Joseph Howse – författare

Create four mobile apps and explore the world through photography and computer visionKey Features[*] Efficiently harness iOS and OpenCV to capture and process high-quality images at high speed[*] Develop photographic apps and augmented reality apps quickly and easily[*] Detect, recognize, and morph faces and objectsBook DescriptioniOS Application Development with OpenCV 3 enables you to turn your smartphone camera into an advanced tool for photography and computer vision. Using the highly optimized OpenCV library, you will process high-resolution images in real time. You will locate and classify objects, and create models of their geometry. As you develop photo and augmented reality apps, you will gain a general understanding of iOS frameworks and developer tools, plus a deeper understanding of the camera and image APIs. After completing the book's four projects, you will be a well-rounded iOS developer with valuable experience in OpenCV.What you will learn[*] Use Xcode and Interface Builder to develop iOS apps[*] Obtain OpenCV s standard modules and build extra modules from source[*] Control all the parameters of the iOS device s camera[*] Capture, save, and share photos and videos[*] Analyze colors, shapes, and textures in ordinary and specialized photographs[*] Blend and compare images to create special photographic effects and augmented reality tools[*] Detect faces and morph facial features[*] Classify coins and other objectsWho this book is forIf you want to do computational photography and computer vision on Apple’s mobile devices, then this book is for you. No previous experience with app development or OpenCV is required. However, basic knowledge of C++ or Objective-C is recommended.

Get savvy with OpenCV and actualize cool computer vision applicationsAbout This Book* Use OpenCV's Python bindings to capture video, manipulate images, and track objects* Learn about the different functions of OpenCV and their actual implementations.* Develop a series of intermediate to advanced projects using OpenCV and PythonWho This Book Is ForThis learning path is for someone who has a working knowledge of Python and wants to try out OpenCV. This Learning Path will take you from a beginner to an expert in computer vision applications using OpenCV. OpenCV's application are humongous and this Learning Path is the best resource to get yourself acquainted thoroughly with OpenCV.What You Will Learn* Install OpenCV and related software such as Python, NumPy, SciPy, OpenNI, and SensorKinect - all on Windows, Mac or Ubuntu* Apply "curves" and other color transformations to simulate the look of old photos, movies, or video games* Apply geometric transformations to images, perform image filtering, and convert an image into a cartoon-like image* Recognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor* Reconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniques* Detect and recognize street signs using a cascade classifier and support vector machines (SVMs)* Identify emotional expressions in human faces using convolutional neural networks (CNNs) and SVMs* Strengthen your OpenCV2 skills and learn how to use new OpenCV3 featuresIn DetailOpenCV is a state-of-art computer vision library that allows a great variety of image and video processing operations. OpenCV for Python enables us to run computer vision algorithms in real time. This learning path proposes to teach the following topics. First, we will learn how to get started with OpenCV and OpenCV3's Python API, and develop a computer vision application that tracks body parts. Then, we will build amazing intermediate-level computer vision applications such as making an object disappear from an image, identifying different shapes, reconstructing a 3D map from images , and building an augmented reality application, Finally, we'll move to more advanced projects such as hand gesture recognition, tracking visually salient objects, as well as recognizing traffic signs and emotions on faces using support vector machines and multi-layer perceptrons respectively. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:* OpenCV Computer Vision with Python by Joseph Howse * OpenCV with Python By Example by Prateek Joshi* OpenCV with Python Blueprints by Michael BeyelerStyle and approachThis course aims to create a smooth learning path that will teach you how to get started with will learn how to get started with OpenCV and OpenCV 3's Python API, and develop superb computer vision applications. Through this comprehensive course, you'll learn to create computer vision applications from scratch to finish and more!.

