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Hands On Ml Projects With Opencv Master Computer Vision And Machine Learning Using Opencv And Python


Hands On Ml Projects With Opencv Master Computer Vision And Machine Learning Using Opencv And Python
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Hands On Ml Projects With Opencv Master Computer Vision And Machine Learning Using Opencv And Python


Hands On Ml Projects With Opencv Master Computer Vision And Machine Learning Using Opencv And Python
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Author : Mugesh S.
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2023-08-09

Hands On Ml Projects With Opencv Master Computer Vision And Machine Learning Using Opencv And Python written by Mugesh S. and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-09 with Computers categories.


Be at your A game in building Intelligent systems by leveraging Computer vision and Machine Learning. Key Features ● Step-by-step instructions and code snippets for real world ML projects. ● Covers entire spectrum from basics to advanced concepts such as deep learning, transfer learning, and model optimization ● Loaded with practical tips and best practices for implementing machine learning with OpenCV for optimising your workflow. Book Description This book is an in-depth guide that merges machine learning techniques with OpenCV, the most popular computer vision library, using Python. The book introduces fundamental concepts in machine learning and computer vision, progressing to practical implementation with OpenCV. Concepts related to image preprocessing, contour and thresholding techniques, motion detection and tracking are explained in a step-by-step manner using code and output snippets. Hands-on projects with real-world datasets will offer you an invaluable experience in solving OpenCV challenges with machine learning. It’s an ultimate guide to explore areas like deep learning, transfer learning, and model optimization, empowering readers to tackle complex tasks. Every chapter offers practical tips and tricks to build effective ML models. By the end, you would have mastered and applied ML concepts confidently to real-world computer vision problems and will be able to develop robust and accurate machine-learning models for diverse applications. Whether you are new to machine learning or seeking to enhance your computer vision skills, This book is an invaluable resource for mastering the integration of machine learning and computer vision using OpenCV and Python. What you will learn ● Learn how to work with images and perform basic image processing tasks using OpenCV. ● Implement machine learning techniques to computer vision tasks such as image classification, object detection, and image segmentation. ● Work on real-world projects and datasets to gain hands-on experience in applying machine learning techniques with OpenCV. ● Explore the concepts of deep learning using Tensorflow and Keras and how it can be used for computer vision tasks. Who is this book for? This book is for everyone with a basic understanding of programming and who wants to apply machine learning in computer vision using OpenCV and Python. Whether you're a student, researcher, or developer, this book will equip you with practical skills for machine learning projects. Some familiarity with Python and machine learning concepts is assumed. Table of ContentsChapter 1: Getting Started With OpenCV Chapter 2: Basic Image & Video Analytics in OpenCV Chapter 3: Image Processing 1 using OpenCV Chapter 4: Image Processing 2 using OpenCV Chapter 5: Thresholding and Contour Techniques Using OpenCV Chapter 6: Detect Corners and Road Lane using OpenCV Chapter 7: Object And Motion Detection Using Opencv Chapter 8: Image Segmentation and Detecting Faces Using OpenCV Chapter 9: Introduction to Deep Learning with OpenCV Chapter 10: Advance Deep Learning Projects with OpenCV Chapter 11: Deployment of OpenCV projects



Hands On Ml Projects With Opencv


Hands On Ml Projects With Opencv
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Author : Mugesh S.
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2023-08-10

Hands On Ml Projects With Opencv written by Mugesh S. and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-10 with Computers categories.


