@note To use the OpenCV library you have two options: @ref tutorial_windows_install_prebuilt or

@ref tutorial_windows_install_build. While the first one is easier to complete, it only works if you are coding

technologies we integrate into our library. .. _Windows_Install_Prebuild:

Installation by Using the Pre-built Libraries {#tutorial_windows_install_prebuilt}

you have in your system's CPU.

- [Intel Integrated Performance Primitives (*IPP*)](http://software.intel.com/en-us/articles/intel-ipp/) may be used to improve the performance

of color conversion, Haar training and DFT functions of the OpenCV library. Watch out, since

- [Intel IPP Asynchronous C/C++](http://software.intel.com/en-us/intel-ipp-preview) is currently focused delivering Intel Graphics

support for advanced image processing and computer vision functions.

- OpenCV offers a somewhat fancier and more useful graphical user interface, than the default one

*OpenCV documentation*.

Now we will describe the steps to follow for a full build (using all the above frameworks, tools and

which you need only to unpack to get access to the console version of Git. Supposing that for

some of us it could be quite enough.

-# Install [TortoiseGit](http://code.google.com/p/tortoisegit/wiki/Download). Choose the 32 or 64 bit version according to the type of OS you work in.

wizard -- the default options are OK for the most part.

-# Choose a directory in your file system, where you will download the OpenCV libraries to. I

-# Clone the repository to the selected directory. After clicking *Clone* button, a window will

appear where you can select from what repository you want to download source files

(<https://github.com/opencv/opencv.git>) and to what directory (`D:/OpenCV`).

-# Push the OK button and be patient as the repository is quite a heavy download. It will take

some time depending on your Internet connection.

-# Download the [Python libraries](http://www.python.org/downloads/) and install it with the default options. You will need a

couple other python extensions. Luckily installing all these may be automated by a nice tool

called [Setuptools](http://pypi.python.org/pypi/setuptools#downloads). Download and install

it inside a directory on your system. For example let there be `D:/OpenCV/dep`. For installing

the [Intel Integrated Performance Primitives (*IPP*)](http://software.intel.com/en-us/articles/intel-ipp/)

the story is the same. For


Select all the packages you want to use and press again the *Configure* button. For an easier

overview of the build options make sure the *Grouped* option under the binary directory

selection is turned on. For some of the packages CMake may not find all of the required files or


Furthermore, you need to select what part of OpenCV you want to build.

- *BUILD_DOCS* -\> It creates two projects for building the documentation of OpenCV (there

built together with the solution. You need to make an explicit build project command on

these to do so.

- *BUILD_EXAMPLES* -\> OpenCV comes with many example applications from which you may learn

most of the libraries capabilities. This will also come handy to easily try out if OpenCV is

fully functional on your computer.

- *BUILD_PACKAGE* -\> Prior to version 2.3 with this you could build a project that will

systems. For the latest source files of OpenCV, it generates a new project that simply

creates a zip archive with OpenCV sources.

- *BUILD_SHARED_LIBS* -\> With this you can control to build DLL files (when turned on) or

test projects is also a good way to try out, that the modules work just as expected on your

system too.

- *BUILD_PERF_TESTS* -\> There are also performance tests for many OpenCV functions. If

- *BUILD_opencv_python* -\> Self-explanatory. Create the binaries to use OpenCV from the

Python language.

can tell CMake to create the project files by pushing the *Generate* button. Go to the build

directory and open the created **OpenCV** solution. Depending on just how much of the above

options you have selected the solution may contain quite a lot of projects so be tolerant on the



For the documentation, you need to explicitly issue the build commands on the *doxygen* project for

all the hard work. You can find the generated documentation inside the `build/doc/doxygen/html`.

To collect the header and the binary files, that you will use during your own projects, into a

the *Install* project.


To test your build just go into the `Build/bin/Debug` or `Build/bin/Release` directory and start

a couple of applications like the *contours.exe*. If they run, you are done. Otherwise,

something definitely went awfully wrong. In this case you should contact us at our [Q&A forum](http://answers.opencv.org/).

built with Qt support):


your GPU. Error messages containing invalid entries in (or cannot find) the nvcuda.dll are

caused mostly by old video card drivers. For testing the GPU (if built) run the

*performance_gpu.exe* sample application.

First we set an environment variable to make easier our work. This will hold the build directory of

our OpenCV library that we use in our projects. Start up a command window and enter:

setx -m OPENCV_DIR D:\OpenCV\Build\x86\vc11 (suggested for Visual Studio 2012 - 32 bit Windows)

setx -m OPENCV_DIR D:\OpenCV\Build\x64\vc11 (suggested for Visual Studio 2012 - 64 bit Windows)

Here the directory is where you have your OpenCV binaries (*extracted* or *built*). You can have

different platform (e.g. x64 instead of x86) or compiler type, so substitute appropriate value.

to make the settings computer wise, instead of user wise.

If you built static libraries then you are done. Otherwise, you need to add the *bin* folders path

a list of folders where DLLs can be found. Add the OpenCV library path to this and the OS will know

where to look if he ever needs the OpenCV binaries. Otherwise, you will need to copy the used DLLs

right beside the applications executable file (*exe*) for the OS to find it, which is highly

following new entry (right click in the application to bring up the menu):

%OPENCV_DIR%\bin

Save it to the registry and you are done. If you ever change the location of your build directories

OPENCV_DIR variable via the *setx* command inside a command window.

Now you can continue reading the tutorials with the @ref tutorial_windows_visual_studio_Opencv section.