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Python Image Processing Cookbook: Over 60 recipes to help you perform complex image processing and computer vision tasks with ease
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Python Image Processing Cookbook: Over 60 recipes to help you perform complex image processing and computer vision tasks with ease
Discover solutions to complex image processing tasks using Python tools such as scikit-image and Keras
Python Image Processing Cookbook: Over 60 recipes to help you perform complex image processing and computer vision tasks with ease
Item #: 42406013

Python Image Processing Cookbook: Over 60 recipes to help you perform complex image processing and computer vision tasks with ease

83% of respondents would recommend this to a friend

Item #: 42406013

XCD 155

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What Stands Out

Comprehensive Recipes
Offers over 60 detailed recipes covering a wide range of image processing tasks, making it easy for users to follow and implement complex techniques without prior expertise.
User-Friendly Approach
Written in an accessible format that simplifies complex concepts, allowing beginners to grasp the fundamentals of computer vision while providing advanced tips for seasoned users.
Practical Applications
Focuses on real-world applications and projects, equipping readers with hands-on experience for immediate integration of image processing skills in various industries and use cases.

Product Details

Buy the Python Image Processing Cookbook on Ubuy Montserrat and perform complex image processing and computer vision tasks with ease. Over 60 recipes available!
  • Over 60 recipes to help you perform complex image processing and computer vision tasks with ease
  • Utilize Python tools such as scikit-image and Keras to solve real-world image processing problems
  • Explore concepts like machine learning, deep learning, and neural networks for image processing
  • Implement supervised and unsupervised machine learning algorithms for image processing
  • Apply image segmentation, registration, and restoration techniques on medical images
  • Suitable for image processing engineers, computer vision engineers, and anyone interested in image processing techniques
Publisher Packt Publishing
Publication date April 17, 2020
Language English
Print length 438 pages
ISBN-10 1789537142
ISBN-13 978-1789537147
Item Weight 1.65 pounds (750 grams)
Dimensions 7.5 x 0.99 x 9.25 inches (19.1 x 2.5 x 23.5 cm)

Who Should Buy?

Suitable For
  • Data Scientists

    Ideal for data scientists looking to enhance image data analysis and manipulation using Python libraries effectively.

  • Beginner Programmers

    Perfect for beginners aiming to learn image processing concepts through practical, hands-on recipes and examples.

  • Machine Learning Enthusiasts

    Beneficial for those interested in integrating image processing techniques into machine learning projects to enhance model performance.

Not Suitable For
  • Advanced Experts

    Not suitable for advanced users seeking in-depth theoretical understanding or highly specialized techniques in image processing.

Product Description

Python Image Processing Cookbook: Over 60 recipes to help you perform complex image processing and computer vision tasks with ease

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Customer Questions & Answers

  • Question: What topics are covered in the Python Image Processing Cookbook?

    Answer: The Python Image Processing Cookbook covers a diverse range of topics related to image processing and computer vision. Key subjects include image manipulation, filtering techniques, object detection, and feature extraction. Each recipe is designed to address specific challenges or tasks, making it easy to find solutions applicable to your projects. Whether you are a beginner or an experienced developer, the cookbook provides practical examples that you can immediately implement in areas such as graphic design, augmented reality, or machine learning.
  • Question: Who is the target audience for the Python Image Processing Cookbook?

    Answer: The target audience for the Python Image Processing Cookbook includes software developers, data scientists, and computer vision enthusiasts. Ideal readers are those who seek to enhance their skills in image processing using Python. With recipes tailored for various levels of expertise, the cookbook can serve as a great learning tool for students and professionals looking to delve into real-world applications of image processing, such as automating photo editing or building vision-based applications.
  • Question: What programming knowledge do I need to use the Python Image Processing Cookbook?

    Answer: To effectively use the Python Image Processing Cookbook, a basic understanding of the Python programming language is essential. Familiarity with libraries such as NumPy and OpenCV will greatly enhance your ability to leverage the recipes provided. Additionally, knowledge of fundamental programming concepts such as loops, functions, and data types is beneficial. This foundational understanding will enable you to customize the recipes for your unique projects, ensuring more efficient workflows in applications ranging from scientific research to e-commerce visual content.
  • Question: Are there any prerequisites before starting with the Cookbook?