Be at your A game in building Intelligent systems by leveraging Computer vision and Machine Learning. KEY FEATURES ● Step-by-step instructions and code snippets for real world ML projects. ● Covers entire spectrum from basics to advanced concepts such as deep learning, transfer learning, and model optimization ● Loaded with practical tips and best practices for implementing machine learning with OpenCV for optimising your workflow. DESCRIPTION This book is an in-depth guide that merges machine learning techniques with OpenCV, the most popular computer vision library, using Python. The book introduces fundamental concepts in machine learning and computer vision, progressing to practical implementation with OpenCV. Concepts related to image preprocessing, contour and thresholding techniques, motion detection and tracking are explained in a step-by-step manner using code and output snippets. Hands-on projects with real-world datasets will offer you an invaluable experience in solving OpenCV challenges with machine learning. It’s an ultimate guide to explore areas like deep learning, transfer learning, and model optimization, empowering readers to tackle complex tasks. Every chapter offers practical tips and tricks to build effective ML models. By the end, you would have mastered and applied ML concepts confidently to real-world computer vision problems and will be able to develop robust and accurate machine-learning models for diverse applications. Whether you are new to machine learning or seeking to enhance your computer vision skills, This book is an invaluable resource for mastering the integration of machine learning and computer vision using OpenCV and Python. WHAT WILL YOU LEARN ● Learn how to work with images and perform basic image processing tasks using OpenCV. ● Implement machine learning techniques to computer vision tasks such as image classification, object detection, and image segmentation. ● Work on real-world projects and datasets to gain hands-on experience in applying machine learning techniques with OpenCV. ● Explore the concepts of deep learning using Tensorflow and Keras and how it can be used for computer vision tasks. ● Understand the concept of transfer learning and how pre-trained models can be leveraged for new tasks. ● Utilize techniques for model optimization and deployment in resource-constrained environments. ● Implement end-to-end solutions and address challenges encountered in practical scenarios. WHO IS THIS BOOK FOR? This book is for everyone with a basic understanding of programming and who wants to apply machine learning in computer vision using OpenCV and Python. Whether you're a student, researcher, or developer, this book will equip you with practical skills for machine learning projects. Some familiarity with Python and machine learning concepts is assumed. Beginners too will find this book valuable as it offers clear examples and explanations for every concept. TABLE OF CONTENTS Chapter 1: Getting Started With OpenCV Chapter 2: Basic Image & Video Analytics in OpenCV Chapter 3: Image Processing 1 using OpenCV Chapter 4: Image Processing 2 using OpenCV Chapter 5: Thresholding and Contour Techniques Using OpenCV Chapter 6: Detect Corners and Road Lane using OpenCV Chapter 7: Object And Motion Detection Using Opencv Chapter 8: Image Segmentation and Detecting Faces Using OpenCV Chapter 9: Introduction to Deep Learning with OpenCV Chapter 10: Advance Deep Learning Projects with OpenCV Chapter 11: Deployment of OpenCV projects



Mastering Opencv With Python Use Numpy Scikit Tensorflow And Matplotlib To Learn Advanced Algorithms For Machine Learning Through A Set Of Practical Projects


Mastering Opencv With Python Use Numpy Scikit Tensorflow And Matplotlib To Learn Advanced Algorithms For Machine Learning Through A Set Of Practical Projects
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Author : Ayush Vaishya
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2023-11-16

Mastering Opencv With Python Use Numpy Scikit Tensorflow And Matplotlib To Learn Advanced Algorithms For Machine Learning Through A Set Of Practical Projects written by Ayush Vaishya and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-16 with Computers categories.


Unlocking Visual Insights: OpenCV Made Simple and Powerful. Key Features ● OpenCV Mastery: Harness the full potential of OpenCV. ● Comprehensive Coverage: From fundamentals to advanced techniques. ● Practical Exercises: Apply knowledge through hands-on tasks. Book Description "Mastering OpenCV with Python" immerses you in the captivating realm of computer vision, with a structured approach that equips you with the knowledge and skills essential for success in this rapidly evolving field. From grasping the fundamental concepts of image processing and OpenCV to mastering advanced techniques such as neural networks and object detection, you will gain a comprehensive understanding. Each chapter is enriched with hands-on exercises and real-world projects, ensuring the acquisition of practical skills that can be immediately applied in your professional journey. This book not only elevates your technical proficiency but also prepares you for a rewarding career. The technological job landscape is constantly evolving, and professionals who can harness the potential of computer vision are in high demand. By mastering the skills and insights contained within these pages, you will be well-prepared to explore exciting career opportunities, ranging from machine learning engineering to computer vision research. This book is your ticket to a future filled with innovation and professional advancement within the dynamic world of computer vision. What you will learn ● Master Image Processing and Machine Learning with OpenCV using advanced Tools and Libraries. ● Create Real-World Projects with Hands-On Experience. ● Explore Machine Learning for Computer Vision. ● Develop Confidence in Practical Computer Vision Projects. ● Conquer Real-World Image Processing Challenges. ● Apply Computer Vision Across Diverse Industries. ● Boost Your Career in Computer Vision. ● Become an Expert in Computer Vision for Career Advancement. Who is this book for? This beginner-friendly book in computer vision requires no prior experience, making it accessible to newcomers. While a basic programming understanding is helpful, it's designed to guide individuals from diverse backgrounds into the captivating realms of AI, computer vision, and image processing. It's equally valuable for aspiring tech professionals, students, and enthusiasts seeking rewarding careers and knowledge in these cutting-edge fields. Table of Contents 1. Introduction to Computer Vision 2. Getting Started with Images 3. Image Processing Fundamentals 4. Image Operations 5. Image Histograms 6. Image Segmentation 7. Edges and Contours 8. Machine Learning with Images 9. Advanced Computer Vision Algorithms 10. Neural Networks 11. Object Detection Using OpenCV 12. Projects Using OpenCV Index



