Computer Vision Projects with OpenCV and Python 3: Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow
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Computer Vision Projects with OpenCV and Python 3: Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow
Gain a working knowledge of advanced machine learning and explore Python's powerful tools for extracting data from images and videos
Computer Vision Projects with OpenCV and Python 3: Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow
منتج #: 13078226

Computer Vision Projects with OpenCV and Python 3: Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow

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منتج #: 13078226

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أبرز ما يلفت الانتباه

Hands-on Projects
Engages learners with diverse, practical computer vision projects that enhance understanding of OpenCV and Python, bridging theory with real-world applications.
Comprehensive Guidance
Provides step-by-step instructions and detailed explanations, making it accessible for beginners while also offering valuable insights for experienced developers.
Community Support
Connects learners with an active community for troubleshooting and inspiration, fostering collaborative learning and problem-solving in the field of computer vision.

تفاصيل المنتج

Build interactive computer vision projects using OpenCV, Python, and TensorFlow. Learn machine learning techniques and implement six end-to-end projects. Shop now at Ubuy Chad.
  • Gain a working knowledge of advanced machine learning and explore Python's powerful tools for extracting data from images and videosKey Features: - Implement image classification and object detection using machine learning and deep learning- Perform image classification, object detection, image segmentation, and other Computer Vision tasks- Crisp content with a practical approach to solving real-world problems in Computer VisionBook Description: Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems.With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features, and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google's Tesseract software, and tracking human body poses using DeeperCut within TensorFlow.By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries.What You Will Learn: - Install and run major Computer Vision packages within Python- Apply powerful support vector machines for simple digit classification- Understand deep learning with TensorFlow- Build a deep learning classifier for general images- Use LSTMs for automated image captioning- Read text from real-world images- Extract human pose data from imagesWho this book is for: Python programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.
Publisher Packt Publishing
Publication date December 28, 2018
Language English
Print length 182 pages
ISBN-10 178995455X
ISBN-13 978-1789954555
Item Weight 11.4 ounces (323.19 grams)
Dimensions 7.5 x 0.41 x 9.25 inches (19.1 x 1 x 23.5 cm)

من يجب أن يشتري؟

Suitable For
  • Beginners to CV

    Ideal for individuals new to computer vision, providing practical projects to build foundational skills with OpenCV and Python.

  • Students in Tech

    Great for students studying computer science or engineering who want to enhance their understanding through hands-on projects.

  • Hobbyist Developers

    Perfect for hobbyists looking to explore and experiment with computer vision applications in personal projects or tech interests.

Not Suitable For
  • Expert Users

    Advanced users may find the content too basic and not sufficiently challenging to engage with their skills.

وصف المنتج

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أسئلة العملاء & الإجابات

  • سؤال: What is OpenCV and why is it used in computer vision projects?

    إجابه: OpenCV (Open Source Computer Vision Library) is a powerful library aimed at real-time computer vision. It's widely used due to its comprehensive suite of tools for image and video analysis. With support for various programming languages, including Python 3, OpenCV allows developers to implement complex algorithms for tasks like object detection, recognition, and image segmentation. Practically, a developer might use OpenCV to create an application that identifies and tracks faces in security video feeds.
  • سؤال: Can I build a real-time object detection system using OpenCV and Python?

    إجابه: Yes, you can build a real-time object detection system using OpenCV and Python. By leveraging pre-trained models and OpenCV’s robust features, you can create applications that analyze video streams to detect and track objects dynamically. For instance, a retail business might use such a system to monitor customer behavior and optimize store layouts based on tracked movements.
  • سؤال: What are some common projects I can create with OpenCV and Python?

    إجابه: Common projects include facial recognition systems, gesture recognition applications, augmented reality experiences, and image filtering tools. Each project allows you to explore different aspects of computer vision while honing your coding skills. For instance, a simple project could involve creating a motion detector that sends alerts when movement is detected in a designated area using video feeds.
  • سؤال: Is prior programming knowledge required to work on OpenCV projects?

