OpenCV configuration options reference {#tutorial_config_reference}
======================================

@prev_tutorial{tutorial_general_install}
@next_tutorial{tutorial_env_reference}

@tableofcontents

# Introduction {#tutorial_config_reference_intro}

@note
We assume you have read @ref tutorial_general_install tutorial or have experience with CMake.

Configuration options can be set in several different ways:
* Command line: `cmake -Doption=value ...`
* Initial cache files: `cmake -C my_options.txt ...`
* Interactive via GUI

In this reference we will use regular command line.

Most of the options can be found in the root cmake script of OpenCV: `opencv/CMakeLists.txt`. Some options can be defined in specific modules.

It is possible to use CMake tool to print all available options:
```.sh
# initial configuration
cmake ../opencv

# print all options
cmake -L

# print all options with help message
cmake -LH

# print all options including advanced
cmake -LA
```

Most popular and useful are options starting with `WITH_`, `ENABLE_`, `BUILD_`, `OPENCV_`.

Default values vary depending on platform and other options values.


# General options {#tutorial_config_reference_general}

## Build with extra modules {#tutorial_config_reference_general_contrib}

`OPENCV_EXTRA_MODULES_PATH` option contains a semicolon-separated list of directories containing extra modules which will be added to the build. Module directory must have compatible layout and CMakeLists.txt, brief description can be found in the [Coding Style Guide](https://github.com/opencv/opencv/wiki/Coding_Style_Guide).

Examples:
```.sh
# build with all modules in opencv_contrib
cmake -DOPENCV_EXTRA_MODULES_PATH=../opencv_contrib/modules ../opencv

# build with one of opencv_contrib modules
cmake -DOPENCV_EXTRA_MODULES_PATH=../opencv_contrib/modules/bgsegm ../opencv

# build with two custom modules (semicolon must be escaped in bash)
cmake -DOPENCV_EXTRA_MODULES_PATH=../my_mod1\;../my_mod2 ../opencv
```

@note
Only 0- and 1-level deep module locations are supported, following command will raise an error:
```.sh
cmake -DOPENCV_EXTRA_MODULES_PATH=../opencv_contrib ../opencv
```

## Build with C++ Standard setting {#tutorial_config_reference_general_cxx_standard}

`CMAKE_CXX_STANDARD` option can be used to set C++ standard settings for OpenCV building.

```.sh
cmake -DCMAKE_CXX_STANDARD=17 ../opencv
cmake --build .
```

- C++11 is default/required/recommended for OpenCV 4.x. C++17 is default/required/recomended for OpenCV 5.x.
- If your compiler does not support required C++ Standard features, OpenCV configuration should be fail.
- If you set older C++ Standard than required, OpenCV configuration should be fail.
  For workaround, `OPENCV_SKIP_CMAKE_CXX_STANDARD` option can be used to skip `CMAKE_CXX_STANDARD` version check.
- If you set newer C++ Standard than recomended, numerous warnings may appear or OpenCV build may fail.


## Debug build {#tutorial_config_reference_general_debug}

`CMAKE_BUILD_TYPE` option can be used to enable debug build; resulting binaries will contain debug symbols and most of compiler optimizations will be turned off. To enable debug symbols in Release build turn the `BUILD_WITH_DEBUG_INFO` option on.

On some platforms (e.g. Linux) build type must be set at configuration stage:
```.sh
cmake -DCMAKE_BUILD_TYPE=Debug ../opencv
cmake --build .
```
On other platforms different types of build can be produced in the same build directory (e.g. Visual Studio, XCode):
```.sh
cmake <options> ../opencv
cmake --build . --config Debug
```

If you use GNU libstdc++ (default for GCC) you can turn on the `ENABLE_GNU_STL_DEBUG` option, then C++ library will be used in Debug mode, e.g. indexes will be bound-checked during vector element access.

Many kinds of optimizations can be disabled with `CV_DISABLE_OPTIMIZATION` option:
* Some third-party libraries (e.g. IPP, Lapack, Eigen)
* Explicit vectorized implementation (universal intrinsics, raw intrinsics, etc.)
* Dispatched optimizations
* Explicit loop unrolling

@see https://cmake.org/cmake/help/latest/variable/CMAKE_BUILD_TYPE.html
@see https://gcc.gnu.org/onlinedocs/libstdc++/manual/using_macros.html
@see https://github.com/opencv/opencv/wiki/CPU-optimizations-build-options


## Static build {#tutorial_config_reference_general_static}

`BUILD_SHARED_LIBS` option control whether to produce dynamic (.dll, .so, .dylib) or static (.a, .lib) libraries. Default value depends on target platform, in most cases it is `ON`.

