Scala, Eclipse and Maven integration tutorial

I have evaluated Scala as a language for cloud computing and Hadoop. One requirement was a robust development environment, with a real build system, a good IDE with code completion and debugging.

The combination of Scala, Eclipse and Maven seemed like a fit for this requirement, but my initial experience was mixed.

Problems with Scala, Eclipse and Maven integration

It was easy to install Scala, Eclipse and Maven, but when I set up a project it had a persistent error in Eclipse:

object Predef does not have a member AnyRef

Other problems:

• There were problems running the unit test.
• I had to restart Eclipse a lot.
• Eclipse had Scala set to version 2.9.0.1 while Maven had 2.8.0. When I tried to change Maven to use 2.9.0.1 the pom.xml file would be marked as having an error.

I searched internet for help but could not find it. After a good deal of experimenting I sorted out the problems and found a good solution.

Software versions

My setup is:

• Scala 2.9.0.1.
• Eclipse 3.7 Indigo
• Scala-ide Eclipse plugin: scala nightly 29 - http://download.scala-ide.org/nightly-update-wip-experiment-2.9.0-1

Scala, Eclipse Maven project setup tutorial

Here are that steps that I took to set up at new Scala, Eclipse and Maven project so it works with unit testing.

Press menu item: File - New - Other...

Select Maven Project

Select the org.scala-tools.archetypes scala-archetype-simple

Add group id and artifact id to project. Click Finish

This will create the project with example program and unit tests, but it will leave Eclipse in an unstable state

In the project's pom.xml file make the changes that I have marked in red:

<properties>
 <maven.compiler.source>1.5</maven.compiler.source>
 <maven.compiler.target>1.5</maven.compiler.target>
 <encoding>UTF-8</encoding>
 <scala.version>2.9.0-1</scala.version>
</properties>


<dependency>
 <groupId>org.scala-tools.testing</groupId>
 <artifactId>specs_${scala.version}</artifactId>
 <version>1.6.8</version>
 <scope>test</scope>
</dependency>

Now both Scala IDE and Maven are both using the same version of Scala. Scala 2.9.0.1


Right click the whole project and select: Configure - Add Scala Nature

Now use the Maven build system to clean, build and run unit tests. Run from either Eclipse or command line.

From Eclipse, right click the whole project and selecting:

Maven clean

Maven install

From command line:

C:\prog\apache-maven-2.2.1\bin\mvn clean

C:\prog\apache-maven-2.2.1\bin\mvn install

Note that you have to use Maven 2.2 and not Maven 3.

Now there should be no more errors.
The unit test: "scalatest.scala" has some problems, delete it.

Run all unit tests from Eclipse. By right clicking the whole project and select Run As JUnit Test

Now you can see the result in the JUnit runner.

Final impression of Scala, Eclipse and Maven integration

Once I had resolved the problems the Scala, Eclipse and Maven combination was a great development environment meeting my requirements.

One thing that is currently missing from the Scala Eclipse plugin is code refactoring. Refactoring works very well in both Eclipse for Java and Visual Studio for C#.

Computer vision C++ libraries review

I am trying to create an easy to use, minimalistic C++ cross-platform computer vision system, with a non-restrictive license. My biggest challenge was to chose the best libraries and to get them to work together; this took some investigation and experimenting. This posting is a brief description of my findings.

This is what ShapeLogic C++ currently looks like:


Windows


Linux

In order to construct ShapeLogic C++, I had to make choices within the following categories:

• Computer vision and image processing libraries
• GUI libraries
  
• Unit test systems
• Build systems
• Compilers under Windows
  
• C++ IDEs under UNIX
  

ImageJ, the Java open source image processing tool, is the inspiration for the first part of my work: it is very simple to learn, use and program in. This is a follow up to my last posting: Computer Vision C++ vs Java. The result of my work is released as an open source project ShapeLogic C++, under the MIT license.

Computer vision and image processing libraries

The candidates I considered were:

• GIL, Generic Image Library
  
• OpenCV
• VXL

GIL, Generic Image Library

GIL, Generic Image Library by Adobe.

Pros

• Very non intrusive, only based on header files
  
• Puts a wrapper around most image format
• You can write a algorithm once and it will work for most image types
• Part of Boost since 1.35
  

Cons

• Does not come with a lot of image processing algorithms
  

OpenCV

OpenCV, Open Computer Vision by Intel.

Pros

• Very simple
• Works with both C and C++
• Very broad range of algorithms
• Complex algorithms: face detection, convexity defects
• Very popular
  

Cons

• You have to use OpenCV's IplImage
• IplImage byte order is BGR instead of the normal RGB
  

VXL, Vision X Library

VXL a combination of 2 big older vision libraries TargetJR and IUE

Pros

• Well tested technology
  
• Simpler build process using cmake
  
• Uses modern programming techniques: classes, template and STL
  
• It has a lot of functionality
  
• Simple to get started with

Cons

• It is not using normal STL, but in order to work on different compiler it had to make its own version with different names.
• Class structure is somewhat complex.
  

