Display any image.
The source code was extracted from the book
"Learning OpenCV 3 - Computer vision in C++ with the opencv library"
by Adrian Kaehler & Gary Bradski
g++ -o viewer main.cpp `pkg-config --cflags --libs opencv`./viewer greyhound.jpgIf your distribution doesn't offer OpenCV, you will have to build it from sources. You can start at
https://opencv.org/releases, where you can select the files for the current OpenCV source code bundle.
To build the libraries and demos, you'll need GTK+ 2.x or higher, including headers.
You'll also need gcc and the essential development packages, cmake and libtbb (Intel thread building blocks), and
optionally zlib, libpng, libjpeg, libtiff, and libjasper with development files (i.e., the versions with -dev at the
end of their package names).
You'll need Python 2.6 or later with headers installed (developer package), as well as NumPy in order to make Python
bindings work. You will also need libavcodec and the other libav* libraries (including headers) from ffmpeg.
For the latter, install libav/ffmpeg packages supplied with your distribution or download ffmpeg from http://www.ffmpeg.org.
To actually build the library, you will need to unpack the ZIP file and go into the created source directory, and do
the following:
mkdir realese && cd release
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local ..
make
sudo make install # optionalThe first command create a new subdirectory and move you into it. The second command tells CMake how to configure
your build. The example options we give are probably the right ones to get you started.