Gain a working knowledge of advanced machine learning and explore Python's powerful tools for extracting data from images and videos
Key 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 Vision
Book 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 images
Who 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.
Matthew Rever received his PhD. in electrical engineering from the University of Michigan, Ann Arbor. His career revolves around image processing, computer vision, and machine learning for scientific research applications. He started programming in C++, a language he still uses today, over 20 years ago, and has also used Matlab and most heavily Python in the past few years, using OpenCV, SciPy, scikit-learn, TensorFlow, and PyTorch. He believes it is important to stay up to date on the latest tools to be as productive as possible. Dr. Rever is the author of Packt's Computer Vision Projects with Python 3 and Advanced Computer Vision Projects.
