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Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition
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Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition
By the end of this book, you'll have the skills you need to execute real-world computer vision projects.
Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition
Item #: 36269596

Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd

90% of respondents would recommend this to a friend

Item #: 36269596

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What Stands Out

Comprehensive Guidance
Provides thorough tutorials on OpenCV 4 and Python, ensuring both beginners and experienced users can master computer vision concepts effectively with practical examples.
Updated Techniques
Incorporates the latest advancements in computer vision, equipping readers with modern tools and methodologies that enhance their projects and workflows over previous editions.
Hands-On Projects
Includes numerous real-world projects that promote hands-on learning, enabling readers to apply theoretical knowledge and build valuable skills for practical applications in the field.

Product Details

Discover tools, techniques, and algorithms for computer vision and machine learning with the updated 3rd edition of Learning OpenCV 4. Shop now at Ubuy Anguilla.
  • Updated for OpenCV 4 and Python 3
  • Covers depth cameras, 3D tracking, augmented reality, and deep neural networks
  • Build powerful computer vision applications with OpenCV 4 and Python 3
  • Learn fundamental concepts of image processing, object classification, and 2D and 3D tracking
  • Train and use machine learning models like SVMs and neural networks
  • Suitable for beginners and experts in computer vision, machine learning, and OpenCV 4 and Python 3
Publisher Packt Publishing
Publication date February 20, 2020
Edition 3rd ed.
Language English
Print length 372 pages
ISBN-10 1789531616
ISBN-13 978-1789531619
Item Weight 1.54 pounds (700 grams)
Dimensions 7.5 x 0.84 x 9.25 inches (19.1 x 2.1 x 23.5 cm)

Who Should Buy?

Suitable For
  • Beginner Programmers

    Ideal for those new to computer vision and Python, offering foundational knowledge and practical examples.

  • Data Scientists

    Great for data scientists wanting to implement computer vision techniques in their projects using Python.

  • Students

    Perfect for university students studying computer vision, providing relevant content and exercises for practical understanding.

Not Suitable For
  • Advanced Users

    Experienced developers may find the content too basic and not advanced enough for deep exploration.

Product Description

Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition

About This Item

Title: Learning OpenCV 4 Computer Vision with Python 3: Dive into the World of Computer Vision and Machine Learning Description: Are you fascinated by the possibilities of computer vision and machine learning? Look no further! With "Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition," you'll embark on an exciting journey into the realm of computer vision. Whether you're a beginner or an experienced programmer, this comprehensive guide, now in its 3rd edition, will equip you with the knowledge and skills to master OpenCV 4, Python 3, and the techniques required for advanced computer vision applications. This book emphasizes hands-on learning, allowing you to quickly grasp the concepts and put them into practice. You'll start by exploring the basics of computer vision, learning the fundamentals and building a solid foundation. From there, you'll progress to more advanced topics, including deep learning with OpenCV 4, image processing, and machine learning for computer vision. Throughout the book, you'll find practical examples and code snippets that demonstrate how to implement the techniques and algorithms discussed.

You'll learn to tackle real-world challenges, such as object detection, face recognition, and image segmentation, using OpenCV 4 and Python 3. With "Learning OpenCV 4 Computer Vision with Python 3," you'll have a valuable resource at your fingertips. Whether you're a computer vision enthusiast, a machine learning expert, or a professional developer looking to enhance your skills, this book is essential for anyone interested in pushing the boundaries of computer vision. Revolutionize your understanding of computer vision and unlock its potential with OpenCV 4 and Python 3. Get your copy of "Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition" now, and embark on an exciting journey into the world of computer vision.

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Customer Questions & Answers

  • Question: What is 'Learning OpenCV 4 Computer Vision with Python 3rd ed.' about?

    Answer: This book serves as a comprehensive guide to computer vision techniques and applications using OpenCV 4 and Python. It covers fundamental concepts such as image processing, object detection, and machine learning integration. Each chapter includes practical examples and code snippets that allow readers to develop hands-on skills, making it suitable for both students and professionals in the field.
  • Question: Who is the intended audience for this book?

    Answer: The book is tailored for beginners with no prior experience in computer vision, as well as experienced developers looking to deepen their understanding of OpenCV. It is particularly beneficial for students in engineering or computer science disciplines, hobbyists, and industry professionals eager to apply practical vision techniques in projects ranging from robotics to automation.
  • Question: Do I need prior programming experience to start this book?

