Learn OpenCV with Python by Examples: Implement Computer Vision Algorithms Provided by OpenCV with Python for Image Processing, Object Detection and Machine Learning

This book is a comprehensive guide to learning the basics of computer vision and machine learning using the powerful OpenCV library and the Python programming language. The book offers a practical, hands-on approach to learn the concepts and techniques of computer vision through practical example. All codes in this book are available at Github.Through a series of examples, the book covers a wide range of topics including image and video processing, feature detection, object detection and recognition, machine learning and deep neural networks. Each chapter includes detailed explanations of the concepts and techniques involved, as well as practical examples and code snippets that demonstrate how to implement them in Python. Throughout the book, readers will work through hands-on examples and projects, learning how to build image processing applications from scratch.Whether you are a beginner or an experienced programmer, this book provides a valuable resource for learning computer vision with OpenCV and Python. The clear and concise writing style makes it easy for readers to follow along, and the numerous examples ensure that readers can practice and apply what they have learned. By the end of the book, readers will have a solid understanding of the fundamentals of computer vision and be able to build their own computer vision applications with confidence. This book is an excellent resource for anyone looking to learn computer vision and machine learning using the OpenCV library and Python programming language.Table of Contents1. INTRODUCTION 9 1.1 About OpenCV 10 1.2 Target Audients of This Book 12 1.3 Source Codes for This Book 13 1.4 Hardware Requirements and Software Versions 14 1.5 How This Book Is Organized 152. INSTALLATION 17 2.1 Install on Windows 18 2.2 Install Python on Ubuntu 20 2.3 Configure PyCharm and Install OpenCV 223. OPENCV BASICS 30 3.1 Load and Display Images 31 3.2 Load and Display Videos 35 3.3 Display Webcam 37 3.4 Image Fundamentals 40 3.5 Draw Shapes 47 3.6 Draw Texts 53 3.7 Draw an OpenCV-like Icon 554. USER INTERACTION 58 4.1 Mouse Operations 59 4.2 Draw Circles with Mouse 62 4.3 Draw Polygon with Mouse 66 4.4 Crop an Image with Mouse 68 4.5 Input Values with Trackbars 705. IMAGE PROCESSING 76 5.1 Conversion of Color Spaces 77 5.2 Resize, Crop and Rotate an Image 82 5.3 Adjust Contrast and Brightness of an Image 88 5.4 Adjust Hue, Saturation and Value 92 5.5 Blend Image 96 5.6 Bitwise Operation 100 5.7 Warp Image 107 5.8 Blur Image 113 5.9 Histogram 1196. OBJECT DETECTION 126 6.1 Canny Edge Detection 127 6.2 Dilation and Erosion 130 6.3 Shape Detection 135 6.4 Color Detection 145 6.5 Text Recognition with Tesseract 156 6.6 Human Detection 167 6.7 Face and Eye Detection 171 6.8 Remove Background 176 6.9 Blur Background 1967. MACHINE LEARNING 203 7.1 K-Means Clustering 207 7.2 K-Nearest Neighbors 223 7.3 Support Vector Machine 244 7.4 Artificial Neural Network (ANN) 261 7.5 Convolutional Neural Network (CNN) 283INDEX 313REFERENCES 316ABOUT THE AUTHOR 318 Read more