Choice computer vision library for ShapeLogic C++
OpenCV for existing image processing and vision algorithms. GIL for writing new algorithms.

Cross platform GUI

The candidates I considered were:

• GIMP plugin
• GTK+, GIMP toolkit
• FLTK
• HighGui from OpenCV
• PhotoShop plugin
• wxWidget

Run ShapeLogic as a GIMP plugin

Pros

• GIMP is the main cross platform OSS image editing programs.
  
• It is in wide use.
  
• Has a lot of powerful features including scripting functionality in Scheme and Python.
  
• From a user perspective this would be an excellent choice.

Cons

• GIMP is GPL, but you could have a wrapper around plugins in order to access them as GIMP plugins.
• The plugin works with tiles, which gives good performance, but does not fit well with either the way OpenCV or GIL are processing images.

GTK+, GIMP Toolkit

Pros

• GTK+ is a great looking and very powerful framework that works on: Windows, Linux, Mac, a.o.

Cons

• It is written in C and has a homegrown object system, which is not type safe.

GTKMM C++ wrapper around GTK+

Pros

• CTKMM is a great looking and very powerful framework, that works on: Windows, Linux, Mac, a.o.
  
• It feels natural to program in for a C++ programmer.

Cons

• The class hierarchy is somewhat deep since it is built on top of GTK.

FLTK, Fast light toolkit

Pros

• FLTK is very lightweight.
  
• Very clean C++, you actually have a main().
  
• Native C++ build on top of X11 or Windows.
• Fluid, a simple GUI builder
  

Cons

• Not as many widgets.
  
• Dated look.

HighGui from OpenCV

Pros

• Very lightweight.
  
• There is some functionality for displaying images, video and an event handler for mouse events.

Cons

• Does not come with a menu system.

Run ShapeLogic as a PhotoShop plugin

Pros

• PhotoShop is the main image editing programs.
  
• It is in wide use, has a lot of powerful features including macros.
  
• From a user perspective this would be an excellent choice.

Cons

• The PhotoShop SDK is not freely available, you have to apply to get it.
• The plugin does not fit well with either the way OpenCV or GIL are processing images.

wxWidgets

Pros

• wxWidgets is a full featured GUI toolkit, built on top of native toolkits: Win32, Mac OS X, GTK+, X11, Motif, WinCE and more.
• Looks good and modern.
  
• Big community.
• Several GUI builders.
  

Cons

• The programming style is close to Windows MFC programming.
  
• There are many layers.

Choice
This was a hard choice and I went back and forth between FLTK and wxWidgets, but went with FLTK. All the GUI code is separate from the image processing code, so if I wanted to change from FLTK to another toolkit later it should not be too dramatic.

C++ unit test frameworks

There are a lot of different choices and no clear leader. Some of the candidates were:

• Boost.test
• CppUnit
  
• Google C++ Testing Framework
  

Boost.test

Pros

• Boost.test is part of the Boost library.
  
• Powerful with a lot of options.
  

Cons

• You have to manually set up test suites.
  
• It is somewhat heavy.
  
• The documentation is extensive but not easy to read.
  

CppUnit

Pros

• CppUnit is following a standard unit testing convention XUnit.
• Integration with Eclipse CDT.
  

Cons

• You have to manually set up test suites.
  
• It is an extra library to install.

Google C++ Testing Frameworks

Pros

• Google test is following a standard unit testing convention XUnit.
  
• Strong focus on simplicity.
• Documentation is short and easy to read.
  

Cons

• It is an extra library to install.

Choice of C++ unit test framework for ShapeLogic C++

I spent quite a bit of time reading the Boost Test documentation, finally I tried Google C++ Testing Framework and got it working very fast.

Build system

The candidates I considered were:

• Boost build
  
• Make

Boost build

Pros

• Boost build is part of Boost.
  
• Clean design, made as a Make replacement.
• Works on most platforms and with most compilers.
• The scripts are pretty short.
  

Cons

• There is a learning curve.
  

Make

Pros

• Make is the standard for build on C++.
• Widely used.
• Works with Eclipse, MSVC, NetBeans.
• Short scripts.
  

Cons

• It has gotten messy over time.
  
• Shell script dependency.
  
• There is too much magic for my taste.
  

Choice of build system for ShapeLogic C++

I chose to go with Boost Build because it has a cleaner design, but Make looks very competitive when looking over the pros and cons.

Compilers under Windows

In order to compile Boost you need a pretty modern and standard compliant compiler. The candidates that I looked at are:

• Cygwin GCC
  
• MinGW GCC
• MSVC Microsoft Visual C++
  

Cygwin GCC

Pros

• Cygwin GCC is close to GCC under UNIX
  

Cons

• Uses emulation of UNIX system call.
  
