Ashwin Pajankar – författare

Quickly learn how to automate unit testing of Python 3 code with Python 3 automation libraries, such as doctest, unittest, nose, nose2, and pytest. 

This book explores the important concepts in software testing and their implementation in Python 3 and shows you how to automate, organize, and execute unit tests for this language. This knowledge is often acquired by reading source code, manuals, and posting questions on community forums, which tends to be a slow and painful process.

Python Unit Test Automation will allow you to quickly ramp up your understanding of unit test libraries for Python 3 through the practical use of code examples and exercises. All of which makes this book a great resource for software developers and testers who want to get started with unit test automation in Python 3 and compare the differences with Python 2.

This short work is your must-have quick start guide to mastering the essential concepts of software testing in Python.

What You''ll Learn: Essential concepts in software testingVarious test automation libraries for Python, such as doctest, unittest, nose, nose2, and pytestTest-driven development and best practices for test automation in PythonCode examples and exercisesWho This Book Is For:Python developers, software testers, open source enthusiasts, and contributors to the Python community

Write your own Digital Image Processing programs with the use of pillow, scipy.ndimage, and matplotlib in Python 3 with Raspberry Pi 3 as the hardware platform. This concise quick-start guide provides working code examples and exercises. Learn how to interface Raspberry Pi with various image sensors.What You''ll LearnUnderstand Raspberry Pi concepts and setupUnderstand digital image processing conceptsStudy pillow, the friendly PIL forkExplore scipy.ndimage and matplotlibMaster use of the Pi camera and webcamWho This Book Is ForRaspberry Pi and IoT enthusiasts, digital image processing enthusiasts, Python and Open Source enthusiasts and professionals

Build an inexpensive cluster of multiple Raspberry Pi computers and install all the required libraries to write parallel and scientific programs in Python 3. This book covers setting up your Raspberry Pis, installing the necessary software, and making a cluster of multiple Pis. Once the cluster is built, its power has to be exploited by means of programs to run on it. So, Raspberry Pi Supercomputing and Scientific Programming teaches you to code the cluster with the MPI4PY library of Python 3. Along the way, you will learn the concepts of the Message Passing Interface (MPI) standards and will explore the fundamentals of parallel programming on your inexpensive cluster. This will make this book a great starting point for supercomputing enthusiasts who want to get started with parallel programming. The book finishes with details of symbolic mathematics and scientific and numerical programming in Python, using SymPi, SciPy, NumPy, and Matplotlib. You’ll see how to process signals and images, carry out calculations using linear algebra, and visualize your results, all using Python code. With the power of a Raspberry Pi supercomputer at your fingertips, data-intensive scientific programming becomes a reality at home.What You Will Learn  Discover the essentials of supercomputingBuild a low-cost cluster of Raspberry Pis at homeHarness the power of parallel programming and the Message Passing Interface (MPI)Use your Raspberry Pi for symbolic, numerical, and scientific programmingWho This Book Is ForPython 3 developers who seek the knowledge of parallel programming, Raspberry Pi enthusiasts, researchers, and the scientific Python community.

Build an inexpensive cluster of multiple Raspberry Pi computers and install all the required libraries to write parallel and scientific programs in Python 3. This book covers setting up your Raspberry Pis, installing the necessary software, and making a cluster of multiple Pis. Once the cluster is built, its power has to be exploited by means of programs to run on it. So, Raspberry Pi Supercomputing and Scientific Programming teaches you to code the cluster with the MPI4PY library of Python 3. Along the way, you will learn the concepts of the Message Passing Interface (MPI) standards and will explore the fundamentals of parallel programming on your inexpensive cluster. This will make this book a great starting point for supercomputing enthusiasts who want to get started with parallel programming. The book finishes with details of symbolic mathematics and scientific and numerical programming in Python, using SymPi, SciPy, NumPy, and Matplotlib. You’ll see how to process signals and images, carry out calculations using linear algebra, and visualize your results, all using Python code. With the power of a Raspberry Pi supercomputer at your fingertips, data-intensive scientific programming becomes a reality at home.What You Will Learn  Discover the essentials of supercomputingBuild a low-cost cluster of Raspberry Pis at homeHarness the power of parallel programming and the Message Passing Interface (MPI)Use your Raspberry Pi for symbolic, numerical, and scientific programmingWho This Book Is ForPython 3 developers who seek the knowledge of parallel programming, Raspberry Pi enthusiasts, researchers, and the scientific Python community.

