jash101 / computer-vision-with-python-3

Computer Vision with Python 3, published by Packt

Computer Vision with Python 3

This is the code repository for Computer Vision with Python 3, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.

About the Book

This book is a thorough guide for developers who want to get started with building computer vision applications using Python 3. The book is divided into five sections: The Fundamentals of Image Processing, Applied Computer Vision, Making Applications Smarter,Extending your Capabilities using OpenCV, and Getting Hands on. Throughout this book, three image processing libraries Pillow, Scikit-Image, and OpenCV will be used to implement different computer vision algorithms.

The book aims to equip readers to build Computer Vision applications that are capable of working in real-world scenarios effectively. Some of the applications that we will look at in the book are Optical Character Recognition, Object Tracking and building a Computer Vision as a Service platform that works over the internet.

Instructions and Navigation

All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter02.

The code will look like the following:

private void initialiseBluetooth() {
bluetoothManager = 
(BluetoothManager)getSystemService
(Context.BLUETOOTH_SERVICE);
bluetoothAdapter = bluetoothManager.getAdapter();
bluetoothLeScanner = bluetoothAdapter.getBluetoothLeScanner(); 
}

This book will guide you through the installation of all the tools that you need to follow the code samples. Code samples introduced in various chapters are for both Android and iOS platforms hence you will need to install the Android Studio and XCode IDEs. Since simulators lack Bluetooth functionality, hence you will need physical Android and iOS devices to run the code samples. In terms of hardware, you will be needing a Raspberry Pi for the Code Lab specific for Chapter 5, Beacons with Raspberry Pi. For Chapter 4, Designing a Personal Tracking System, and Chapter 6, Weather Monitoring Using BLE in Warehouses, you will be needing a very low cost iTag and the Texas Instruments Sensor Tag. All of the hardware can be easily procured online.

Related Products

• Learning OpenCV 3 Computer Vision with Python - Second Edition

• OpenCV: Computer Vision Projects with Python

• OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition