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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
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MYR 238
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Gain a working knowledge of advanced machine learning and explore Python's powerful tools for extracting data from images and videos
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Maklumat produk
- 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) |
Who Should Buy?
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Beginners to CV
Ideal for individuals new to computer vision, providing practical projects to build foundational skills with OpenCV and Python.
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Students in Tech
Great for students studying computer science or engineering who want to enhance their understanding through hands-on projects.
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Hobbyist Developers
Perfect for hobbyists looking to explore and experiment with computer vision applications in personal projects or tech interests.
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Expert Users
Advanced users may find the content too basic and not sufficiently challenging to engage with their skills.
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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.
Customer Reviews & Ratings
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Kebaikan
- 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
Keburukan
- Some readers may desire more advanced projects
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MYR 238
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Ciri & Faedah
- 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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