Get a quick start to learn, understand, and apply GNU Octave using a math- and programming-friendly approach. This book focuses on an end-to-end track to teach mathematical programming, data science, signal processing, and image processing with GNU Octave.GNU Octave by Example starts with an introduction to GNU Octave, a free and open-source alternative to MATLAB. Next, it explains the processes to install GNU Octave on popular operating systems such as Windows, Ubuntu, Raspberry Pi, and other platforms. Further, it covers hands-on exercises with GNU Octave exploring the basic functionality and command line in interactive mode. This is followed by covering matrices and various operations including how to read and analyze data from various sources. Moving forward, it introduces commonly used programming constructs in data visualization. It explains 2D and 3D data visualization along with data analysis. It also demonstrates the concepts related to geometry and its application with GNU Octave. It concludes with coverage of signal processing followed by image, video, and audio processing techniques.After reading this book, you will be able to write your own programs for scientific and numerical applications.What You Will Learn  ●        Understand the practical aspects of GNU Octave with math and programming-friendly abstractions●        Install GNU Octave on multiple platforms including Windows, Raspberry Pi, and Ubuntu●        Work with GNU Octave using the GUI, the command line, and Jupyter notebooks●        Implement 2D and 3D data visualization and analysis with GNU OctaveWho This Book Is For Software engineers, data engineers, data science enthusiasts, and computer vision professionals.

Get a quick start to learn, understand, and apply GNU Octave using a math- and programming-friendly approach. This book focuses on an end-to-end track to teach mathematical programming, data science, signal processing, and image processing with GNU Octave.

GNU Octave by Example starts with an introduction to GNU Octave, a free and open-source alternative to MATLAB. Next, it explains the processes to install GNU Octave on popular operating systems such as Windows, Ubuntu, Raspberry Pi, and other platforms. Further, it covers hands-on exercises with GNU Octave exploring the basic functionality and command line in interactive mode. This is followed by covering matrices and various operations including how to read and analyze data from various sources. Moving forward, it introduces commonly used programming constructs in data visualization. It explains 2D and 3D data visualization along with data analysis. It also demonstrates the concepts related to geometry and its application with GNU Octave. It concludes with coverage of signal processing followed by image, video, and audio processing techniques.

After reading this book, you will be able to write your own programs for scientific and numerical applications.

What You Will Learn  

●        Understand the practical aspects of GNU Octave with math and programming-friendly abstractions

●        Install GNU Octave on multiple platforms including Windows, Raspberry Pi, and Ubuntu

●        Work with GNU Octave using the GUI, the command line, and Jupyter notebooks

●        Implement 2D and 3D data visualization and analysis with GNU Octave

Who This Book Is For

Software engineers, data engineers, data science enthusiasts, and computer vision professionals.

Quickly start programming with Python 3 for data visualization with this step-by-step, detailed guide. This book’s programming-friendly approach using libraries such as leather, NumPy, Matplotlib, and Pandas will serve as a template for business and scientific visualizations.You’ll begin by installing Python 3, see how to work in Jupyter notebook, and explore Leather, Python’s popular data visualization charting library. You’ll also be introduced to the scientific Python 3 ecosystem and work with the basics of NumPy, an integral part of that ecosystem. Later chapters are focused on various NumPy routines along with getting started with Scientific Data visualization using matplotlib. You’ll review the visualization of 3D data using graphs and networks and finish up by looking at data visualization with Pandas, including the visualization of COVID-19 data sets.The code examples are tested on popular platforms like Ubuntu, Windows, and Raspberry Pi OS. WithPractical Python Data Visualization you’ll master the core concepts of data visualization with Pandas and the Jupyter notebook interface.What You'll LearnReview practical aspects of Python Data Visualization with programming-friendly abstractions Install Python 3 and Jupyter on multiple platforms including Windows, Raspberry Pi, and Ubuntu Visualize COVID-19 data sets with PandasWho This Book Is ForData Science enthusiasts and professionals, Business analysts and managers, software engineers, data engineers.

