Using OpenCV ¶

OpenCV (Open Computer Vision) is a C++ library containing various state-of-the-art vision algorithms, from object recognition to video analysis, image processing etc.

OpenCV 2.3.1 ¶

Since version 1.14, NAOqi SDK supports OpenCV 2.3.1 for both compilation and cross-compilation. This latest version contains various fixes and optimizations compared to the previously supported 2.1 versions, also with an important restructuring of the library’s architecture.

OpenCV 2.3 is practically entirely backward compatible with OpenCV 2.1. So everything working on 2.1 should work on 2.3.

However, there has been a complete refactoring of the structure:

• separating the C API from the C++ one
• separating the distribution into logical modules

Modules ¶

The main modules are

• core : it contains the basic structures and functionalities
• highgui : anything to do with display, opening or saving images
• imgproc : color conversion, filters...
• video : optical flow, background substraction...
• calib3d : homography, fundamental matrices... anything to do with camera calibration and stereovision
• features2d : feature detection, descriptors (FAST, SURF), matching
• ml : machine learning (neural networks, SVM, boosting, KNN etc)
• flann : efficient clustering and search in databases
• objectdetection : object detection with Cascade or Haar classifiers

Each module has its associated include file(s). For example



#include <opencv2/core/core.hpp>



API ¶

The API has been cleaned: C and C++ API are now clearly distinguished. For example CvMat is C API, and has its equivalent in C++ cv::Mat . Unless you are doing C, use C++ API! No need to mix both. If you really need to use the C API, use the right include



#include <opencv2/core/core_c.h>



but again, do not mix the includes.

IplImage and cv::Mat

IplImage* has been replaced by cv::Mat. This is basically the same structure, but more generic. So all methods that had IplImage* arguments now use cv::Mat.

cv::Mat is a smart pointer, which means that you do not have to release it by hand (though there is a release method). It behaves like a pointer, which means that if you do the following code:



cv::Mat oldMat;
// Do some processing.
cv::Mat newMat = oldMat;



no data will be copied . Which means that if oldMat is released, then newMat is emptied. If you want to copy some data, use the copyTo or clone methods.

ROI are handled that way: you create a new matrix pointing to the desired area, without any data copy, and then copy what you want to that new matrix.

Here is a non-exhaustive list of some interesting fields of IplImage, and what they have become in cv::Mat.

OpenCV 2.1 OpenCV 2.3
width cols
height rows
imageData data
nChannels channels()

CvSeq* and std::vector

You might have dabbled a bit with the storage structures of OpenCV, CvSeq and CvMemStorage. If you did, you might have noticed that they are rather counter-intuitive and nearly impossible to create yourself. Fortunately, if you use the C++ API, all CvSeq have disappeared and have been replaced by std::vector, that is infinitely easier to handle!

From C to C++

Even if you code in C++, you might be used to the C API, which has this typical format: cvSomeOpenCVMethod(...). To use the C++ equivalent try replacing CvSeq by std::vector and IplImage by cv::Mat.

CMake dependencies ¶

OpenCV 2.3 is now packaged according to the modules. So when you want to use OpenCV, instead of using



qi_use_lib(mylib OPENCV)



specify the modules that you want to use. For example, if you are using core and highgui



qi_use_lib(mylib OPENCV2_CORE OPENCV2_HIGHGUI)



All modules use the following format: OPENCV2_MODULENAME.

What’s new in OpenCV 2.3 ¶

OpenCV 2.3 is not only a code clean-up and refactoring. It also offers a lot of new wrapper classes which make life much easier, especially in terms of keypoint extraction and so on.

There are new implementations of various keypoints / descriptors: Star (also called Censure), MSER, Upgraded SURF, BRIEF, Ferns...

Toolchain OpenCV versus system OpenCV ¶

C++ NAOqi SDK provides some OpenCV libraries.

However, on Ubuntu, these libraries have been built without GTK support for portability reasons (GTK has a lot of dependencies, and will be useless on the robot since it has no display). This means that you will not be able to use any of the graphical interface methods of OpenCV (such as cv::imshow). This seems natural if you are working on the robot, but you will probably want to have some visual debug. You will also have the same problem if you try to execute this example: Getting an image .

You might also want to work with your specific OpenCV (for example, using special compilation flags or optimization libraries).

The solution is to replace SoftBank Robotics ‘ version of OpenCV by your system one. To do so, follow these steps:

Cleaning old versions

If you do not have any previous OpenCV installation on your machine, you may skip this section and go directly to Installing the latest version .

If you installed your version from the sources

• go to the build folder where you built the sources.

• execute the following command (possibly with sudo on Ubuntu):



make uninstall


• If you installed it from the sources but cannot find the build directory, you can either remove OpenCV libraries by hand or:

• build the sources (as in Installing the latest version but with an older version)

• execute the following (possibly with sudo on Ubuntu):



make
make install
make uninstall



If you used an installer or a package

Uninstall it using the provided uninstaller (from Synaptic Package Manager for Ubuntu, for example).

The best solution is to build OpenCV from the sources and install it.

• Get the latest OpenCV version from http://sourceforge.net/projects/opencvlibrary/ .

• Uncompress it somewhere on your machine (it is better to keep it afterwards)

• Inside the extracted folder, create a build directory and open it



mkdir build
cd build


• Configure your project using CMake



cmake ..



This command will output a large log which will show what prerequisites have been found. Some are optional, some are more important. For example, you have to check that GTK support is enabled, but you do not need IPP support or CUDA.

To have an idea of the prerequisites, refer to: http://opencv.willowgarage.com/wiki/InstallGuide .

Note

On Ubuntu, you might need amongst other the package libgstreamermm-0.10-dev for gstreamer missing libraries.

Warning

If you are using Ubuntu 11.10, you will probably get some issues with ffmpgeg/avcodec.h. If you don’t need ffmpeg (which you probably don’t, or else you would know it), then remove ffmpeg support. Do do so, uncheck WITH_FFMPEG key in CMake GUI, configure and generate, then proceed as usual. If you are convinced that you need ffmpeg, you might want to follow the instructions from this link .

• Build the distribution



make


• Install it



make install



You now have OpenCV installed on your machine!

Removing OpenCV from the NAOqi SDK ¶

Once you have OpenCV installed for your system, you have to remove it from the SDK. Do not remove the CMake configuration files.

• Remove all OpenCV libraries from the lib/ directory of the SDK. They will have the following format: libopencv_modulename.so, libcv.so, libhighui.so and libml.so
• Remove the opencv folder from the include folder

Now clean your project, then run again



qibuild configure [-c mytoolchain]
qibuild make [-c mytoolchain]



Cross compilation of OpenCV code ¶

The cross toolchain contains OpenCV libraries. To ensure that your code will run on NAO, simply make sure that you are not using any graphical interface methods (such as windows, trackbars etc).

Troubleshooting ¶

CMake configuration ¶

If you get some issues while configuring the project saying that some OpenCV packages are not found, there might be several explanations:

• you have removed opencv from the toolchain, but do not have it installed on your system
• you used a wrong name in your CMakeLists.txt: check that the format is OPENCV2_MODULENAME (ex: OPENCV2_CORE).