• You can only use it to build GPL compatible application.
  

MinGW GCC

Pros

• MingGW integrates well with Eclipse CDT.
• Works more natively with Windows.
• Most libraries build fine with MinGW.
  

Cons

• It was supposed to be able to build FLTK, but I tried a few times and could not get it to work.
• In order to run Make files you also have to install MSYS, which is a minimal shell.
  

MSVC, Microsoft Visual C++

Pros

• MSVC is a high quality compiler.
  
• Most used compiler under Windows.
  
• There is a free Express version.
  

Cons

• There seems to be some restrictions of the Express version that I did not quite understand.
  

Choice of compiler under Windows for ShapeLogic C++

MSVC.

C++ IDEs under UNIX

The candidates I considered were:

• Eclipse 3.4
  
• Emacs / Xemacs
• NetBeans 6.1
  

Eclipse 3.4

Pros

• Eclipse 3.4 CDT has a good debugger.
• Easy to jump from classes to files defining the classes.
  

Cons

• Not nearly as good as Eclipse for Java.
• Unstable under Linux AMD64.

Emacs

Pros

• Emacs is powerful tools that runs in a terminal.
• Takes up less resources.
• Not dependent on Java.
  

Cons

• The Java bases IDE have more features.
• Demands more knowledge to use.
  

NetBeans 6.1

Pros

• NetBeans 6.1 seem a little lighter than Eclipse.

Cons

• It is made to work with Make files, and ShapeLogic C++ is using Boost Build / Bjam.
  

Choice of IDE under UNIX for ShapeLogic C++

Eclipse.

Summary of libraries and tools used

• Boost the C++ library
• Generic Image Library for writing new image processing code
• OpenCV for existing computer vision algorithms
• FLTK, Fast Light Toolkit lightweight cross platform GUI
• Google C++ Testing Framework
• Boost.build v2 for command line based build system

Status of ShapeLogic C++

ShapeLogic C++ 0.4 is the first alpha release. It can do some useful work, but it still mainly an example application.

Currently has

• Comes with some image processing operation
• Comes with 3 brushes
• It is pretty simple to program an image processing algorithm
  

Missing

• Drawing is currently slow and there is only one pen size
• None of the ShapeLogic Java algorithms have been ported yet
• Documentation is poor

Hardest problems

• Learning how FLTK works
• Building a cross platform C++ build script covering several libraries

None of these problems will effect ShapeLogic users.

Porting computer vision code from Java to C++

Before I started porting ShapeLogic from Java, I thought that C++ was moving towards becoming a legacy language. What I have learned from this work is that C++ has advanced substantially since 2002, when I last used it professionally. C++ still seems competitive, at least in computer vision, and according to my old video game colleagues also in games, where I though that C# might have taken a lead by now. Both C++ and Java have substantial advantages.

C++

• OpenCV has a lot of vision algorithms, e.g. face recognition
• C++ is faster than Java
  
• Better for video processing
  
• Programs are shorter
• Generic programming working on primitive types
  
• You can make build script that build under both Windows and UNIX

Java / ImageJ

• ImageJ has more open source algorithms for medical image processing
  
• Better support for medical image files formats under ImageJ
• IDEs are better under Java
• Build process is simpler than C++
  
• Simpler language
• Better support for parallel processing
• A lot easier to dynamically load plugins
  

The next step is to port my framework for declarative programming -- it is based on lazy streams -- and port the Color Particle Analyzer. C++ / Boost have good support for functional programming techniques: Boost.Bind and Boost.Lambda, and the Phoenix library has just been accepted into Boost. When complete, I will do another posting about how it went.

-Sami Badawi
http://www.shapelogic.org

Computer Vision C++ vs Java review

In 2007 I created an open source computer vision project, ShapeLogic, built in Java to work with ImageJ. This setup has been very easy to work with and very productive. Bjarne Stroustrup the creator of C++ gave an interview about the new features in the C++0x standard and TR1. C++ now has a lot of innovating programming constructs e.g. template meta programming, lambda functions, concepts and traits. When I found out that "axiom" is going to be a keyword in C++ my inner mathematician demanded that I take a second look at C++ in connection with computer vision.

This post is a review of my personal past experience with computer vision in C++ and Java. I did my masters thesis in computer vision in the early 90ies, but I ended up working in other fields: video games, Internet and finance, which only left a little time to do vision in my free time. While both C++ and Java were good choices for professional vision programmers, several of the approaches I chose caused me to run out of steam. I also tried to do computer vision with functional, declarative and hybrid languages e.g. Oz, Scheme and Scala but will not cover that here.