Example:
```.sh
cmake -DBUILD_SHARED_LIBS=OFF ../opencv
```

@see https://en.wikipedia.org/wiki/Static_library

`ENABLE_PIC` sets the [CMAKE_POSITION_INDEPENDENT_CODE](https://cmake.org/cmake/help/latest/variable/CMAKE_POSITION_INDEPENDENT_CODE.html) option. It enables or disable generation of "position-independent code". This option must be enabled when building dynamic libraries or static libraries intended to be linked into dynamic libraries. Default value is `ON`.

@see https://en.wikipedia.org/wiki/Position-independent_code


## Generate pkg-config info

`OPENCV_GENERATE_PKGCONFIG` option enables `.pc` file generation along with standard CMake package. This file can be useful for projects which do not use CMake for build.

Example:
```.sh
cmake -DOPENCV_GENERATE_PKGCONFIG=ON ../opencv
```

@note
Due to complexity of configuration process resulting `.pc` file can contain incomplete list of third-party dependencies and may not work in some configurations, especially for static builds. This feature is not officially supported since 4.x version and is disabled by default.


## Build tests, samples and applications {#tutorial_config_reference_general_tests}

There are two kinds of tests: accuracy (`opencv_test_*`) and performance (`opencv_perf_*`). Tests and applications are enabled by default. Examples are not being built by default and should be enabled explicitly.

Corresponding _cmake_ options:
```.sh
cmake \
  -DBUILD_TESTS=ON \
  -DBUILD_PERF_TESTS=ON \
  -DBUILD_EXAMPLES=ON \
  -DBUILD_opencv_apps=ON \
  ../opencv
```


## Build limited set of modules {#tutorial_config_reference_general_modules}

Each module is a subdirectory of the `modules` directory. It is possible to disable one module:
```.sh
cmake -DBUILD_opencv_geometry=OFF ../opencv
```

The opposite option is to build only specified modules and all modules they depend on:
```.sh
cmake -DBUILD_LIST=geometry,videoio,ts ../opencv
```
In this example we requested 3 modules and configuration script has determined all dependencies automatically:
```
--   OpenCV modules:
--     To be built:                 core features flann geometry highgui imgcodecs imgproc ts videoio
```


## Downloaded dependencies {#tutorial_config_reference_general_download}

Configuration script can try to download additional libraries and files from the internet, if it fails to do it corresponding features will be turned off. In some cases configuration error can occur. By default all files are first downloaded to the `<source>/.cache` directory and then unpacked or copied to the build directory. It is possible to change download cache location by setting environment variable or configuration option:
```.sh
export OPENCV_DOWNLOAD_PATH=/tmp/opencv-cache
cmake ../opencv
# or
cmake -DOPENCV_DOWNLOAD_PATH=/tmp/opencv-cache ../opencv
```

In case of access via proxy, corresponding environment variables should be set before running cmake:
```.sh
export http_proxy=<proxy-host>:<port>
export https_proxy=<proxy-host>:<port>
```

Full log of download process can be found in build directory - `CMakeDownloadLog.txt`. In addition, for each failed download a command will be added to helper scripts in the build directory, e.g. `download_with_wget.sh`. Users can run these scripts as is or modify according to their needs.


## CPU optimization level {#tutorial_config_reference_general_cpu}

On x86_64 machines the library will be compiled for SSE3 instruction set level by default. This level can be changed by configuration option:
```.sh
cmake -DCPU_BASELINE=AVX2 ../opencv
```

@note
Other platforms have their own instruction set levels: `VFPV3` and `NEON` on ARM, `VSX` on PowerPC.