Mastering Opencv With Python


Mastering Opencv With Python
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Author : Ayush Vaishya
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2023-11-15

Mastering Opencv With Python written by Ayush Vaishya and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-15 with Computers categories.


Unlocking Visual Insights: OpenCV Made Simple and Powerful. KEY FEATURES ● OpenCV Mastery: Harness the full potential of OpenCV. ● Comprehensive Coverage: From fundamentals to advanced techniques. ● Practical Exercises: Apply knowledge through hands-on tasks. DESCRIPTION "Mastering OpenCV with Python" immerses you in the captivating realm of computer vision, with a structured approach that equips you with the knowledge and skills essential for success in this rapidly evolving field. From grasping the fundamental concepts of image processing and OpenCV to mastering advanced techniques such as neural networks and object detection, you will gain a comprehensive understanding. Each chapter is enriched with hands-on exercises and real-world projects, ensuring the acquisition of practical skills that can be immediately applied in your professional journey. This book not only elevates your technical proficiency but also prepares you for a rewarding career. The technological job landscape is constantly evolving, and professionals who can harness the potential of computer vision are in high demand. By mastering the skills and insights contained within these pages, you will be well-prepared to explore exciting career opportunities, ranging from machine learning engineering to computer vision research. This book is your ticket to a future filled with innovation and professional advancement within the dynamic world of computer vision. WHAT WILL YOU LEARN ● Master Image Processing and Machine Learning with OpenCV using advanced Tools and Libraries. ● Create Real-World Projects with Hands-On Experience. ● Explore Machine Learning for Computer Vision. ● Develop Confidence in Practical Computer Vision Projects. ● Conquer Real-World Image Processing Challenges. ● Apply Computer Vision Across Diverse Industries. ● Boost Your Career in Computer Vision. ● Become an Expert in Computer Vision for Career Advancement. WHO IS THIS BOOK FOR? This beginner-friendly book in computer vision requires no prior experience, making it accessible to newcomers. While a basic programming understanding is helpful, it's designed to guide individuals from diverse backgrounds into the captivating realms of AI, computer vision, and image processing. It's equally valuable for aspiring tech professionals, students, and enthusiasts seeking rewarding careers and knowledge in these cutting-edge fields. TABLE OF CONTENTS 1. Introduction to Computer Vision 2. Getting Started with Images 3. Image Processing Fundamentals 4. Image Operations 5. Image Histograms 6. Image Segmentation 7. Edges and Contours 8. Machine Learning with Images 9. Advanced Computer Vision Algorithms 10. Neural Networks 11. Object Detection Using OpenCV 12. Projects Using OpenCV Index



Machine Learning For Opencv


Machine Learning For Opencv
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Author : Michael Beyeler
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-07-14

Machine Learning For Opencv written by Michael Beyeler and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-14 with Computers categories.


Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide. About This Book Load, store, edit, and visualize data using OpenCV and Python Grasp the fundamental concepts of classification, regression, and clustering Understand, perform, and experiment with machine learning techniques using this easy-to-follow guide Evaluate, compare, and choose the right algorithm for any task Who This Book Is For This book targets Python programmers who are already familiar with OpenCV; this book will give you the tools and understanding required to build your own machine learning systems, tailored to practical real-world tasks. What You Will Learn Explore and make effective use of OpenCV's machine learning module Learn deep learning for computer vision with Python Master linear regression and regularization techniques Classify objects such as flower species, handwritten digits, and pedestrians Explore the effective use of support vector machines, boosted decision trees, and random forests Get acquainted with neural networks and Deep Learning to address real-world problems Discover hidden structures in your data using k-means clustering Get to grips with data pre-processing and feature engineering In Detail Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today's most exciting application fields of machine learning, with Deep Learning driving innovative systems such as self-driving cars and Google's DeepMind. OpenCV lies at the intersection of these topics, providing a comprehensive open-source library for classic as well as state-of-the-art computer vision and machine learning algorithms. In combination with Python Anaconda, you will have access to all the open-source computing libraries you could possibly ask for. Machine learning for OpenCV begins by introducing you to the essential concepts of statistical learning, such as classification and regression. Once all the basics are covered, you will start exploring various algorithms such as decision trees, support vector machines, and Bayesian networks, and learn how to combine them with other OpenCV functionality. As the book progresses, so will your machine learning skills, until you are ready to take on today's hottest topic in the field: Deep Learning. By the end of this book, you will be ready to take on your own machine learning problems, either by building on the existing source code or developing your own algorithm from scratch! Style and approach OpenCV machine learning connects the fundamental theoretical principles behind machine learning to their practical applications in a way that focuses on asking and answering the right questions. This book walks you through the key elements of OpenCV and its powerful machine learning classes, while demonstrating how to get to grips with a range of models.