Borland C++ early 90ies

C++ did not have STL or any other standard library so I used Borland's OWL library for images and for the application. I used C++ templates, classes with multiple inheritance, RTTI just to set up basic container functionality. There were a few books that has some free C or C++ source code for image processing and vision, but they did not spawn a user community. I did not really get to do anything interesting.

JAI, Java Advanced Imaging late 90ies

I was very excited when Java came around, this was the language to cure all programming ailments. Now they had added a library that could be used for vision and a lot of big companies were sponsoring JAI. It turned out to be a very complex framework with a deep class hierarchy, I spent a lot of time reading the manual trying to find out how to get access to image pixels. I gave up using it and the framework never gained much popularity.

VXL, C++, STL, Boost, Python, GCC, Linux around 2000

Open source software, OSS had started to become prominent. There were 2 OSS libraries:

• OpenCV (Open Computer Vision), wich was still in alpha.
• VXL (Vision X Library) wich was a merge of 2 big non OSS libs TargetJR and IUE.

VXL finally got into beta and I tried to combine it with Python for more high level processing.

Tools needed for build and GUI

• VXL does builds using CMake to create Make files
• Boost uses BJam to do builds
  
• Python bindings using Pyste from Boost
• VXL used FLTK and OpenGL as a GUI

Problems encountered

• It was hard to get the different build systems, CMake, Bjam and Make, to work together
  
• GCC 3.1 and 3.2 core dumped when compiling certain Boost classes
• Python bindings worked for simple C++ classes, but not for the nested template classes in VXL
  
• It was hard to debug the template programs
  
• Emacs was not really as easy to use as Visual Studio
  
• Bad drivers for OpenGL on Linux
  

I actually got some examples set up, but spent more time fighting with the tool stack than doing vision work.

ImageJ in Java around 2004

A colleague showed me a visualization tool he had worked on and said that he did it in around 1 month. I barely believed him, but tried the underlying framework, ImageJ. To my big surprise I was up and running and doing real work in a few hours. ImageJ just got things right. It was built using pure Java by one man, Wayne Rasband. It is very easy to work with and very modular, so a lot of people have made plugins and there is a vibrant development community. When I started working on ShapeLogic that was the best choice.

OpenCV, GIL Generic Image Library, Boost and Eclipse in C++ 2008

In the light of advance in the C++ language and tools, I have decided to try it again.
C++ image libraries choices

• OpenCV, Open Computer Vision
  
• Openframeworks built on top of OpenCV
  
• GIL Generic Image Library
• VXL

I chose to start with OpenCV made by Intel and GIL made by Adobe but a part of Boost since 1.35.

C++ IDE tried

• Eclipse 3.4
  
• NetBeans 6.1
  

Eclipse worked better for me, it has its own build system so you do not have to mess with Make files.

C++ cross platform GUIs

• FLTK Fast Light Toolkit
• wxWidgets
• HighGui from OpenCV

Not sure which one will be best for my purpose.

First attempt
I tried Boost, OpenCV and GIL and got them up and running under both Linux and Windows in a few hours. Eclipse CDT C++ IDE works great.

Porting ShapeLogic algorithms to C++ version

My plan is to port some algorithms from ShapeLogic from Java to C++. ShapeLogic is a toolkit for declarative programming, specialized for vision. In principle you should be able to make a list of rules for categorizing say the shape of a particle in a particle analyzer. You put them in a database or a flat file and the same rules should work for C++ and Java version of ShapeLogic. In practice this might not work out.

Advantages of C++ and Java

This is a loose first assessment.
Constructs used in ShapeLogic that are missing or less convenient in C++

• Uniform cross platform GUI
• Dynamic cross platform libraries
• HashTable
• Reflection
• Garbage collection
• Antlr for parsing logic language
  

Advantages of C++ over Java in vision

• Substantially higher speed
  
• Better handling of video
• Used more frequently for computer vision programming
  
• Good tracking and face recognition algorithms in OpenCV
  

For me, Java has been very good for doing medical image processing algorithms. I have heard conflicting evidence about whether it is feasible for doing computer vision on video using Java. Video handling in Java has been bad up to now, this is supposed to be fixed with the new JavaFX. Shadow Monsters is a computer vision based art piece taking video footage of silhouette of the viewer and adding monsters to them, I saw it on display at Museum of Modern Art. It was programmed using Processing, which is a Java based image processing tool for artists. I discussed the issue with a computer programmer / artist who said that he had tried to do a motion algorithm in Processing and had to port it to C++ based Openframeworks since Java was too slow. After being discouraged by my prior attempts to do vision in C++, I am very happy to see the dramatic developments in C++ and see if it is suitable for a simple port of ShapeLogic algorithms. The result of this C++ port will be covered in 2 postings:

• Computer vision C++ libraries review
• Declarative framework and Particle Analyzer Java to C++ port
  

-Sami Badawi
http://www.shapelogic.org