Learn OpenCV with Python by Examples

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 learning the concepts and techniques of computer vision through practical examples. All codes in this book are available on 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. Introduction1.1 About OpenCV1.2 Target Audients1.3 Source Codes for This Book1.4 Hardware Requirements1.5 How This Book Organized2. Installation2.1 Install on Windows2.2 Install on Ubuntu2.3 Configure PyCharm and Install OpenCV3. OpenCV Basics3.1 Load and Display Images3.2 Load and Display Videos3.3 Display Webcam3.4 Image Fundamentals3.5 Draw Shapes3.6 Draw Texts3.7 Draw an OpenCV-like Icon4. User Interaction4.1 Mouse Operations4.2 Draw Circles with Mouse4.3 Draw Polygon with Mouse4.4 Crop an Image with Mouse4.5 Input Values with Trackbars5. Image Processing5.1 Conversion of Color Spaces5.2 Resize, Crop and Rotate an Image5.3 Adjust Contrast and Brightness of an Image5.4 Adjust Hue, Saturation and Value5.5 Blend Image5.6 Bitwise Operation5.7 Warp Image5.8 Blur Image5.9 Histogram6. Object Detection6.1 Canny Edge Detection6.2 Dilation and Erosion6.3 Shape Detection6.4 Color Detection6.5 Text Recognition with Tesseract6.6 Human Detection6.7 Face and Eye Detection6.8 Remove Background6.9 Blur Background7. Machine Learning7.1 K-Means Clustering7.2 K-Nearest Neighbors7.3 Support Vector Machine7.4 Artificial Neural Network (ANN)7.5 Convolutional Neural Network (CNN)ReferencesAbout the Author