Mastering Opencv 4 With Python
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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.
Mastering Opencv 4
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Author : Roy Shilkrot
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-27
Mastering Opencv 4 written by Roy Shilkrot 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 2018-12-27 with Computers categories.
Work on practical computer vision projects covering advanced object detector techniques and modern deep learning and machine learning algorithms Key FeaturesLearn about the new features that help unlock the full potential of OpenCV 4Build face detection applications with a cascade classifier using face landmarksCreate an optical character recognition (OCR) model using deep learning and convolutional neural networksBook Description Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks. You’ll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You’ll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You’ll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4. What you will learnBuild real-world computer vision problems with working OpenCV code samplesUncover best practices in engineering and maintaining OpenCV projectsExplore algorithmic design approaches for complex computer vision tasksWork with OpenCV’s most updated API (v4.0.0) through projectsUnderstand 3D scene reconstruction and Structure from Motion (SfM)Study camera calibration and overlay AR using the ArUco ModuleWho this book is for This book is for those who have a basic knowledge of OpenCV and are competent C++ programmers. You need to have an understanding of some of the more theoretical/mathematical concepts, as we move quite quickly throughout the book.
Mastering Opencv 4
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Author : Roy Shilkrot
language : en
Publisher:
Release Date : 2018
Mastering Opencv 4 written by Roy Shilkrot and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
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
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
Hands On Computer Vision With Tensorflow 2
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Author : Benjamin Planche
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-30
Hands On Computer Vision With Tensorflow 2 written by Benjamin Planche 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 2019-05-30 with Computers categories.
A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more Key FeaturesDiscover how to build, train, and serve your own deep neural networks with TensorFlow 2 and KerasApply modern solutions to a wide range of applications such as object detection and video analysisLearn how to run your models on mobile devices and web pages and improve their performanceBook Description Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0. What you will learnCreate your own neural networks from scratchClassify images with modern architectures including Inception and ResNetDetect and segment objects in images with YOLO, Mask R-CNN, and U-NetTackle problems faced when developing self-driving cars and facial emotion recognition systemsBoost your application's performance with transfer learning, GANs, and domain adaptationUse recurrent neural networks (RNNs) for video analysisOptimize and deploy your networks on mobile devices and in the browserWho this book is for If you're new to deep learning and have some background in Python programming and image processing, like reading/writing image files and editing pixels, this book is for you. Even if you're an expert curious about the new TensorFlow 2 features, you'll find this book useful. While some theoretical concepts require knowledge of algebra and calculus, the book covers concrete examples focused on practical applications such as visual recognition for self-driving cars and smartphone apps.
Artificial Intelligence Over Infrared Images For Medical Applications
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Author : Siva Teja Kakileti
language : en
Publisher: Springer Nature
Release Date : 2023-09-28
Artificial Intelligence Over Infrared Images For Medical Applications written by Siva Teja Kakileti and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-28 with Computers categories.
This book constitutes the refereed proceedings of the Second Workshop on Artificial Intelligence over Infrared Images for Medical Applications, AIIIMA 2023 held in conjunction with MICCAI 2023, held in Vancouver, BC, Canada, on October 2, 2023. The 10 full papers presented in this book were carefully peer reviewed and selected from 15 submissions. The second workshop on AIIIMA, similarily to the first, aimes to create a forum to discuss the specific sub-topic of AI over Infrared Images for Medical Applications at MICCAI and promote this novel area of research, that has the potential to hugely impact our society, among the research community.
The Art Of Deep Learning Image Augmentation The Seeds Of Success
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Author : Jyotismita Chaki
language : en
Publisher: Springer Nature
Release Date : 2025-05-02
The Art Of Deep Learning Image Augmentation The Seeds Of Success written by Jyotismita Chaki and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-02 with Computers categories.
This book addresses the critical challenge of limited training data in deep learning for computer vision by exploring and evaluating various image augmentation techniques, with a particular emphasis on deep learning-based methods. Chapter 1 establishes the core problem of data scarcity, outlining its negative impacts on model performance, and introduces traditional image augmentation techniques like geometric transformations, color space manipulations, and other methods such as noise injection. It highlights the limitations of these traditional approaches, including limited variation, lack of control, and inability to introduce new information, before introducing the advantages of deep learning-based augmentation, such as superior control, task adaptability, enhanced realism, and automation. Chapter 2 delves into GAN-based image augmentation, discussing how GANs generate realistic synthetic images for various applications like super-resolution and image-to-image translation, while also addressing the challenges associated with GAN training and potential future directions. Chapter 3 explores autoencoder-based image augmentation, covering techniques like VAEs, DAEs, and AAEs, and highlighting architectural considerations and challenges such as overfitting. Chapter 4 showcases the diverse applications of deep learning-based image augmentation and how it enhances various computer vision tasks by improving generalization, robustness, and accuracy. Chapter 5 discusses strategies for evaluating and optimizing deep learning image augmentation, including traditional metrics, image quality metrics, and hyperparameter tuning techniques. Finally, Chapter 6 explores cutting-edge advancements, covering AutoAugment, interpretable augmentation, attention-based augmentation, counterfactual augmentation, and human-in-the-loop augmentation, emphasizing the role of human expertise in creating high-quality augmented data.
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
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.