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 to be useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.
Computer Vision Projects with OpenCV and Python 3
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Computer Vision Projects with OpenCV and Python 3
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Overview of this book
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.
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Computer Vision Projects with OpenCV and Python 3
Table of Contents (9 chapters)
Preface
Free Chapter
Setting Up an Anaconda Environment
Image Captioning with TensorFlow
Reading License Plates with OpenCV
Human Pose Estimation with TensorFlow
Handwritten Digit Recognition with scikit-learn and TensorFlow
Facial Feature Tracking and Classification with dlib
Deep Learning Image Classification with TensorFlow
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