Computer vision, C++ OR Java

Question

I'm a complete newbie in the computer vision world and recently I implemented some examples using OpenCV with Java. I'm impressed with the potential this area has and wish to continue learning more.

I learned that OpenCV is written in C++ and while Java has a wrapper (JavaCV) I understood that the applications in Java are slower than in C++ and most enterprise application are written in C++.

My question is this: I have few years of experience in Java and I feel very comfortable to write any application with it; would it be smart to move to C++ to learn CV or should I stick with Java and use its wrapper.

Answer 1

Computer vision is a demanding area - and while it is true that you'd best stay with what you know, and move to opencv only if performance is needed, another truth is that you'll need to go deep into mathematics, pointers and algorithms to learn and build a good computer vision app. And to do that in Java can be more cumbersome than learning c++.

So, if all you want to do is to apply a filter over an image for some school project - go for Java. But if you want to stay more with OpenCV, to learn vision algorithms or to write your own, my strong suggestion is to learn C++ - isn't that scary!

A reason to write native code is flexibility - you'll want to do all kind of tricks that are difficult or performance-killers in Java.

Shortly speaking, learning C++ is much simpler than computer vision. And OpenCV is not just a library you want to call to do some processing out there. It's bleeding edge technology - you'll want to understand it, to hack into it, to build over it, to go through the code, much more than call someJNIfunc();

And if you do so, please be aware that OpenCV offers two interfaces - one for C and one for C++. And while they offer the same functionality, the C++ one is much like Java - with automatic memory management and more sweeties. You can refer to this post to see the differences

Answer 2

I suggest sticking with what you're comfortable with for now. Only switch to C++ when you find that it doesn't expose certain APIs you want or performance actually becomes a problem. Right now, you're in the learning phase.

Answer 3

JavaCV uses a wrapper called JavaCPP to call OpenCV from Java programs. JavaCPP automatically generates temporary native libraries that form a bridge used by JNI to let Java programs call the OpenCV native libraries.

The solution is elegant and it works well, but is quite finicky about installing just the right versions and having classpaths set correctly. You can get a glimpse of the difficulties people face at the JavaCV discussion forum, and at http://code.google.com/p/javacv/wiki/Windows7AndOpenCV .

I got this working with OpenCV-2.3.1 on XP, Windows 7, and Ubuntu 10.11, and still it took me several days to get it all updated to OpenCV-2.4.2. ffmpeg is especially tricky to get right across all platforms.

There is little or no speed overhead if you are using Java for high level program control because image objects and list-based data structures are maintained on the native side through pointers. One pitfall is knowing who is responsible for releasing allocated memory, so be prepared for VM crashes with complicated programs.

There is a bit overhead in transferring data objects to the Java side. I find that it takes about 1 microsecond to copy a keypoint location into a Java-side Point object. This doesn't sound like much but in a real-time application with thousands of keypoints it can make a difference. We also copy JavaCV IplImage objects to Java through ByteBuffers. This takes a millisecond or less so is quite feasible for real-time use.

In our case, we have a substantial body of Java code to leverage against OpenCV. And Java's garbage collection makes many things much much easier. I are satisfied that the overhead of learning JavaCV has been well worth it.

I found it necessary to build the project in Eclipse and compile JavaCV from source instead of using javacv.jar. (You'll need the other .jar files though.) This lets you examine exceptions to track down library version and classpath errors. And the JavaCV source is needed to understand how JavaCV exposes the OpenCV API.

Answer 4

How much time is spent in the OpenCV library and how much time is spend in your program? If your program entirely in C++ it cannot reduce the time spent in your program (outside the library) to less than nothing. eg if you spend 99% of your time in the library, using C++ cannot make it more than 1% faster.

Answer 5

For simple programs, Java and C++ doesn't make any significant difference in speed. But for a large code with lot of computational complexity, C++ turns out to be faster. Wrappers do have a problem of overhead. But this will be negligible for a small program. If you write a complex code in Java, it wont be easy to rewrite it into C++. This is because of the large no of functions available in Java which will be so much different from C++.

Whether you should use Java or C++ for OpenCV depends on your motive. If you seriously want to lean OpenCV and work on some big projects , I suggest you to move on to C++. But if you are looking for having just some fun with OpenCV, it will be better to stick to what you know.

Answer 6

Among C++ or Java, better use C++. I have almost no experience in Java, but the reason I would recommend C++ is its common usage among ML&CV libraries.

One of the best solution of powerful and flexible computer vision application may be next sequence:

1. training a model using flexible Python and popular machine learning libraries;
2. storing pre-trained weights;
3. rewriting the best model architechture to C++ using OpenCV library with useful, but not extensive Mat class or compiling to C++ ML model;
4. compiling with definite specification of your device processor.

Advances of this solution are application work speed, code safety, development speed and compatibility with many devices. Moreover, Python Tensorflow and other models could be loaded to C++, eg PyTorch . Besides, it is much more easier to get help from CV community with the C++ OpenCV code.

Disadvantages are tons of development problems and development speed (which may not be omitted with Java), sometimes strictful flexibility limits of OpenCV lib, and many others you may not think of at the beginning.