    Answer: While some familiarity with Python is advantageous, extensive programming experience is not mandatory. The book introduces concepts step-by-step, enabling readers to learn as they progress. Beginners can gain confidence while tackling practical examples, ultimately allowing them to apply Python and OpenCV in real-life applications like automation or AI development.
  • Question: What type of projects can I build using the knowledge from this book?

    Answer: Readers can build a range of exciting projects, such as facial recognition systems, image classification applications, or augmented reality experiences. The book provides the foundational knowledge necessary to implement both basic and complex computer vision tasks, empowering you to explore innovative ideas in various domains like robotics, medical imaging, and surveillance.
  • Question: Is there any supplementary material provided with the book?

    Answer: Yes, the book comes with access to a companion GitHub repository, which features the source code for all examples covered in the chapters. This repository allows you to experiment with the code and encourages further learning through modification and exploration of advanced concepts, enriching your practical experience.
  • Question: What are some key topics covered in the book?

    Answer: Key topics include image processing fundamentals, contour detection, deep learning models for object detection, camera calibration, and augmented reality. By diving into these subjects, readers will grasp essential principles of computer vision and how to apply them using the OpenCV library effectively, ensuring a well-rounded understanding of the field.
  • Question: Can this book help me prepare for a career in computer vision?

    Answer: Absolutely! This book provides essential skills and knowledge necessary for a successful career in computer vision and AI. With thorough insights into practical applications and theoretical concepts, you can develop a strong portfolio of projects that showcase your expertise, making you more competitive in the job market within tech and research sectors.
  • Question: What programming language is primarily used in this book?

    Answer: The book primarily utilizes Python to illustrate various OpenCV functionalities. Python’s simplicity and readability make it an ideal language for beginners, while also offering advanced capabilities for experienced programmers. By focusing on this language, readers can quickly grasp the programming aspects of computer vision and apply them efficiently in diverse applications.
  • Question: Where can I buy 'Learning OpenCV 4 Computer Vision with Python 3rd ed.' in Anguilla?

    Answer: You can easily purchase 'Learning OpenCV 4 Computer Vision with Python 3rd ed.' on Ubuy, which provides a seamless shopping experience for this excellent resource. Ubuy often features a variety of offerings and convenient payment options, making it a reliable choice for acquiring tech books tailored to your learning needs.
  • Question: Is this edition significantly different from the previous ones?

    Answer: Yes, the 3rd edition includes updated content reflecting the latest developments in the OpenCV library, additional chapters on current technologies, and enhanced practical examples using recent Python capabilities. These improvements ensure that readers are learning the most relevant and up-to-date techniques in computer vision, making it an essential resource for anyone interested in this field.

Computer Vision & Pattern Recognition Editorial Review

The Learning OpenCV 4 Computer Vision with Python 3 book receives overall positive reviews from readers. However, there are some critiques on its teaching approach, particularly on the lack of explanation regarding certain details that could be relevant in using OpenCV, such as converting images to and from byteArrays and the importance of understanding image shape. Nevertheless, the book is well-written and engaging with excellent examples that cover all major topics under the OpenCV umbrella. The book's approach to building a suite of modules is also helpful to facilitate expansion of the program later. Some readers appreciate the guidance provided in detecting custom objects, while others are disappointed with the unclear explanations of certain algorithms. The last few chapters are noted to be somewhat fast-paced, and the suggestion is made to expand them in future versions. Despite some difficulties in finding and downloading public training datasets, the book is still Considered one of the best OpenCV resources available, recommended for those seeking to learn OpenCV.

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Pros

  • Well-written and engaging
  • Excellent examples that cover all major topics under the OpenCV umbrella
  • Provides guidance on building a suite of modules, including detecting custom objects
  • Recommended for those seeking to learn OpenCV

Cons

  • Lack of explanation regarding certain details that could be relevant in using OpenCV

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Features & Benefits

  • Learn OpenCV 4 and Python 3 for computer vision and machine learning.
  • Build powerful applications using concise code.
  • Understand the fundamental concepts of image processing, object classification, and 2D and 3D tracking.
  • Tackle popular challenges such as face detection and recognition, 3D tracking, and augmented reality.
  • Develop skills in machine learning models, including SVMs, ANNs, and DNNs.
  • Execute real-world computer vision projects.

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