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Java Image Processing Recipes: With OpenCV and JVM
Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub via the book’s product page, located at www.apress.com/9781484234648 . For more detailed information, please visit http://www.apress.com/source-code .
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Introduction
My father is a dentist. When I was in my early childhood, he used to repeat the same sentence over and over again, which as far as I can remember and translate properly now was something like:
“Son, get the right tool for the job.”
And as he was looking at me trying to wash the car with the wrong washing product and spending twice the amount of time that I should have, I knew somewhere deep inside of me that he was right.
He did not use a screwdriver to pull out teeth from his patients, and he had what seemed like twenty different brushes to clean each type of tooth. I even thought it was funny at the time.
Fast-forward thirty years later; I was talking about this book with him and he added:
“Well, son, you know, it’s not only about the right tool, it’s about the right tool at the right time.”
And so, this is the philosophy guiding this book.
OpenCV, the computer vision library, has always been one of the tools to work on imaging- and vision-related projects, even
more so with every improvement in AI and neural networks. But OpenCV was always taking some time to get the right libraries, and the right build tools, and the right build settings, and so forth.
The vision of the Clojure wrapper Origami is to bring you all the power of OpenCV to your hands almost instantly, along with a pleasurable syntax. This way we hope you can focus and spend your time entirely on the job, not on the tool.
Chapter 1 will introduce you to pure OpenCV on the JVM using Java, Scala, and Kotlin and present some of their shortcomings.
Chapter 2 will present Origami, the Clojure wrapper, and how to use it to perform simple image manipulation.
Chapter 3 will get you up to speed with more advanced concepts of image manipulation, like shape inding, but still in a pleasant syntax.
Finally, Chapter 4 moves to video analysis, with shape inding, transformations, and various techniques to analyze real-time streams with ease.
The original version of the book FM was revised. The changes have been made in the editorial section of the copyright page.
Acknowledgments
It’s been the most amazing typing race of my life to get this book out on time, and to beat time and the odds, I got support from so many people that it would take another book just to write the list of names. So …
Thank you to all my family, brother, sister, friends, Abe-san, all my soccer friends, people still having Guinness pints in Ireland (keep one for me!), the awesome people in America (who sometimes send LP records… when I need them the most), Sawada-san, Chris and the Biners, my French friends (always there for support even when not being asked for it), publisher Apress, Divya for never being impressed and kicking my butt on a regular basis, and … the people deep in my heart for your NEVERENDING support. I never could have inished this without you. I appreciate it so much.
And, of course… thank you to my two beautiful daughters, Mei and Manon, for keeping up and always doing their best even during hard times. You simply rock! I love you.
TABLE OF CONTENTS
Chapter 1: OpenCV on the JavaVM
1-1 Getting Started with Leiningen
Problem Solution
How it works
1-2 Writing Your First OpenCV Java Program Problem
Solution
How it works
1-3 Automatically Compiling and Running Code Problem Solution
How it works
1-4 Using a Better Text Editor Problem
Solution
How it works
1-5 Learning the Basics of the OpenCV Mat Object Problem Solution
How it works
1-6 Loading Images from a File Problem
Solution
How it works
1-7 Saving Images into a File
Problem
Solution
How it works
1-8 Cropping a Picture with Submat
Problem
Solution
How it works
1-9 Creating a Mat from Submats
Problem
Solution
How it works
1-10 Highlighting Objects in a Picture
Problem
Solution
How it works
1-11 Using a Canny Result as a Mask
Problem Solutions
How it works
1-12 Detecting Edges with Contours
Problem
Solution
How it works
1-13 Working with Video Streams
Problem
Solution
How it works
1-14 Writing OpenCV Code in Scala
Problem
Solution
How it works
1-15 Writing OpenCV Code in Kotlin
Problems
Solutions
How it works
Chapter 2: OpenCV with Origami
2-1 Starting to Code with Origami
Problem
Solution
How it works
2-2 Working with Mats