Opencv 3 Computer Vision With Python Cookbook


Opencv 3 Computer Vision With Python Cookbook
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Author : Aleksei Spizhevoi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-03-23

Opencv 3 Computer Vision With Python Cookbook written by Aleksei Spizhevoi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-23 with Computers categories.


OpenCV 3 is a native cross-platform library for computer vision, machine learning, and image processing. OpenCV's convenient high-level APIs hide very powerful internals designed for computational efficiency that can take advantage of multicore and GPU processing. This book will help you tackle increasingly challenging computer vision problems ...



Mastering Opencv 4 With Python


Mastering Opencv 4 With Python
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Author : Alberto Fernández Villán
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-03-29

Mastering Opencv 4 With Python written by Alberto Fernández Villán and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-29 with Computers categories.


Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key FeaturesDevelop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4) and PythonApply machine learning and deep learning techniques with TensorFlow and KerasDiscover the modern design patterns you should avoid when developing efficient computer vision applicationsBook Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learnHandle files and images, and explore various image processing techniquesExplore image transformations, including translation, resizing, and croppingGain insights into building histogramsBrush up on contour detection, filtering, and drawingWork with Augmented Reality to build marker-based and markerless applicationsWork with the main machine learning algorithms in OpenCVExplore the deep learning Python libraries and OpenCV deep learning capabilitiesCreate computer vision and deep learning web applicationsWho this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.



Machine Learning For Opencv 4


Machine Learning For Opencv 4
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Author : Aditya Sharma
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-09-06

Machine Learning For Opencv 4 written by Aditya Sharma and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-06 with Computers categories.


A practical guide to understanding the core machine learning and deep learning algorithms, and implementing them to create intelligent image processing systems using OpenCV 4 Key FeaturesGain insights into machine learning algorithms, and implement them using OpenCV 4 and scikit-learnGet up to speed with Intel OpenVINO and its integration with OpenCV 4Implement high-performance machine learning models with helpful tips and best practicesBook Description OpenCV is an opensource library for building computer vision apps. The latest release, OpenCV 4, offers a plethora of features and platform improvements that are covered comprehensively in this up-to-date second edition. You'll start by understanding the new features and setting up OpenCV 4 to build your computer vision applications. You will explore the fundamentals of machine learning and even learn to design different algorithms that can be used for image processing. Gradually, the book will take you through supervised and unsupervised machine learning. You will gain hands-on experience using scikit-learn in Python for a variety of machine learning applications. Later chapters will focus on different machine learning algorithms, such as a decision tree, support vector machines (SVM), and Bayesian learning, and how they can be used for object detection computer vision operations. You will then delve into deep learning and ensemble learning, and discover their real-world applications, such as handwritten digit classification and gesture recognition. Finally, you’ll get to grips with the latest Intel OpenVINO for building an image processing system. By the end of this book, you will have developed the skills you need to use machine learning for building intelligent computer vision applications with OpenCV 4. What you will learnUnderstand the core machine learning concepts for image processingExplore the theory behind machine learning and deep learning algorithm designDiscover effective techniques to train your deep learning modelsEvaluate machine learning models to improve the performance of your modelsIntegrate algorithms such as support vector machines and Bayes classifier in your computer vision applicationsUse OpenVINO with OpenCV 4 to speed up model inferenceWho this book is for This book is for Computer Vision professionals, machine learning developers, or anyone who wants to learn machine learning algorithms and implement them using OpenCV 4. If you want to build real-world Computer Vision and image processing applications powered by machine learning, then this book is for you. Working knowledge of Python programming is required to get the most out of this book.