Quickly start programming with Python 3 for data visualization with this step-by-step, detailed guide. This book’s programming-friendly approach using libraries such as leather, NumPy, Matplotlib, and Pandas will serve as a template for business and scientific visualizations.

You’ll begin by installing Python 3, see how to work in Jupyter notebook, and explore Leather, Python’s popular data visualization charting library. You’ll also be introduced to the scientific Python 3 ecosystem and work with the basics of NumPy, an integral part of that ecosystem. Later chapters are focused on various NumPy routines along with getting started with Scientific Data visualization using matplotlib. You’ll review the visualization of 3D data using graphs and networks and finish up by looking at data visualization with Pandas, including the visualization of COVID-19 data sets.

The code examples are tested on popular platforms like Ubuntu, Windows, and Raspberry Pi OS. WithPractical Python Data Visualization you’ll master the core concepts of data visualization with Pandas and the Jupyter notebook interface.

What You''ll LearnReview practical aspects of Python Data Visualization with programming-friendly abstractions Install Python 3 and Jupyter on multiple platforms including Windows, Raspberry Pi, and Ubuntu Visualize COVID-19 data sets with PandasWho This Book Is ForData Science enthusiasts and professionals, Business analysts and managers, software engineers, data engineers. 

Quickly start programming with Linux while learning the Raspberry Pi OS—the Linux distribution designed specifically for low-cost Raspberry Pis. This short guide reviews Linux commands, GUI, and shell scripting in a holistic manner by diving into both advanced and day-to-day tasks using the Raspberry Pi OS.You'll comfortably work with the Linux command prompt, and explore the RPi OS GUI and all its base applications. Then move into writing your own programs with shell-programming and using high-level languages such as C, C++, and Python 3. You’ll also study hardware and GPIO programming. Use Python 3 for GPIO programming to drive LEDs and pushbuttons.Examples are written in Shell, C, C++, and Python 3. Graphical output is displayed in helpful screenshots that capture just what you’ll see when working in this environment. All code examples are well tested on actual Raspberry Pi boards. After reading this book and following the examples, you’ll be able to write programs for demonstration in your academic/industrial research work, business environment, or just your circle of friends for fun! What You'll LearnNavigate the core aspects of Linux and programming on a Linux platform Install Raspberry Pi OS on a Raspberry PiProgram in Shell, C, C++, and PythonRedirect Io and work with the crontabWho This Book Is ForLinux enthusiasts, software engineers, researchers, business analysts, and managers working with the low-cost Raspberry Pi.

Quickly start programming with Linux while learning the Raspberry Pi OS—the Linux distribution designed specifically for low-cost Raspberry Pis. This short guide reviews Linux commands, GUI, and shell scripting in a holistic manner by diving into both advanced and day-to-day tasks using the Raspberry Pi OS.You''ll comfortably work with the Linux command prompt, and explore the RPi OS GUI and all its base applications. Then move into writing your own programs with shell-programming and using high-level languages such as C, C++, and Python 3. You’ll also study hardware and GPIO programming. Use Python 3 for GPIO programming to drive LEDs and pushbuttons.Examples are written in Shell, C, C++, and Python 3. Graphical output is displayed in helpful screenshots that capture just what you’ll see when working in this environment. All code examples are well tested on actual Raspberry Pi boards. After reading this book and following the examples, you’ll be able to write programs for demonstration in your academic/industrial research work, business environment, or just your circle of friends for fun!

What You''ll Learn

Navigate the core aspects of Linux and programming on a Linux platform Install Raspberry Pi OS on a Raspberry PiProgram in Shell, C, C++, and PythonRedirect Io and work with the crontab

Who This Book Is For

Linux enthusiasts, software engineers, researchers, business analysts, and managers working with the low-cost Raspberry Pi.