Some functions support dispatch mechanism allowing to compile them for several instruction sets and to choose one during runtime. List of enabled instruction sets can be changed during configuration:
```.sh
cmake -DCPU_DISPATCH=AVX,AVX2 ../opencv
```
To disable dispatch mechanism this option should be set to an empty value:
```.sh
cmake -DCPU_DISPATCH= ../opencv
```

It is possible to disable optimized parts of code for troubleshooting and debugging:
```.sh
# disable universal intrinsics
cmake -DCV_ENABLE_INTRINSICS=OFF ../opencv
# disable all possible built-in optimizations
cmake -DCV_DISABLE_OPTIMIZATION=ON ../opencv
```

@note
More details on CPU optimization options can be found in wiki: https://github.com/opencv/opencv/wiki/CPU-optimizations-build-options


## Profiling, coverage, sanitize, hardening, size optimization {#profiling_coverage_sanitize_hardening_size_optimization}

Following options can be used to produce special builds with instrumentation or improved security. All options are disabled by default.

| Option | Compiler | Description |
| -------| -------- | ----------- |
| `ENABLE_PROFILING` | GCC or Clang | Enable profiling compiler and linker options. |
| `ENABLE_COVERAGE` | GCC or Clang | Enable code coverage support. |
| `OPENCV_ENABLE_MEMORY_SANITIZER` | N/A | Enable several quirks in code to assist memory sanitizer. |
| `ENABLE_BUILD_HARDENING` | GCC, Clang, MSVC | Enable compiler options which reduce possibility of code exploitation.  |
| `ENABLE_LTO` | GCC, Clang, MSVC | Enable Link Time Optimization (LTO). |
| `ENABLE_THIN_LTO` | Clang | Enable thin LTO which incorporates intermediate bitcode to binaries allowing consumers optimize their applications later. |
| `OPENCV_ALGO_HINT_DEFAULT` | Any | Set default OpenCV implementation hint value: `ALGO_HINT_ACCURATE` or `ALGO_HINT_APPROX`. Dangerous! The option  changes behaviour globally and may affect accuracy of many algorithms. |

@see [GCC instrumentation](https://gcc.gnu.org/onlinedocs/gcc/Instrumentation-Options.html)
@see [Build hardening](https://en.wikipedia.org/wiki/Hardening_(computing))
@see [Interprocedural optimization](https://en.wikipedia.org/wiki/Interprocedural_optimization)
@see [Link time optimization](https://gcc.gnu.org/wiki/LinkTimeOptimization)
@see [ThinLTO](https://clang.llvm.org/docs/ThinLTO.html)

## Enable IPP optimization

Following options can be used to enables IPP optimizations for each functions but increases the size of the opencv library. All options are disabled by default.

| Option | Functions | + roughly size |
| -------| --------- | -------------- |
| `OPENCV_IPP_GAUSSIAN_BLUR` | GaussianBlur() | +8Mb |
| `OPENCV_IPP_MEAN` | mean() / meanStdDev() | +0.2Mb |
| `OPENCV_IPP_MINMAX` | minMaxLoc() / minMaxIdx() | +0.2Mb |
| `OPENCV_IPP_SUM` | sum() | +0.1Mb |

# Functional features and dependencies {#tutorial_config_reference_func}

There are many optional dependencies and features that can be turned on or off. _cmake_ has special option allowing to print all available configuration parameters:
```.sh
cmake -LH ../opencv
```


## Options naming conventions

There are three kinds of options used to control dependencies of the library, they have different prefixes:
- Options starting with `WITH_` enable or disable a dependency
- Options starting with `BUILD_` enable or disable building and using 3rdparty library bundled with OpenCV
- Options starting with `HAVE_` indicate that dependency have been enabled, can be used to manually enable a dependency if automatic detection can not be used.

When `WITH_` option is enabled:
- If `BUILD_` option is enabled, 3rdparty library will be built and enabled => `HAVE_` set to `ON`
- If `BUILD_` option is disabled, 3rdparty library will be detected and enabled if found => `HAVE_` set to `ON` if dependency is found


## Heterogeneous computation {#tutorial_config_reference_func_hetero}

### CUDA support

`WITH_CUDA` (default: _OFF_)

Many algorithms have been implemented using CUDA acceleration, these functions are located in separate modules. CUDA toolkit must be installed from the official NVIDIA site as a prerequisite. For cmake versions older than 3.9 OpenCV uses own `cmake/FindCUDA.cmake` script, for newer versions - the one packaged with CMake. Additional options can be used to control build process, e.g. `CUDA_GENERATION` or `CUDA_ARCH_BIN`. These parameters are not documented yet, please consult with the `cmake/OpenCVDetectCUDA.cmake` script for details.