    إجابه: Some programming experience is beneficial, as working with OpenCV involves understanding Python and basic programming concepts. However, many tutorials cater to beginners, providing a step-by-step approach. For example, a new learner can start with a basic image manipulation project before advancing to more complex tasks like facial recognition, gradually building confidence and expertise.
  • سؤال: What hardware do I need for running OpenCV projects?

    إجابه: You can run OpenCV projects on standard personal computers or laptops with a decent CPU and RAM. For more demanding tasks, such as real-time video processing or machine learning models, a dedicated GPU can enhance performance. For example, a gaming laptop with a strong graphics card can improve the execution speed for complex computer vision tasks, making development more efficient.
  • سؤال: What are the advantages of using Python with OpenCV?

    إجابه: Python is a versatile programming language that enhances OpenCV by providing a simple syntax, extensive libraries, and a supportive community. This makes it easier to implement complex algorithms and visualize data. For instance, using Python, a developer can quickly prototype and test computer vision applications, such as a motion detection system, allowing for rapid iteration and development.
  • سؤال: How does OpenCV handle image processing tasks?

    إجابه: OpenCV provides a plethora of built-in functions for various image processing tasks, including filtering, transformations, and morphological operations. It processes images by applying these functions effectively to manipulate pixel data. A common use case is using OpenCV to enhance the quality of images in medical imaging, where clarity can be crucial for analysis.
  • سؤال: What software tools can complement OpenCV in a project?

    إجابه: Tools such as Jupyter Notebook, NumPy, and Matplotlib significantly complement OpenCV projects. Jupyter allows for interactive coding, NumPy provides efficient numerical operations, and Matplotlib enables data visualization. For instance, in a project that involves detecting edges in images, you can use Matplotlib to visualize the results in real-time, making it easier to tune parameters and improve outcomes.
  • سؤال: Where can I find tutorials and resources for OpenCV and Python projects?

    إجابه: Numerous online platforms offer rich resources for learning OpenCV and Python. Websites like YouTube, Coursera, and the official OpenCV documentation provide comprehensive tutorials that guide beginners and experienced developers alike. For instance, a beginner might follow a step-by-step video series on YouTube that covers basic image processing techniques, leading to more advanced applications.
  • سؤال: Where can I buy Computer Vision Projects with OpenCV and Python 3 in Chad?

    إجابه: You can buy Computer Vision Projects with OpenCV and Python 3 on Ubuy. They offer a variety of resources and tools needed to kickstart your journey in computer vision, ensuring you have access to quality materials to enhance your learning and project development.

Intelligence & Semantics Editorial Review

Computer Vision Projects with OpenCV and Python 3 presents six comprehensive projects that leverage machine learning techniques using OpenCV, Python, and TensorFlow. With a print length of 182 pages published by Packt Publishing on December 28, 2018, this book serves as a valuable resource for those looking to deepen their understanding of computer vision. Readers appreciate the structured approach to projects, allowing them to learn through practical implementation. The accessible language makes it suitable for both beginners and those with some prior knowledge of programming. It's a solid choice for anyone interested in enhancing their technical skills in computer vision.

مراجعات العملاء وتقييماتهم

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إيجابيات

  • Features six comprehensive end-to-end projects
  • Integrates machine learning concepts effectively
  • Uses popular tools like OpenCV and TensorFlow
  • Clear explanations suitable for beginners
  • Well-structured project approach

سلبيات

  • Some readers may desire more advanced projects

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المميزات والفوائد

  • Implement image classification and object detection using machine learning and deep learning
  • Perform image classification, object detection, image segmentation, and other Computer Vision tasks
  • Crisp content with a practical approach to solving real-world problems in Computer Vision
  • Install and run major Computer Vision packages within Python
  • Apply powerful support vector machines for simple digit classification
  • Understand deep learning with TensorFlow

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