Learn the core aspects of NumPy, Matplotlib, and Pandas, and use them to write programs with Python 3. This book focuses heavily on various data visualization techniques and will help you acquire expert-level knowledge of working with Matplotlib, a MATLAB-style plotting library for Python programming language that provides an object-oriented API for embedding plots into applications. You'll begin with an introduction to Python 3 and the scientific Python ecosystem. Next, you'll explore NumPy and ndarray data structures, creation routines, and data visualization. You'll examine useful concepts related to style sheets, legends, and layouts, followed by line, bar, and scatter plots. Chapters then cover recipes of histograms, contours, streamplots, and heatmaps, and how to visualize images and audio with pie and polar charts. Moving forward, you'll learn how to visualize with pcolor, pcolormesh, and colorbar, and how to visualize in 3D in Matplotlib, create simple animations, and embed Matplotlib with different frameworks. The concluding chapters cover how to visualize data with Pandas and Matplotlib, Seaborn, and how to work with the real-life data and visualize it. After reading Hands-on Matplotlib you'll be proficient with Matplotlib and able to comfortably work with ndarrays in NumPy and data frames in Pandas. What You'll LearnUnderstand Data Visualization and Python using MatplotlibReview the fundamental data structures in NumPy and Pandas Work with 3D plotting, visualizations, and animationsVisualize images and audio dataWho This Book Is ForData scientists, machine learning engineers and software professionals with basic programming skills.

Learn the core aspects of NumPy, Matplotlib, and Pandas, and use them to write programs with Python 3. This book focuses heavily on various data visualization techniques and will help you acquire expert-level knowledge of working with Matplotlib, a MATLAB-style plotting library for Python programming language that provides an object-oriented API for embedding plots into applications. You''ll begin with an introduction to Python 3 and the scientific Python ecosystem. Next, you''ll explore NumPy and ndarray data structures, creation routines, and data visualization. You''ll examine useful concepts related to style sheets, legends, and layouts, followed by line, bar, and scatter plots. Chapters then cover recipes of histograms, contours, streamplots, and heatmaps, and how to visualize images and audio with pie and polar charts. Moving forward, you''ll learn how to visualize with pcolor, pcolormesh, and colorbar, and how to visualize in 3D in Matplotlib, create simple animations, and embed Matplotlib with different frameworks. The concluding chapters cover how to visualize data with Pandas and Matplotlib, Seaborn, and how to work with the real-life data and visualize it. After reading Hands-on Matplotlib you''ll be proficient with Matplotlib and able to comfortably work with ndarrays in NumPy and data frames in Pandas. What You''ll LearnUnderstand Data Visualization and Python using MatplotlibReview the fundamental data structures in NumPy and Pandas Work with 3D plotting, visualizations, and animationsVisualize images and audio dataWho This Book Is ForData scientists, machine learning engineers and software professionals with basic programming skills.

Learn how to automate unit tests of Python 3 with automation libraries, such as doctest, unittest, nose, nose2, pytest, and selenium. This book explores important concepts in software test automation and demonstrates how to automate, organize, and execute unit tests with Python. It also introduces readers to the concepts of web browser automation and logging.This new edition starts with an introduction to Python 3. Next, it covers doctest and pydoc. This is followed by a discussion on unittest, a framework that comes packaged with Python 3 itself. There is a dedicated section on creating test suites, followed by an explanation of how nose2 provides automatic test module discovery. Moving forward, you will learn about pytest, the most popular third-party library and testrunner for Python. You will see how to write and execute tests with pytest. You’ll also learn to discover tests automatically with pytest.This edition features two brand new chapters, the firstof which focuses on the basics of web browser automation with Selenium. You’ll learn how to use Selenium with unittest to write test cases for browser automation and use the Selenium IDE with web browsers such as Chrome and Firefox. You’ll then explore logging frameworks such as Python’s built-in logger and the third-party framework loguru.The book concludes with an exploration of test-driven development with pytest, during which you will execute a small project using TDD methodology.What You Will LearnStart testing with doctest and unittestUnderstand the idea of unit testingGet started with nose 2 and pytestLearn how to use logger and loguruWork with Selenium and test driven development Who This Book Is ForPython developers, software testers, open source enthusiasts, and contributors to the Python community.

Learn how to automate unit tests of Python 3 with automation libraries, such as doctest, unittest, nose, nose2, pytest, and selenium. This book explores important concepts in software test automation and demonstrates how to automate, organize, and execute unit tests with Python. It also introduces readers to the concepts of web browser automation and logging.

