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.
Author(s): James Chen
Year: 2023
Language: English
Pages: 316
Introduction
About OpenCV
Target Audients of This Book
Source Codes for This Book
Hardware Requirements and Software Versions
How This Book Is Organized
Installation
Install on Windows
Install Python on Windows 10
PyCharm, the Integrated Development Environment
Install Python on Ubuntu
Install Python on Ubuntu
Install PyCharm on Ubuntu
Configure PyCharm and Install OpenCV
Create a New Python Project
Install and Upgrade OpenCV and Libraries
Load the Project Files
Hello OpenCV
OpenCV Basics
Load and Display Images
Load Color Images
Load Grayscale Images
Convert Color Image to Grayscale
Load and Display Videos
Display Webcam
Image Fundamentals
Pixels
BGR Color Space and Channels
HSV Color Space and Channels
Draw Shapes
Create an Empty Canvas
Draw a Line
Draw Rectangles, Circles, Ellipses and Polylines
Draw Texts
Draw an OpenCV-like Icon
User Interaction
Mouse Operations
Draw Circles with Mouse
Draw Polygon with Mouse
Crop an Image with Mouse
Input Values with Trackbars
Image Processing
Conversion of Color Spaces
Convert BGR to Gray
Convert Grayscale to BGR
Convert BGR to HSV
Convert HSV to BGR
Resize, Crop and Rotate an Image
Adjust Contrast and Brightness of an Image
Adjust Hue, Saturation and Value
Blend Image
Bitwise Operation
Warp Image
Blur Image
What is Gaussian Blur
Gaussian Blur
Median Blur
Histogram
About Histogram
Histogram for Grayscale Images
Histogram for Color Images
Object Detection
Canny Edge Detection
Dilation and Erosion
Shape Detection
Pre-processing for Shape Detection
Find Contours
Detect the Type, Area and Perimeter of the Shapes
Other Contour Features
Color Detection
Find Color from an Image
Find Color Labels
Text Recognition with Tesseract
Install and configure Tesseract
Text Recognition
Human Detection
Human Detection from Pictures
Human Detection from Videos
Face and Eye Detection
Remove Background
Remove Background by Color
Remove Background by Contour
Remove Background by Machine Learning
Remove Background by Mask
Blur Background
Machine Learning
K-Means Clustering
What is K-Means Clustering
Color Quantization
Handwritten Digits Grouping
K-Nearest Neighbors
What is K-Nearest Neighbors
KNN Evaluation
Recognize Handwritten Digits with KNN
Support Vector Machine
What is Support Vector Machine
Recognize Handwritten Digits with SVM
IRIS Dataset Classification
Artificial Neural Network (ANN)
What is an Artificial Neural Network (ANN)?
Activation Functions
Recognize Handwritten Digits with ANN
Convolutional Neural Network (CNN)
What is a Convolutional Neural Network
Convolution Layer
Pooling Layer
Fully Connected Layer
CNN Architecture
Build a CNN Model with Tensorflow/Keras
Popular CNN Architectures
References
About the Author