Problem
Solution
How it works
2-3 Loading, Showing, Saving Mats
Problem
Solution
How it works
2-4 Working with Colors, ColorMaps, and ColorSpaces
Problem
Solution
How it works
2-5 Rotating and Transforming Mats
Problem
Solution
How it works
2-6 Filtering Mats
Problem
Solution
How it works
2-7 Applying Simple Masking Techniques
Problem
Solution
How it works
2-8 Blurring Images
Problem
Solution
How it works
Chapter 3: Imaging Techniques
3-1 Playing with Colors
Problem
Solution
How it works
3-2 Creating Cartoons
Problem
Solution
How it works
3-3 Creating Pencil Sketches
Problem
Solution
How it works
3-4 Creating a Canvas Effect
Problem Solution
How it works
3-5 Highlighting Lines and Circles
Problem Solution
How it works
3-6 Finding and Drawing Contours and Bounding Boxes
Problem
Solution
How it works
3-7 More on Contours: Playing with Shapes
Problem
Solution
How it works
3-8 Moving Shapes
Problem
Solution
How it works
3-9 Looking at Trees
Problem Solution
How it works
3-10 Detecting Blur
Problem
Solution
How it works
3-11 Making Photomosaics
Problem Solution
How it works
Chapter 4: Real-Time Video
4-1 Getting Started with Video Streaming
Problem
Solution
How it works
4-2 Combining Multiple Video Streams
Problem
Solution
How it works
4-3 Warping Video
Problem
Solution
How it works
4-4 Using Face Recognition
Problem
Solution
How it works
4-5 Dif ing with a Base Image
Problem
Solution
How it works
4-6 Finding Movement
Problem
Solution
How it works
4-7 Separating the Foreground from the Background Using Grabcut
Problem
Solution
How it works
4-8 Finding an Orange in Real Time
Problem
Solution
How it works
4-9 Finding an Image Within the Video Stream
Problem
Solution
How it works
Index
ABOUT THE AUTHOR AND ABOUT THE TECHNICAL REVIEWER
ABOUT THE AUTHOR
Nicolas Modrzyk
is currently Chief Technical Of icer of Karabiner Software and a leader of development teams.
He is also an active contributor to the open source software community. As a developer and technical consultant, Nico has been involved over many years in designing large-scale server applications for a video conferencing company, managing enormous clusters of databases through high-performance middleware developed from scratch, enabling Japanese leaders with content management and process management systems, and pushing the boundaries of business processes for leading Asian companies.
Nico is an ardent advocate of Agile methods and is focused on getting the job done right to satisfy clients. He also loves to push friends and team members to challenge themselves and reach their goals. He has lived by those empowering standards in various countries, including France, America, Ireland, Japan,
China, and India. Nico is also the author of a few other books on the Clojure programming language, in both English and Japanese.
He is currently based in Tokyo, Japan, where he is often found after hours playing soccer, hiking, performing live concerts with his guitar, and enjoying life with friends and colleagues.
ABOUT THE TECHNICAL REVIEWER
Aakash Kag is an AI developer at Manacola Private Ltd. He has two years of experience in big data analytics. He is a postgraduate in Computer Science with a specialization in Big Data Analytics. Aakash has also made contributions to the Microsoft bot builder.
Currently, Aakash is working on problems related to Conversational Bots and Natural Language Understanding.
He is passionate about Machine Learning meetups, where he often presents talks.
A few years ago, while on a trip to Shanghai, a very good friend of mine bought me a massive book on OpenCV. It had tons of photography manipulation, real–time video analysis samples, and in-depth explanations that were very appealing, and I just could not wait to get things up and running on my local environment.
OpenCV, as you may know, stands for Open Source Computer Vision ; it is an open source library that gives you ready-to-use implementations of advanced imaging algorithms, going from simple-to-use but advanced image manipulations to shape recognition and real-time video analysis spy powers.
The very core of OpenCV is a multidimensional matrix object named Mat. Mat is going to be our best friend all along this book. Input objects are Mat, operations are run on Mat, and the output of our work is also going to be Mat. 1
Mat , even though it is going to be our best friend, is a C++ object, and as such, is not the easiest of friends to bring and show around. You have to recompile, install, and be very gentle about the new environment almost anywhere you take him.