This new edition starts with an introduction to Python 3. Next, it covers doctest and pydoc. This is followed by a discussion on unittest, a framework that comes packaged with Python 3 itself. There is a dedicated section on creating test suites, followed by an explanation of how nose2 provides automatic test module discovery. Moving forward, you will learn about pytest, the most popular third-party library and testrunner for Python. You will see how to write and execute tests with pytest. You’ll also learn to discover tests automatically with pytest.

This edition features two brand new chapters, the firstof which focuses on the basics of web browser automation with Selenium. You’ll learn how to use Selenium with unittest to write test cases for browser automation and use the Selenium IDE with web browsers such as Chrome and Firefox. You’ll then explore logging frameworks such as Python’s built-in logger and the third-party framework loguru.

The book concludes with an exploration of test-driven development with pytest, during which you will execute a small project using TDD methodology.

What You Will Learn

Start testing with doctest and unittestUnderstand the idea of unit testingGet started with nose 2 and pytestLearn how to use logger and loguruWork with Selenium and test driven development

Who This Book Is ForPython developers, software testers, open source enthusiasts, and contributors to the Python community.

Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It introduces tools such as NumPy for numerical processing, Pandas for panel data analysis, Matplotlib for visualization, Scikit-learn for machine learning, and Pytorch for deep learning with Python. It also serves as a long-term reference manual for the practitioners who will find solutions to commonly occurring scenarios.The book is divided into three sections. The first section introduces you to number crunching and data analysis tools using Python with in-depth explanation on environment configuration, data loading, numerical processing, data analysis, and visualizations. The second section covers machine learning basics and Scikit-learn library. It also explains supervised learning, unsupervised learning, implementation, and classification of regression algorithms, and ensemble learning methods in an easy manner with theoreticaland practical lessons. The third section explains complex neural network architectures with details on internal working and implementation of convolutional neural networks. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch.After completing Hands-on Machine Learning with Python, you will be able to implement machine learning and neural network solutions and extend them to your advantage. What You'll LearnReview data structures in NumPy and Pandas Demonstrate machine learning techniques and algorithmUnderstand supervised learning and unsupervised learning Examine convolutional neural networks and Recurrent neural networksGet acquainted with scikit-learn and PyTorchPredict sequences in recurrent neural networks and long short term memory Who This Book Is ForData scientists, machine learning engineers, and software professionals with basic skills in Python programming.

Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It introduces tools such as NumPy for numerical processing, Pandas for panel data analysis, Matplotlib for visualization, Scikit-learn for machine learning, and Pytorch for deep learning with Python. It also serves as a long-term reference manual for the practitioners who will find solutions to commonly occurring scenarios.The book is divided into three sections. The first section introduces you to number crunching and data analysis tools using Python with in-depth explanation on environment configuration, data loading, numerical processing, data analysis, and visualizations. The second section covers machine learning basics and Scikit-learn library. It also explains supervised learning, unsupervised learning, implementation, and classification of regression algorithms, and ensemble learning methods in an easy manner with theoreticaland practical lessons. The third section explains complex neural network architectures with details on internal working and implementation of convolutional neural networks. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch.After completing Hands-on Machine Learning with Python, you will be able to implement machine learning and neural network solutions and extend them to your advantage. What You''ll LearnReview data structures in NumPy and Pandas Demonstrate machine learning techniques and algorithmUnderstand supervised learning and unsupervised learning Examine convolutional neural networks and Recurrent neural networksGet acquainted with scikit-learn and PyTorchPredict sequences in recurrent neural networks and long short term memory Who This Book Is ForData scientists, machine learning engineers, and software professionals with basic skills in Python programming.