@note Since OpenCV version 4.0 all CUDA-accelerated algorithm implementations have been moved to the _opencv_contrib_ repository. To build _opencv_ and _opencv_contrib_ together check @ref tutorial_config_reference_general_contrib.

@cond CUDA_MODULES
@note Some tutorials can be found in the corresponding section: @ref tutorial_table_of_content_gpu
@see @ref cuda
@endcond

@see https://en.wikipedia.org/wiki/CUDA

TODO: other options: `WITH_CUFFT`, `WITH_CUBLAS`, `WITH_NVCUVID`?

### OpenCL support

`WITH_OPENCL` (default: _ON_)

Multiple OpenCL-accelerated algorithms are available via so-called "Transparent API (T-API)". This integration uses same functions at the user level as regular CPU implementations. Switch to the OpenCL execution branch happens if input and output image arguments are passed as opaque cv::UMat objects. More information can be found in [the brief introduction](https://opencv.org/opencl/) and @ref core_opencl

At the build time this feature does not have any prerequisites. During runtime a working OpenCL runtime is required, to check it run `clinfo` and/or `opencv_version --opencl` command. Some parameters of OpenCL integration can be modified using environment variables, e.g. `OPENCV_OPENCL_DEVICE`. However there is no thorough documentation for this feature yet, so please check the source code in `modules/core/src/ocl.cpp` file for details.

@see https://en.wikipedia.org/wiki/OpenCL

TODO: other options: `WITH_OPENCL_SVM`, `WITH_OPENCLAMDFFT`, `WITH_OPENCLAMDBLAS`, `WITH_OPENCL_D3D11_NV`, `WITH_VA_INTEL`

## Image reading and writing (imgcodecs module)  {#tutorial_config_reference_func_imgcodecs}

### Built-in formats

Following formats can be read by OpenCV without help of any third-party library:

| Formats | Option | Default |
| --------| ------ | ------- |
| [BMP](https://en.wikipedia.org/wiki/BMP_file_format) | (Always) | _ON_ |
| [HDR](https://en.wikipedia.org/wiki/RGBE_image_format) | `WITH_IMGCODEC_HDR` | _ON_ |
| [Sun Raster](https://en.wikipedia.org/wiki/Sun_Raster) | `WITH_IMGCODEC_SUNRASTER` | _ON_ |
| [PPM, PGM, PBM, PAM](https://en.wikipedia.org/wiki/Netpbm#File_formats) | `WITH_IMGCODEC_PXM` | _ON_ |
| [PFM](https://en.wikipedia.org/wiki/Netpbm#File_formats) | `WITH_IMGCODEC_PFM` | _ON_ |
| [GIF](https://en.wikipedia.org/wiki/GIF) | `WITH_IMGCODEC_GIF` | _ON_ |

### PNG, JPEG, TIFF, WEBP, JPEG 2000, EXR, JPEG XL, AVIF support

| Formats | Library | Option | Default | Force build own |
| --------| ------- | ------ | ------- | --------------- |
| [PNG](https://en.wikipedia.org/wiki/Portable_Network_Graphics) | [libpng](https://en.wikipedia.org/wiki/Libpng)| `WITH_PNG` | _ON_ | `BUILD_PNG` |
|^| [libspng(simple png)](https://libspng.org/) | `WITH_SPNG` | _OFF_ | `BUILD_SPNG` |
| [JPEG](https://en.wikipedia.org/wiki/JPEG) | [libjpeg-turbo](https://en.wikipedia.org/wiki/Libjpeg) | `WITH_JPEG` | _ON_ | `BUILD_JPEG` |
|^| [libjpeg](https://en.wikipedia.org/wiki/Libjpeg) | `WITH_JPEG` | _OFF_ | Not supported. (see note) |
| [TIFF](https://en.wikipedia.org/wiki/TIFF) | [LibTIFF](https://en.wikipedia.org/wiki/LibTIFF) | `WITH_TIFF` | _ON_ | `BUILD_TIFF` |
| [WebP](https://en.wikipedia.org/wiki/WebP) || `WITH_WEBP` | _ON_ | `BUILD_WEBP` |
| [JPEG 2000](https://en.wikipedia.org/wiki/JPEG_2000) | [OpenJPEG](https://en.wikipedia.org/wiki/OpenJPEG) | `WITH_OPENJPEG` | _ON_ | `BUILD_OPENJPEG` |
|^| [JasPer](https://en.wikipedia.org/wiki/JasPer) | `WITH_JASPER` | _ON_ (see note) | `BUILD_JASPER` |
| [OpenEXR](https://en.wikipedia.org/wiki/OpenEXR) || `WITH_OPENEXR` | _ON_ | `BUILD_OPENEXR` |
| [JPEG XL](https://en.wikipedia.org/wiki/JPEG_XL) || `WITH_JPEGXL` | _ON_ | Not supported. (see note) |
| [AVIF](https://en.wikipedia.org/wiki/AVIF) || `WITH_AVIF` | _ON_ | Not supported. (see note) |

