To get the most out of this book

All of our code use Python 3.8, which is available on a variety of operating systems, such as Windows, GNU Linux, macOS, and others. We have made an effort to use only libraries that are available on these three operating systems. We will go over the exact versions of each of the dependencies we have used, which can be installed using pip (Python's dependency management system). If you have trouble getting any of these working, we have Dockerfiles available with which we have tested all the code in this book, which we cover in Appendix B, Setting Up a Docker Container.

Here is a list of dependencies that we have used, with the chapters they were used in:

Software required	Version	Chapter number	Download links to the software
Python	3.8	All	https://www.python.org/downloads/
OpenCV	4.2	All	https://opencv.org/releases/
NumPy	1.18.1	All	http://www.scipy.org/scipylib/download.html
wxPython	4.0	1, 4, 8	http://www.wxpython.org/download.php
matplotlib	3.1	4, 5, 6, 7	http://matplotlib.org/downloads.html
SciPy	1.4	1, 10	http://www.scipy.org/scipylib/download.html
rawpy	0.14	5	https://pypi.org/project/rawpy/
ExifRead	2.1.2	5	https://pypi.org/project/ExifRead/
TensorFlow	2.0	7, 9	https://www.tensorflow.org/install

In order to run the codes, you will need a regular laptop or Personal Computer (PC). Some chapters require a webcam, which can be either an embedded laptop camera or an external one. Chapter 2, Hand Gesture Recognition Using a Kinect Depth Sensor also requires a depth sensor that can be either a Microsoft 3D Kinect sensor or any other sensor, which is supported either by the libfreenect library or OpenCV, such as ASUS Xtion.

We have tested this using Python 3.8 and Python 3.7, on Ubuntu 18.04.

If you already have Python on your computer, you can just get going with running the following on your terminal:

$ pip install -r requirements.txt

Here, requirements.txt is provided in the GitHub repository of the project, and has the following contents (which is the previously given table in a text file):

wxPython==4.0.5
numpy==1.18.1
scipy==1.4.1
matplotlib==3.1.2
requests==2.22.0
opencv-contrib-python==4.2.0.32
opencv-python==4.2.0.32
rawpy==0.14.0
ExifRead==2.1.2
tensorflow==2.0.1

Alternatively, you can follow the instructions in Appendix B, Setting Up a Docker Container, to get everything working with a Docker container.

Download the example code files

You can download the example code files for this book from your account at www.packt.com. If you purchased this book elsewhere, you can visit www.packtpub.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

1. Log in or register at www.packt.com.
2. Select the Support tab.
3. Click on Code Downloads.
4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

• WinRAR/7-Zip for Windows
• Zipeg/iZip/UnRarX for Mac
• 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/OpenCV-4-with-Python-Blueprints-Second-Edition. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Code in Action

Code in Action videos for this book can be viewed at http://bit.ly/2xcjKdS.

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: http://static.packt-cdn.com/downloads/9781789801811_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "We will use argparse as we want our script to accept arguments."

A block of code is set as follows:

import argparse

import cv2
import numpy as np

from classes import CLASSES_90
from sort import Sort

Any command-line input or output is written as follows:

$ python chapter8.py collect

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Select System info from the Administration panel."

Warnings or important notes appear like this.

Tips and tricks appear like this.