Understand the concepts of image processing with Python 3 and create applications using Raspberry Pi 4. This book covers image processing with the latest release of Python 3, using Raspberry Pi OS and Raspberry Pi 4B with the 8 GB RAM model as the preferred computing platform.This second edition begins with the installation of Raspberry Pi OS on the latest model of Raspberry Pi and then introduces Python programming language, IDEs for Python, and digital image processing. It also illustrates the theoretical foundations of Image processing followed by advanced operations in image processing. You'll then review image processing with NumPy, and Matplotlib followed by transformations, interpolation, and measurements of images. Different types of filters such as Kernels convolution filters, low pass filters, high pass filters, and Fourier filters are discussed in a clear, methodical manner. Additionally, the book examines variousimage processing techniques such as Morphology, Thresholding, and Segmentation, followed by a chapter on live webcam input with OpenCV, an image processing library with Python. The book concludes with an appendix covering a new library for image processing with Python, pgmagik, followed by a few important tips and tricks relevant to RPi.What You'll LearnGet started with Raspberry Pi and PythonUnderstand Image Processing with PillowSee how image processing is processed using Numpy and MatplotlibUse Pi camera and webcamWho This Book Is ForRaspberry Pi and IoT enthusiasts, and Python and Open Source professionals

Understand the concepts of image processing with Python 3 and create applications using Raspberry Pi 4. This book covers image processing with the latest release of Python 3, using Raspberry Pi OS and Raspberry Pi 4B with the 8 GB RAM model as the preferred computing platform.This second edition begins with the installation of Raspberry Pi OS on the latest model of Raspberry Pi and then introduces Python programming language, IDEs for Python, and digital image processing. It also illustrates the theoretical foundations of Image processing followed by advanced operations in image processing. You''ll then review image processing with NumPy, and Matplotlib followed by transformations, interpolation, and measurements of images. Different types of filters such as Kernels convolution filters, low pass filters, high pass filters, and Fourier filters are discussed in a clear, methodical manner. Additionally, the book examines variousimage processing techniques such as Morphology, Thresholding, and Segmentation, followed by a chapter on live webcam input with OpenCV, an image processing library with Python. The book concludes with an appendix covering a new library for image processing with Python, pgmagik, followed by a few important tips and tricks relevant to RPi.What You''ll LearnGet started with Raspberry Pi and PythonUnderstand Image Processing with PillowSee how image processing is processed using Numpy and MatplotlibUse Pi camera and webcamWho This Book Is ForRaspberry Pi and IoT enthusiasts, and Python and Open Source professionals 

Start building amazing projects with the Raspberry Pi right out of the box

About This Book

Explore the vast range of opportunities provided by Raspberry Pi and other hardware components such as a webcam, the Pi camera, and sensorsGet hands-on experience with coding, networking, and hardware with the Raspberry Pi platformLearn through ample screenshots that offer a play-by-play account of how to implement Raspberry-Pi-based real-life projects

Who This Book Is For

What''s the best way to learn how to use your Raspberry Pi? By example! If you want something exciting to do whilst getting to grips with what your Pi can offer, this is the book for you. With both simple and complex projects, you''ll create a wide variety of cool toys and functions with your Raspberry Pi - all with minimal coding experience necessary.

What You Will Learn

Set up your Raspberry Pi and get it ready for some interesting real-life projectsWork with images, videos, webcams, and the Pi camera and create amazing time-lapse videosExplore the amazing world of Minecraft PiGet to know how to use PiGlow for GPIO programmingInterface your Pi with Grove Sensors and implement IoT applicationsBuild your own cluster with Raspberry PiUnderstand the networking and network programming fundamentals

In Detail

Want to put your Raspberry Pi through its paces right out of the box? This tutorial guide is designed to get you learning all the tricks of the Raspberry Pi through building complete, hands-on hardware projects. Speed through the basics and then dive right in to development!

Discover that you can do almost anything with your Raspberry Pi with a taste of almost everything. Get started with Pi Gaming as you learn how to set up Minecraft, and then program your own game with the help of Pygame. Turn the Pi into your own home security system with complete guidance on setting up a webcam spy camera and OpenCV computer vision for image recognition capabilities. Get to grips with GPIO programming to make a Pi-based glowing LED system, build a complete functioning motion tracker, and more. Finally, get ready to tackle projects that push your Pi to its limits. Construct a complete Internet of Things home automation system with the Raspberry Pi to control your house via Twitter; turn your Pi into a super-computer through linking multiple boards into a cluster and then add in advanced network capabilities for super speedy processing!

