow control Log in to the serial console • user: root • pwd: rootguri BeagleBoard boot basics Two-phase boot – X-Loader (MLO) – u-boot.bin • Environment setup • Kernel parameters Kernel – Mainline-based (2.6.39-rc1) – One patch for the WLAN daughtercard Connecting to an open Access Point Set your own MAC address ifconfig wlan0 hw ether 08:00:28:00:00:<number> ifconfig wlan0 up Using the iw tool to scan iw wlan0 scan Connecting to an open AP iw wlan0 connect
    [Show full text]
  • NVIDIA Jetson TX2 Module
    ® ™ NVIDIA JETSON TX2 SUPERCOMPUTER ON A MODULE FOR AI AT THE EDGE TAKE REAL-TIME AI PERFORMANCE FARTHER WITH THE HIGH-PERFORMANCE, LOW-POWER JETSON TX2. The most innovative technology for AI computing and visual computing comes in a supercomputer the size of a credit card. Its small form factor and power envelope make the Jetson TX2 module ideal for intelligent edge devices like robots, drones, smart cameras, and portable medical devices. CONTENTS Jetson TX2 features a variety of standard hardware interfaces that make it easy to integrate it into a wide range of products and form factors. Plus, it comes with the complete Jetpack > NVIDIA Jetson TX2 > Attached Thermal Transfer Plate (TTP) SDK, which includes the BSP, libraries for deep learning, computer vision, GPU computing, multimedia processing, and much more to accelerate your software development. And it’s TECHNICAL SPECIFICATIONS supported by the Jetson developer site, which includes documentation, tutorials, and an FEATURES JETSON TX2 ecosystem of partners and developers. It’s never been easier to get started with AI. Graphics NVIDIA Pascal™, 256 NVIDIA For detailed specifications, design guides, Jetpack, and everything else you need to develop CUDA® cores with Jetson, go to developer.nvidia.com/embedded-computing. CPU HMP Dual Denver 2/2MB L2 + Quad ARM® A57/2MB L2 KEY FEATURES Video 4K x 2K 60 Hz Encode (HEVC) 4K x 2K 60 Hz Decode (12-bit Jetson TX2 Module I/O support) > NVIDIA Pascal™ architecture GPU > USB 3.0 Type A Memory 8 GB 128-bit LPDDR4 > Dual-core Denver 2 64-bit CPU
    [Show full text]
  • Jetson TX2 Developer Kit User Guide
    JETSON TX2 DEVELOPER KIT DA_09452-005 | December 17, 2019 ````` User Guide DOCUMENT CHANGE HISTORY DA_09452-005 Version Date Authors Description of Change Revision for Jetson Linux Driver 2.0 March 28, 2019 jsachs, plawrence Package r32.1. Revision for SDK Manager and Jetson 3.0 July 8, 2019 jsachs, plawrence Linux Driver Package r32.2. Revision for Jetson Linux Driver 4.0 December 17, 2019 ssheshadri Package r32.3.1. NOTE Welcome to the NVIDIA Jetson platform! There two key things you should do right away: 1. Sign up for the NVIDIA Developer Program – this enables you to ask questions and contribute on the NVIDIA Jetson Forums, gives access to all documentation and collateral on the Jetson Download Center, and more. 2. Read this User Guide! After that, check out these important links: • Jetson FAQ – Please read the FAQ. • Support Resources – This web page links to important resources, including the Jetson Forum and the Jetson Ecosystem page. • Jetson Linux Driver Package Release Notes – Jetson Linux Driver Package (L4T) is a key component of the Jetson platform, and provides the sample filesystem for your developer kit. Please read the latest release notes. • Thanks, The NVIDIA Jetson team Jetson TX2 Developer Kit DA_09452-005 | ii TABLE OF CONTENTS Note .........................................................................................ii Jetson TX2 Developer Kit ............................................................... 1 Included in the box ............................................................................. 1 Developer
    [Show full text]
  • Debian GNU/Linux Installation Guide
    Debian GNU/Linux Installation Guide July 31, 2021 Debian GNU/Linux Installation Guide Copyright © 2004 – 2021 the Debian Installer team This manual is free software; you may redistribute it and/or modify it under the terms of the GNU General Public License. Please refer to the license in Appendix F. Build version of this manual: 20210730. i Contents 1 Welcome to Debian 1 1.1 What is Debian? . 1 1.2 What is GNU/Linux? . 1 1.3 What is Debian GNU/Linux? . 2 1.4 What is the Debian Installer? . 3 1.5 Getting Debian . 3 1.6 Getting the Newest Version of This Document . 3 1.7 Organization of This Document . 3 1.8 About Copyrights and Software Licenses . 4 2 System Requirements 5 2.1 Supported Hardware . 5 2.1.1 Supported Architectures . 5 2.1.2 Three different ARM ports . 6 2.1.3 Variations in ARM CPU designs and support complexity . 6 2.1.4 Platforms supported by Debian/armhf . 6 2.1.5 Platforms no longer supported by Debian/armhf . 8 2.1.6 Multiple Processors . 8 2.1.7 Graphics Hardware Support . 8 2.1.8 Network Connectivity Hardware . 8 2.1.9 Peripherals and Other Hardware . 8 2.2 Devices Requiring Firmware . 8 2.3 Purchasing Hardware Specifically for GNU/Linux . 9 2.3.1 Avoid Proprietary or Closed Hardware . 9 2.4 Installation Media . 9 2.4.1 CD-ROM/DVD-ROM/BD-ROM . 9 2.4.2 Network . 10 2.4.3 Hard Disk . 10 2.4.4 Un*x or GNU system .
    [Show full text]