But Mat can be packaged.
Mat, even though he is a native (i.e., runs natively), can be dressed to run on the Java Virtual Machine almost without anyone noticing.
This irst chapter wants to get you introduced to work with OpenCV with some of the main languages of the Java Virtual Machine, namely Java of course, but also the easier-to-read Scala and the Google-hyped Kotlin.
To run all these different languages in a similar fashion, you will irst get (re-?)introduced to a Java build tool named leiningen and then you will move on to use simple OpenCV functions with it.
The road of this irst chapter will take you to the door of the similarly JVM-based language Clojure, which will give your OpenCV code instant visual feedback for great creativity. That will be for Chapter 2.
1.1 Getting Started with Leiningen PROBLEM
You remember the write-once-run-everywhere quote, and you would like to compile Java code and run the Java program in an easy and portable manner across different machines. Obviously, you can always revert to using the plain javac command to compile Java code, and pure Java on the command line to run your compiled code , but we are in the 21 century, and hey, you are looking for something more.
Whatever the programming language, setting up your working environment by hand is quite a task, and when you are done, it is hard to share with other people.
Using a build tool, you can de ine in simple ways what is required to work on your project, and get other users to get started quickly.
You would like to get started with an easy-to-work-with build tool.
SOLUTION
Leiningen is a build tool targeting (mostly) the JavaVM. It is similar in that sense to other famous ones like (Remember? The) Ant, (Oh My God) Maven, and (it used to work) Gradle.
Once the leiningen command is installed, you can use it to create new JavaVM projects based on templates, and run them without the usual headaches.
This recipe shows how to install Leiningen quickly and run your irst Java program with it.
HOW IT WORKS
You will start by simply installing Leiningen where you need it, and then creating a blank Java project with it.
NOTE Installing Leiningen requires Java 8 to be installed on your machine. Note also that due to the fact that Java 9 is solving old problems by breaking current solutions, we will choose to keep Java 8 for now.
InstallingLeiningen
The Leiningen web site itself is hosted and can be found at https://leiningen.org/
At the top of the Leiningen page, you can ind the four easy steps to install the tool manually yourself. So here it goes, on macOS and Unix :
2 . Place it on your C:/Windows/System32 folder, using admin permission
3 . Open a command prompt and run it, lein, and it will download the self-install package
On Unix , you can almost always use a package manager. Brew, on macOS, has a package for leiningen.
On Windows , there is also a good Windows installer, located at https://djpowell.github.io/leiningenwin-installer/ .
If you are a Chocolatey fan, Windows has a package for Chocolatey as well: https://chocolatey.org/packages/Lein .
If you inished the install process successfully on a terminal or command prompt, you should be able to check the version of the installed tool. On the irst run, Leiningen downloads its own internal dependencies, but any other subsequent runs will regularly be fast.
NikoMacBook% lein -v
Leiningen 2.7.1 on Java 1.8.0 144 Java HotSpot(TM) 64Bit Server VM
Leiningen mainly works around a text ile, named project.clj , where the metadata, dependencies, plug-ins, and settings for those projects are de ined in a simple map.
When you execute commands on the project calling the lein command, lein will look into that project.clj to ind the relevant information it needs regarding that project.
Leiningen comes with ready-to-use project templates, but in order to understand them properly, let’s irst walk through a irst example step by step.
For a leiningen Java project, you need two iles:
One that describes the project, project clj
One ile with some Java code in it, here Hello.java
A irst project simple directory structure looks like this: . ├ java │ └ Hello.java └ project.clj
1 directory, 2 files
For peace of mind, we will keep the code of this irst Java example pretty simple.
public class Hello { public static void main(String[] args) { System.out.println("beginning of a journey"); } }
Now let’s see the content of the text ile named project.clj in a bit of detail:
This is actually Clojure code, but let’s simply think of it as a domain speci ic language (DSL), a language to describe a project in simple terms.