Most library source codes required to read/write images in these formats are bundled into OpenCV and will be built automatically if not found at the configuration stage
(except for some codecs that require external libraries, e.g. JPEG XL and AVIF).
Corresponding BUILD_* options will force building and using the bundled libraries; they are enabled by default on some platforms, e.g. Windows.

@note (All) Only one library for each image format can be enabled(e.g. In order to use JasPer for JPEG 2000 format, OpenJPEG must be disabled).
@note (JPEG 2000) OpenJPEG have higher priority than JasPer which is deprecated.
@note (JPEG) OpenCV 5 doesn't contain libjpeg source code, so `BUILD_JPEG_TURBO_DISABLE` is not supported. Users can use a system-wide installed libjpeg instead of libjpeg-turbo.
@note (EXR) OpenCV 5 doesn't contain OpenEXR source code, so `BUILD_OPENEXR` is not supported. Users must provide a system-wide installation of libopenexr.
@note (JPEG XL) OpenCV doesn't contain libjxl source code, so `BUILD_JPEGXL` is not supported. Users must provide a system-wide installation of libjxl.
@note (AVIF) OpenCV doesn't contain libavif source code, so `BUILD_AVIF` is not supported. Users must provide a system-wide installation of libavif.

@warning OpenEXR ver 2.2 or earlier cannot be used in combination with C++17 or later. In this case, updating OpenEXR ver 2.3.0 or later is required.

### GDAL integration

`WITH_GDAL` (default: _OFF_)

[GDAL](https://en.wikipedia.org/wiki/GDAL) is a higher level library which supports reading multiple file formats including PNG, JPEG and TIFF. It will have higher priority when opening files and can override other backends. This library will be searched using cmake package mechanism, make sure it is installed correctly or manually set `GDAL_DIR` environment or cmake variable.


### GDCM integration

`WITH_GDCM` (default: _OFF_)

Enables [DICOM](https://en.wikipedia.org/wiki/DICOM) medical image format support through [GDCM  library](https://en.wikipedia.org/wiki/GDCM). This library will be searched using cmake package mechanism, make sure it is installed correctly or manually set `GDCM_DIR` environment or cmake variable.


## Video reading and writing (videoio module) {#tutorial_config_reference_func_videoio}

TODO: how videoio works, registry, priorities

### Video4Linux

`WITH_V4L` (Linux; default: _ON_ )

Capture images from camera using [Video4Linux](https://en.wikipedia.org/wiki/Video4Linux) API. Linux kernel headers must be installed.

### FFmpeg

`WITH_FFMPEG` (default: _ON_)

Integration with [FFmpeg](https://en.wikipedia.org/wiki/FFmpeg) library for decoding and encoding video files and network streams. This library can read and write many popular video formats. It consists of several components which must be installed as prerequisites for the build:
- _avcodec_
- _avformat_
- _avutil_
- _swscale_
- _avresample_ (optional)

Exception is Windows platform where a prebuilt [plugin library containing FFmpeg](https://github.com/opencv/opencv_3rdparty/tree/ffmpeg/5.x) will be downloaded during a configuration stage and copied to the `bin` folder with all produced libraries.

@note [Libav](https://en.wikipedia.org/wiki/Libav) library can be used instead of FFmpeg, but this combination is not actively supported.