Opencv With Python Blueprints


Opencv With Python Blueprints
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Author : Michael Beyeler
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-10-19

Opencv With Python Blueprints written by Michael Beyeler and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-19 with Computers categories.


Design and develop advanced computer vision projects using OpenCV with Python About This Book Program advanced computer vision applications in Python using different features of the OpenCV library Practical end-to-end project covering an important computer vision problem All projects in the book include a step-by-step guide to create computer vision applications Who This Book Is For This book is for intermediate users of OpenCV who aim to master their skills by developing advanced practical applications. Readers are expected to be familiar with OpenCV's concepts and Python libraries. Basic knowledge of Python programming is expected and assumed. What You Will Learn Generate real-time visual effects using different filters and image manipulation techniques such as dodging and burning Recognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor Learn feature extraction and feature matching for tracking arbitrary objects of interest Reconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniques Track visually salient objects by searching for and focusing on important regions of an image Detect faces using a cascade classifier and recognize emotional expressions in human faces using multi-layer peceptrons (MLPs) Recognize street signs using a multi-class adaptation of support vector machines (SVMs) Strengthen your OpenCV2 skills and learn how to use new OpenCV3 features In Detail OpenCV is a native cross platform C++ Library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for development. OpenCV has C++/C, Python, and Java interfaces with support for Windows, Linux, Mac, iOS, and Android. Developers using OpenCV build applications to process visual data; this can include live streaming data from a device like a camera, such as photographs or videos. OpenCV offers extensive libraries with over 500 functions This book demonstrates how to develop a series of intermediate to advanced projects using OpenCV and Python, rather than teaching the core concepts of OpenCV in theoretical lessons. Instead, the working projects developed in this book teach the reader how to apply their theoretical knowledge to topics such as image manipulation, augmented reality, object tracking, 3D scene reconstruction, statistical learning, and object categorization. By the end of this book, readers will be OpenCV experts whose newly gained experience allows them to develop their own advanced computer vision applications. Style and approach This book covers independent hands-on projects that teach important computer vision concepts like image processing and machine learning for OpenCV with multiple examples.



Opencv 4 With Python Blueprints


Opencv 4 With Python Blueprints
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Author : Dr. Menua Gevorgyan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-03-20

Opencv 4 With Python Blueprints written by Dr. Menua Gevorgyan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-20 with Computers categories.


Get to grips with traditional computer vision algorithms and deep learning approaches, and build real-world applications with OpenCV and other machine learning frameworks Key FeaturesUnderstand how to capture high-quality image data, detect and track objects, and process the actions of animals or humansImplement your learning in different areas of computer visionExplore advanced concepts in OpenCV such as machine learning, artificial neural network, and augmented realityBook Description OpenCV is a native cross-platform C++ library for computer vision, machine learning, and image processing. It is increasingly being adopted in Python for development. This book will get you hands-on with a wide range of intermediate to advanced projects using the latest version of the framework and language, OpenCV 4 and Python 3.8, instead of only covering the core concepts of OpenCV in theoretical lessons. This updated second edition will guide you through working on independent hands-on projects that focus on essential OpenCV concepts such as image processing, object detection, image manipulation, object tracking, and 3D scene reconstruction, in addition to statistical learning and neural networks. You’ll begin with concepts such as image filters, Kinect depth sensor, and feature matching. As you advance, you’ll not only get hands-on with reconstructing and visualizing a scene in 3D but also learn to track visually salient objects. The book will help you further build on your skills by demonstrating how to recognize traffic signs and emotions on faces. Later, you’ll understand how to align images, and detect and track objects using neural networks. By the end of this OpenCV Python book, you’ll have gained hands-on experience and become proficient at developing advanced computer vision apps according to specific business needs. What you will learnGenerate real-time visual effects using filters and image manipulation techniques such as dodging and burningRecognize hand gestures in real-time and perform hand-shape analysis based on the output of a Microsoft Kinect sensorLearn feature extraction and feature matching to track arbitrary objects of interestReconstruct a 3D real-world scene using 2D camera motion and camera reprojection techniquesDetect faces using a cascade classifier and identify emotions in human faces using multilayer perceptronsClassify, localize, and detect objects with deep neural networksWho this book is for This book is for intermediate-level OpenCV users who are looking to enhance their skills by developing advanced applications. Familiarity with OpenCV concepts and Python libraries, and basic knowledge of the Python programming language are assumed.