Style and approach

This step-by-step guide to building Raspberry-Pi-based projects is explained in a conversational and easy-to-follow style. Each topic is explained sequentially in the process of creating real-life projects, and detailed explanations of the basic and advanced features of various Python libraries are also included.

Perform a wide variety of computer vision tasks such as image processing and manipulation, feature and object detection, and image restoration to build real-life computer vision applications

Key Features

Explore the potential of computer vision with Raspberry Pi and Python programmingPerform computer vision tasks such as image processing and manipulation using OpenCV and Raspberry PiDiscover easy-to-follow examples and screenshots to implement popular computer vision techniques and applications

Book Description

Raspberry Pi is one of the popular single-board computers of our generation. All the major image processing and computer vision algorithms and operations can be implemented easily with OpenCV on Raspberry Pi. This updated second edition is packed with cutting-edge examples and new topics, and covers the latest versions of key technologies such as Python 3, Raspberry Pi, and OpenCV. This book will equip you with the skills required to successfully design and implement your own OpenCV, Raspberry Pi, and Python-based computer vision projects.

At the start, you''ll learn the basics of Python 3, and the fundamentals of single-board computers and NumPy. Next, you''ll discover how to install OpenCV 4 for Python 3 on Raspberry Pi, before covering major techniques and algorithms in image processing, manipulation, and computer vision. By working through the steps in each chapter, you''ll understand essential OpenCV features. Later sections will take you through creating graphical user interface (GUI) apps with GPIO and OpenCV. You''ll also learn to use the new computer vision library, Mahotas, to perform various image processing operations. Finally, you''ll explore the Jupyter Notebook and how to set up a Windows computer and Ubuntu for computer vision.

By the end of this book, you''ll be able to confidently build and deploy computer vision apps.

What you will learn

Set up a Raspberry Pi for computer vision applicationsPerform basic image processing with libraries such as NumPy, Matplotlib, and OpenCVDemonstrate arithmetical, logical, and other operations on imagesWork with a USB webcam and the Raspberry Pi Camera ModuleImplement low-pass and high-pass filters and understand their applications in image processingCover advanced techniques such as histogram equalization and morphological transformationsCreate GUI apps with Python 3 and OpenCVPerform machine learning with K-means clustering and image quantization

Who this book is for

This book is for beginners as well as experienced Raspberry Pi and Python 3 enthusiasts who are looking to explore the amazing world of computer vision. Working knowledge of the Python 3 programming language is assumed.

Perform a wide variety of computer vision tasks such as image processing and manipulation, feature and object detection, and image restoration to build real-life computer vision applicationsKey FeaturesExplore the potential of computer vision with Raspberry Pi and Python programmingPerform computer vision tasks such as image processing and manipulation using OpenCV and Raspberry PiDiscover easy-to-follow examples and screenshots to implement popular computer vision techniques and applicationsBook DescriptionRaspberry Pi is one of the popular single-board computers of our generation. All the major image processing and computer vision algorithms and operations can be implemented easily with OpenCV on Raspberry Pi. This updated second edition is packed with cutting-edge examples and new topics, and covers the latest versions of key technologies such as Python 3, Raspberry Pi, and OpenCV. This book will equip you with the skills required to successfully design and implement your own OpenCV, Raspberry Pi, and Python-based computer vision projects.At the start, you'll learn the basics of Python 3, and the fundamentals of single-board computers and NumPy. Next, you'll discover how to install OpenCV 4 for Python 3 on Raspberry Pi, before covering major techniques and algorithms in image processing, manipulation, and computer vision. By working through the steps in each chapter, you'll understand essential OpenCV features. Later sections will take you through creating graphical user interface (GUI) apps with GPIO and OpenCV. You'll also learn to use the new computer vision library, Mahotas, to perform various image processing operations. Finally, you'll explore the Jupyter Notebook and how to set up a Windows computer and Ubuntu for computer vision.By the end of this book, you'll be able to confidently build and deploy computer vision apps.What you will learnSet up a Raspberry Pi for computer vision applicationsPerform basic image processing with libraries such as NumPy, Matplotlib, and OpenCVDemonstrate arithmetical, logical, and other operations on imagesWork with a USB webcam and the Raspberry Pi Camera ModuleImplement low-pass and high-pass filters and understand their applications in image processingCover advanced techniques such as histogram equalization and morphological transformationsCreate GUI apps with Python 3 and OpenCVPerform machine learning with K-means clustering and image quantizationWho this book is forThis book is for beginners as well as experienced Raspberry Pi and Python 3 enthusiasts who are looking to explore the amazing world of computer vision. Working knowledge of the Python 3 programming language is assumed.