Turn futuristic ideas about computer vision and machine learning into demonstrations that are both functional and entertainingKey FeaturesBuild OpenCV 4 apps with Python 2 and 3 on desktops and Raspberry Pi, Java on Android, and C# in UnityDetect, classify, recognize, and measure real-world objects in real-timeWork with images from diverse sources, including the web, research datasets, and various camerasBook DescriptionOpenCV 4 is a collection of image processing functions and computer vision algorithms. It is open source, supports many programming languages and platforms, and is fast enough for many real-time applications. With this handy library, you’ll be able to build a variety of impressive gadgets.OpenCV 4 for Secret Agents features a broad selection of projects based on computer vision, machine learning, and several application frameworks. To enable you to build apps for diverse desktop systems and Raspberry Pi, the book supports multiple Python versions, from 2.7 to 3.7. For Android app development, the book also supports Java in Android Studio, and C# in the Unity game engine. Taking inspiration from the world of James Bond, this book will add a touch of adventure and computer vision to your daily routine. You’ll be able to protect your home and car with intelligent camera systems that analyze obstacles, people, and even cats. In addition to this, you’ll also learn how to train a search engine to praise or criticize the images that it finds, and build a mobile app that speaks to you and responds to your body language.By the end of this book, you will be equipped with the knowledge you need to advance your skills as an app developer and a computer vision specialist.What you will learnDetect motion and recognize gestures to control a smartphone gameDetect car headlights and estimate their distanceDetect and recognize human and cat faces to trigger an alarmAmplify motion in a real-time video to show heartbeats and breathsMake a physics simulation that detects shapes in a real-world drawingBuild OpenCV 4 projects in Python 3 for desktops and Raspberry PiDevelop OpenCV 4 Android applications in Android Studio and UnityWho this book is forIf you are an experienced software developer who is new to computer vision or machine learning, and wants to study these topics through creative projects, then this book is for you. The book will also help existing OpenCV users who want upgrade their projects to OpenCV 4 and new versions of other libraries, languages, tools, and operating systems. General familiarity with object-oriented programming, application development, and usage of operating systems (OS), developer tools, and the command line is required.

Updated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer vision problems with practical codeKey FeaturesBuild powerful computer vision applications in concise code with OpenCV 4 and Python 3Learn the fundamental concepts of image processing, object classification, and 2D and 3D trackingTrain, use, and understand machine learning models such as Support Vector Machines (SVMs) and neural networksBook DescriptionComputer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You’ll be able to put theory into practice by building apps with OpenCV 4 and Python 3.You’ll start by understanding OpenCV 4 and how to set it up with Python 3 on various platforms. Next, you’ll learn how to perform basic operations such as reading, writing, manipulating, and displaying still images, videos, and camera feeds. From taking you through image processing, video analysis, and depth estimation and segmentation, to helping you gain practice by building a GUI app, this book ensures you’ll have opportunities for hands-on activities. Next, you’ll tackle two popular challenges: face detection and face recognition. You’ll also learn about object classification and machine learning concepts, which will enable you to create and use object detectors and classifiers, and even track objects in movies or video camera feed. Later, you’ll develop your skills in 3D tracking and augmented reality. Finally, you’ll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age.By the end of this book, you’ll have the skills you need to execute real-world computer vision projects.What you will learnInstall and familiarize yourself with OpenCV 4 s Python 3 bindingsUnderstand image processing and video analysis basicsUse a depth camera to distinguish foreground and background regionsDetect and identify objects, and track their motion in videosTrain and use your own models to match images and classify objectsDetect and recognize faces, and classify their gender and ageBuild an augmented reality application to track an image in 3DWork with machine learning models, including SVMs, artificial neural networks (ANNs), and deep neural networks (DNNs)Who this book is forIf you are interested in learning computer vision, machine learning, and OpenCV in the context of practical real-world applications, then this book is for you. This OpenCV book will also be useful for anyone getting started with computer vision as well as experts who want to stay up-to-date with OpenCV 4 and Python 3. Although no prior knowledge of image processing, computer vision or machine learning is required, familiarity with basic Python programming is a must.