For convenience, each term is described in Table 1-1.
Table 1-1 Leiningen Project Metadata
Word Usage
Defproject
Entry point to de ine a project
Hellojava The name of the project
0.1 A string describing the version
:java-sourcepaths
:dependencies
[[org clojure/cl ojure “1 8 0”]]
:main
A list of directories relative to the project folder, where you will put Java code iles
The list of external libraries and their versions needed to run the project
By default, the list contains Clojure, which is needed to run leiningen You will put OpenCV libraries here later on
The name of the Java class that will be executed by default
Now go ahead and create the preceding directory and ile structure, and copy-paste the content of each ile accordingly.
Once done, run your irst leiningen command: lein run
The command will generate the following output on your terminal or console depending on your environment.
Compiling 1 source files to /Users/niko/hellojava/target/classes beginning of a journey
Whoo-hoo! The journey has begun! But, wait, what happened just there?
A bit of magic was involved. The leiningen run command will make Leiningen execute a compiled Java class main method. The class to be executed was de ined in the project’s metadata, and as you remember, that would be Hello.
Before executing the Java compiled class there is a need to… compile it. By default, Leiningen does compilation before performing the run command, and so this is where the “Compiling … ” message came out from.
Along the way, you may have noticed that a target folder was created inside your project folder, with a classes folder, and a Hello.class ile inside.
The target/classes folder is where the compiled Java bytecode goes by default, and that same target folder is then added to the Java execution runtime (classpath).
The execute phase triggered by “lein run ” follows, and the code block from the main method of the Hello class is executed; then the message prints out.
beginning of a journey.
You may ask: “What if I have multiple Java iles, and want to run a different one than the main one?”
This is a very valid question, as you will be probably doing that a few times in this irst chapter to write and run the different code samples.
Say you write a second Java class in a ile named Hello2.java in the same Java folder, along with some updated journey content.
import static java.lang.System.out; public class Hello2 { public static void main(String[] args) { String[] text = new String[]{ "Sometimes it's the journey that " , "teaches you a lot about your destination.", " -" , " - Drake"}; for(String t : text) out.println(t); } }
To run that exact main method from the Hello2.java ile , you would call lein run with the optional –m option, where m stands for main, and then the name of the main Java class to use.
lein run –m Hello2
This gives you the following output:
Compiling 1 source files to /Users/niko/hellojava/target/classes Sometimes it's the journey that
teaches you a lot about your destination.
--
- Drake
Great. With those instructions, you now know enough to go ahead and run your irst OpenCV Java program.
1.2
Writing Your First OpenCV Java Program
PROBLEM
You would like to use Leiningen to have a Java project setup where you can use OpenCV libraries directly. You would like to run Java code making use of OpenCV, but you got headaches already (while compiling the opencv wrapper yourself), so you would like to make this step as simple as possible.
SOLUTION
Recipe 1-1 presented Leiningen to help you with all the basic required setup. From there, you can add a dependency on the OpenCV C++ library and its Java wrapper.
HOW IT WORKS
For this irst OpenCV example, we will get set up with a Leiningen project template , where the project.clj ile and the project folders are already de ined for you. Leiningen project templates do not have to be downloaded separately and can be called upon to create new projects using Leiningen’s integrated new command. To create this project on your local machine, on the command line , let’s call the command of lein. Whether on Windows or Mac, the command gives
lein new jvm-opencv hellocv
What the preceding command basically does is
1 . create a new project folder named hellocv
2 . create directories and iles with the content of the folder based on a template named jvm-opencv
After running the command, the rather simple following project iles are created: . ├ java │ └ HelloCv.java └ project.clj
That does not seem too impressive, but actually those are almost the same as the two iles from the previous recipe: a project descriptor and a Java ile.
The project.clj content is a slightly modi ied version from before:
You probably have noticed straightaway three new lines you have not seen before.
First of all is the repositories section, which indicates a new repository location to ind dependencies. The one provided
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