Develop real-world interactive physical computing applications using the Micro:bit with more than 100 MicroPython examples with circuit diagramsKey FeaturesExplore hardware programming and leverage the power of the BBC Micro:bit and MicroPythonBuild real-life creative projects step by step with each chapter increasing in complexity and interactivityLearn the features of the Micro:bit and how to interface it with electronic components through circuits and code examplesBook DescriptionThis book is a one-stop guide for learning BBC Micro:bit with MicroPython, exploring many hardware components and programming techniques to provide detailed insights into developing practical applications with the Micro:bit. It will also show you how hardware components can be manipulated using a combination of Micro:bit and MicroPython for developing practical projects. BBC Micro:bit in Practice will help you gain a holistic understanding of the BBC Micro:bit platform and MicroPython programming, guiding you through mini projects aimed at developing practical knowledge of circuit design and writing programs. You’ll learn how to write programs for working with built-in LEDs and buttons, interfacing external LEDs, buttons, motors, buzzers, and much more. You’ll also work with built-in radio, speakers, accelerometer, and a compass. You’ll dive into concepts related to the Micro:bit filesystem, interfacing external displays, and working with libraries in detail before exploring sewable circuits and wearable technology.After reading this Micro:bit book, you’ll understand how to apply principles in electronics and MicroPython to create interesting real-life projects from scratch.What you will learnExplore the essentials of the BBC Micro:bit, its hardware specifications, and versionsProgram built-in and external LEDs and buttonsProgram external LED-based displays, buzzers, and stepper motorsUse analog input and pulse width modulation to drive a servo motorDetect gestures with internal sensors such as accelerometer, compass, and magnetometerWork on projects with built-in features such as music, speech, radio, and filesystemExplore the advanced features of the Micro:bitWho this book is forThis book is for anyone who wants to use the combination of MicroPython and the BBC Micro:bit for building exciting real-life projects. Engineers, researchers, hobbyists, and technology instructors working in areas such as embedded systems, electronics, software development, IoT, robotics, teaching, and training will find this book useful for building projects. Prior experience with building basic electronic circuits and any programming language, not necessarily MicroPython, will be helpful.

The seven chapters in this book serve as the first step for novices and microcontroller enthusiasts wishing to make a head start in Arduino programming. The first chapter introduces the Arduino platform, ecosystem, and existing varieties of Arduino Nano boards. It also teaches how to install various tools needed to get started with Arduino Programming. The second chapter kicks off with electronic circuit building and programming around your Arduino. The third chapter explores various buses and analog inputs, In the fourth chapter, you get acquainted with the concept of pulse width modulation (PWM) and working with unipolar stepper motors. In the fifth chapter, you are sure to learn about creating beautiful graphics and basic but useful animation with the aid of an external display. The sixth chapter introduces the readers to the concept of I/O devices such as sensors and the piezo buzzer, exploring their methods of interfacing and programming with the Arduino Nano. The last chapter explores another member of the Arduino Nano family, Arduino Nano 33 loT with its highly interesting capabilities. This chapter employs and deepens many concepts learned from previous chapters to create interesting applications for the vast world of the Internet of Things.The entire book follows a step-by-step approach to explain concepts and the operation of things. Each concepts is invariably followed by a to-the-point circuit diagram and code examples. Next come detailed explanations of the syntax and the logic used. By closely following the concepts, you will become comfortable with circuit building, Arduino programming, the workings of the code examples, and the circuit diagrams presented. The book also has plenty of references to external resources wherever needed. An archive file (.zip) comprising the software examples and Fritzing-style circuit diagrams discussed in the book may be downloaded free of charge from the book''s product and resources page on www.elektor.com (search for: book title and author).