### GStreamer

`WITH_GSTREAMER` (default: _ON_)

Enable integration with [GStreamer](https://en.wikipedia.org/wiki/GStreamer) library for decoding and encoding video files, capturing frames from cameras and network streams. Numerous plugins can be installed to extend supported formats list. OpenCV allows running arbitrary GStreamer pipelines passed as strings to @ref cv::VideoCapture and @ref cv::VideoWriter objects.

Various GStreamer plugins offer HW-accelerated video processing on different platforms.


### Microsoft Media Foundation

`WITH_MSMF` (Windows; default: _ON_)

Enables MSMF backend which uses Windows' built-in [Media Foundation framework](https://en.wikipedia.org/wiki/Media_Foundation). Can be used to capture frames from camera, decode and encode video files. This backend have HW-accelerated processing support (`WITH_MSMF_DXVA` option, default is _ON_).

@note Older versions of Windows (prior to 10) can have incompatible versions of Media Foundation and are known to have problems when used from OpenCV.


### DirectShow

`WITH_DSHOW` (Windows; default: _ON_)

This backend uses older [DirectShow](https://en.wikipedia.org/wiki/DirectShow) framework. It can be used only to capture frames from camera. It is now deprecated in favor of MSMF backend, although both can be enabled in the same build.


### AVFoundation

`WITH_AVFOUNDATION` (Apple; default: _ON_)

[AVFoundation](https://en.wikipedia.org/wiki/AVFoundation) framework is part of Apple platforms and can be used to capture frames from camera, encode and decode video files.


### Other backends

There are multiple less popular frameworks which can be used to read and write videos. Each requires corresponding library or SDK installed.

| Option | Default | Description |
| ------ | ------- | ----------- |
| `WITH_1394` | _OFF_ | [IIDC IEEE1394](https://en.wikipedia.org/wiki/IEEE_1394#IIDC) support using DC1394 library |
| `WITH_OPENNI` | _OFF_ | [OpenNI](https://en.wikipedia.org/wiki/OpenNI) can be used to capture data from depth-sensing cameras. Deprecated. |
| `WITH_OPENNI2` | _OFF_ | [OpenNI2](https://structure.io/openni) can be used to capture data from depth-sensing cameras. |
| `WITH_PVAPI` | _OFF_ | [PVAPI](https://www.alliedvision.com/en/support/software-downloads.html) is legacy SDK for Prosilica GigE cameras. Deprecated. |
| `WITH_ARAVIS` | _OFF_ | [Aravis](https://github.com/AravisProject/aravis) library is used for video acquisition using Genicam cameras. |
| `WITH_XIMEA` | _OFF_ | [XIMEA](https://www.ximea.com/) cameras support. |
| `WITH_XINE` | _OFF_ | [XINE](https://en.wikipedia.org/wiki/Xine) library support. |
| `WITH_LIBREALSENSE` | _OFF_ | [RealSense](https://en.wikipedia.org/wiki/Intel_RealSense) cameras support. |
| `WITH_MFX` | _OFF_ | [MediaSDK](http://mediasdk.intel.com/) library can be used for HW-accelerated decoding and encoding of raw video streams. |
| `WITH_GPHOTO2` | _OFF_ | [GPhoto](https://en.wikipedia.org/wiki/GPhoto) library can be used to capure frames from cameras. |
| `WITH_ANDROID_MEDIANDK` | _ON_ | [MediaNDK](https://developer.android.com/ndk/guides/stable_apis#libmediandk) library is available on Android since API level 21. |


### videoio plugins

Since version 4.1.0 some _videoio_ backends can be built as plugins thus breaking strict dependency on third-party libraries and making them optional at runtime. Following options can be used to control this mechanism:

| Option | Default | Description |
| --------| ------ | ------- |
| `VIDEOIO_ENABLE_PLUGINS` | _ON_ | Enable or disable plugins completely. |
| `VIDEOIO_PLUGIN_LIST` | _empty_ | Comma- or semicolon-separated list of backend names to be compiled as plugins. Supported names are _ffmpeg_, _gstreamer_, _msmf_, _mfx_ and _all_. |

Check @ref tutorial_general_install for standalone plugins build instructions.