    Answer: While there are no strict prerequisites, it is recommended that users have prior experience with Python programming and a basic understanding of image processing concepts. Familiarity with relevant libraries can also enhance your experience. Knowing how to manipulate images using other software can help solidify the concepts covered in the cookbook, allowing you to apply the techniques more effectively. Whether you are working on enhancing image quality for a website or developing machine learning models, these skills will add value.
  • Question: Can the recipes be adapted for real-time image processing tasks?

    Answer: Absolutely, many of the recipes in the Python Image Processing Cookbook can be adapted for real-time image processing tasks. Techniques such as object recognition and tracking can be implemented in real-time applications, like video surveillance or user-interactive augmented reality experiences. By tweaking the provided code examples and utilizing libraries optimized for speed, you can create dynamic solutions that update in response to live data, making them ideal for gaming or automated monitoring systems.
  • Question: Is the Python Image Processing Cookbook suitable for beginners?

    Answer: Yes, the Python Image Processing Cookbook is suitable for beginners, especially those who have a basic grasp of Python and want to learn about image processing. The book is structured around recipes, each step clearly outlined to guide novices through diverse challenges. This format enables beginners to build confidence as they apply what they learn to progressively more complex problems. For anyone interested in digital art, photography, or technology, this could be a beneficial resource to start enhancing their programming skills.
  • Question: What types of projects can I implement using the Cookbook?

    Answer: The projects you can implement using the Python Image Processing Cookbook range significantly due to the extensive recipes provided. Examples include developing applications that reduce image noise, create artistic filters, perform facial recognition, and automate image editing processes. These projects are not only valuable for personal creative endeavors but also serve practical purposes in fields like marketing, where high-quality visuals can enhance product presentations. Additionally, businesses can automate tasks, improving efficiency and productivity.
  • Question: What is unique about this Cookbook compared to other image processing resources?

    Answer: The uniqueness of the Python Image Processing Cookbook lies in its practical approach. Unlike many resources that focus solely on theoretical concepts, this book is centered around over 60 ready-to-use recipes that solve specific problems in image processing. Each recipe includes detailed explanations and code, which means readers can quickly implement solutions rather than getting bogged down in theory. This hands-on methodology makes learning more engaging and applicable, especially for those in fast-paced industries requiring immediate results.
  • Question: How do I get support when using the recipes from the Cookbook?

    Answer: Support while using the recipes from the Python Image Processing Cookbook can be approached through various channels. Online forums, dedicated Python and image processing communities, and social media groups can provide advice and solutions from fellow enthusiasts and professionals. Additionally, GitHub repositories associated with the book often feature discussions, bug reports, and collaborative troubleshooting. Engaging with these communities not only enhances your learning curve but also connects you with like-minded individuals tackling similar challenges.
  • Question: Where can I buy the Python Image Processing Cookbook in Montserrat?

    Answer: You can purchase the Python Image Processing Cookbook in Montserrat from Ubuy. Ubuy is a reliable online retailer that offers a wide selection of books, including specialized ones on programming and image processing. They cater to various locations, which ensures that you can conveniently access this essential resource for enhancing your skills in image processing and computer vision.

Intelligence & Semantics Editorial Review

This book contains a collection of algorithms for computer vision, but it has poor graphical and printing quality, which makes it difficult to appreciate the processing technique being demonstrated. The book is only a cookbook that does not provide deep details or explain algorithms properly. However, the content is well-structured, with compact chapters. The "How it works" section is also poorly explained and does not provide any background on signal processing terms. There are unexplained figures that seem to fill pages unnecessarily. The book also uses many different frameworks and does not compare the results of different algorithms. It does not give any indication of when to use or not to use a certain algorithm. The font size is huge, which is distracting and lengthens the page numbers, and the images are only black and white with low resolution. The book is not recommended for purchase as a printed version. However, it could still be used as a quick reference for finding a Python implementation of image processing tool and to see which algorithms are available.

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Pros

  • Clearly structured content
  • Compact chapters

Cons

  • Poor graphical and printing quality

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Features & Benefits

  • Over 60 recipes to help you perform complex image processing and computer vision tasks with ease
  • Learn popular concepts such as machine learning, deep learning, and neural networks for image processing
  • Explore and implement various image processing techniques using Python tools

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