## Parallel processing {#tutorial_config_reference_func_core}

Some of OpenCV algorithms can use multithreading to accelerate processing. OpenCV can be built with one of threading backends.

| Backend | Option | Default | Platform | Description |
|-------- | ------ | ------- | -------- | ----------- |
| pthreads | `WITH_PTHREADS_PF` | _ON_ | Unix-like | Default backend based on [pthreads](https://en.wikipedia.org/wiki/POSIX_Threads) library is available on Linux, Android and other Unix-like platforms. Thread pool is implemented in OpenCV and can be controlled with environment variables `OPENCV_THREAD_POOL_*`. Please check sources in _modules/core/src/parallel_impl.cpp_ file for details. |
| Concurrency | N/A | _ON_ | Windows | [Concurrency runtime](https://docs.microsoft.com/en-us/cpp/parallel/concrt/concurrency-runtime) is available on Windows and will be turned _ON_ on supported platforms unless other backend is enabled. |
| GCD | N/A | _ON_ | Apple | [Grand Central Dispatch](https://en.wikipedia.org/wiki/Grand_Central_Dispatch) is available on Apple platforms and will be turned _ON_ automatically unless other backend is enabled. Uses global system thread pool. |
| TBB | `WITH_TBB` | _OFF_ | Multiple | [Threading Building Blocks](https://en.wikipedia.org/wiki/Threading_Building_Blocks) is a cross-platform library for parallel programming. |
| OpenMP | `WITH_OPENMP` | _OFF_ | Multiple | [OpenMP](https://en.wikipedia.org/wiki/OpenMP) API relies on compiler support. |
| HPX | `WITH_HPX` | _OFF_ | Multiple | [High Performance ParallelX](https://en.wikipedia.org/wiki/HPX) is an experimental backend which is more suitable for multiprocessor environments. |

@note OpenCV can download and build TBB library from GitHub, this functionality can be enabled with the `BUILD_TBB` option.


### Threading plugins

Since version 4.5.2 OpenCV supports dynamically loaded threading backends. At this moment only separate compilation process is supported: first you have to build OpenCV with some _default_ parallel backend (e.g. pthreads), then build each plugin and copy resulting binaries to the _lib_ or _bin_ folder.

| Option | Default | Description |
| ------ | ------- | ----------- |
| PARALLEL_ENABLE_PLUGINS | ON | Enable plugin support, if this option is disabled OpenCV will not try to load anything |

Check @ref tutorial_general_install for standalone plugins build instructions.


## GUI backends (highgui module) {#tutorial_config_reference_highgui}

OpenCV relies on various GUI libraries for window drawing.

| Option | Default | Platform | Description |
| ------ | ------- | -------- | ----------- |
| `WITH_GTK` | _ON_ | Linux | [GTK](https://en.wikipedia.org/wiki/GTK) is a common toolkit in Linux and Unix-like OS-es. By default version 3 will be used if found, version 2 can be forced with the `WITH_GTK_2_X` option. |
| `WITH_WIN32UI` | _ON_ | Windows | [WinAPI](https://en.wikipedia.org/wiki/Windows_API) is a standard GUI API in Windows. |
| N/A | _ON_ | macOS | [Cocoa](https://en.wikipedia.org/wiki/Cocoa_(API)) is a framework used in macOS. |
| `WITH_QT` | _OFF_ | Cross-platform | [Qt](https://en.wikipedia.org/wiki/Qt_(software)) is a cross-platform GUI framework. |
| `WITH_FRAMEBUFFER` | _OFF_ | Linux | Experimental backend using [Linux framebuffer](https://en.wikipedia.org/wiki/Linux_framebuffer). Have limited functionality but does not require dependencies. |
| `WITH_FRAMEBUFFER_XVFB` | _OFF_ | Linux | Enables special output mode of the FRAMEBUFFER backend compatible with [xvfb](https://en.wikipedia.org/wiki/Xvfb) tool. Requires some X11 headers. |

@note OpenCV compiled with Qt support enables advanced _highgui_ interface, see @ref highgui_qt for details.


### OpenGL

`WITH_OPENGL` (default: _OFF_)

OpenGL integration can be used to draw HW-accelerated windows with following backends: GTK, WIN32 and Qt. And enables basic interoperability with OpenGL, see @ref core_opengl and @ref highgui_opengl for details.


### highgui plugins

Since OpenCV 4.5.3 GTK backend can be build as a dynamically loaded plugin. Following options can be used to control this mechanism:

| Option | Default | Description |
| --------| ------ | ------- |
| `HIGHGUI_ENABLE_PLUGINS` | _ON_ | Enable or disable plugins completely. |
| `HIGHGUI_PLUGIN_LIST` | _empty_ | Comma- or semicolon-separated list of backend names to be compiled as plugins. Supported names are _gtk_, _gtk2_, _gtk3_, and _all_. |

Check @ref tutorial_general_install for standalone plugins build instructions.


## Deep learning neural networks inference backends and options (dnn module) {#tutorial_config_reference_dnn}

OpenCV have own DNN inference module which have own build-in engine, but can also use other libraries for optimized processing. Multiple backends can be enabled in single build. Selection happens at runtime automatically or manually.

| Option | Default | Description |
| ------ | ------- | ----------- |
| `WITH_PROTOBUF` | _ON_ | Enables [protobuf](https://en.wikipedia.org/wiki/Protocol_Buffers) library search. OpenCV can either build own copy of the library or use external one. This dependency is required by the _dnn_ module, if it can't be found module will be disabled. |
| `BUILD_PROTOBUF` | _ON_ | Build own copy of _protobuf_. Must be disabled if you want to use external library. |
| `PROTOBUF_UPDATE_FILES` | _OFF_ | Re-generate all .proto files. _protoc_ compiler compatible with used version of _protobuf_ must be installed. |
| `OPENCV_DNN_OPENCL` | _ON_ | Enable built-in OpenCL inference backend. |
| `WITH_INF_ENGINE` | _OFF_ | **Deprecated since OpenVINO 2022.1** Enables [Intel Inference Engine (IE)](https://github.com/openvinotoolkit/openvino) backend. Allows to execute networks in IE format (.xml + .bin). Inference Engine must be installed either as part of [OpenVINO toolkit](https://en.wikipedia.org/wiki/OpenVINO), either as a standalone library built from sources. |
| `INF_ENGINE_RELEASE` | _2020040000_ | **Deprecated since OpenVINO 2022.1** Defines version of Inference Engine library which is tied to OpenVINO toolkit version. Must be a 10-digit string, e.g. _2020040000_ for OpenVINO 2020.4. |
| `WITH_NGRAPH` | _OFF_ | **Deprecated since OpenVINO 2022.1** Enables Intel NGraph library support. This library is part of Inference Engine backend which allows executing arbitrary networks read from files in multiple formats supported by OpenCV: ONNX, TensorFlow, PyTorch, etc.. NGraph library must be installed, it is included into Inference Engine. |
| `WITH_OPENVINO` | _OFF_ | Enable Intel OpenVINO Toolkit support. Should be used for OpenVINO>=2022.1 instead of `WITH_INF_ENGINE` and `WITH_NGRAPH`. |
| `WITH_ONNXRUNTIME` | _OFF_ | Enable Microsoft ONNX Runtime backend support for OpenCV DNN. |
| `DOWNLOAD_ONNXRUNTIME` | _OFF_ | Download official ONNX Runtime prebuilt binaries when enabled (or when ONNX Runtime is not available in system paths). |
| `DOWNLOAD_ONNXRUNTIME_GPU` | _OFF_ | Download GPU-enabled ONNX Runtime prebuilt binaries when available (Windows x64 and Linux x64 only). Requires `WITH_ONNXRUNTIME=ON`. |
| `ONNXRUNTIME_PREFER_STATIC` | _ON_ | Prefer static `libonnxruntime.a` when both static and shared ONNX Runtime libraries are available. |
| `ONNXRUNTIME_VERSION` | _1.25.1_ | ONNX Runtime version to download for prebuilt packages. |
| `OPENCV_DNN_CUDA` | _OFF_ | Enable CUDA backend. [CUDA](https://en.wikipedia.org/wiki/CUDA), CUBLAS and [CUDNN](https://developer.nvidia.com/cudnn) must be installed. |
| `WITH_VULKAN` | _OFF_ | Enable experimental [Vulkan](https://en.wikipedia.org/wiki/Vulkan_(API)) backend. Does not require additional dependencies, but can use external Vulkan headers (`VULKAN_INCLUDE_DIRS`). |


# Installation layout {#tutorial_config_reference_install}

## Installation root {#tutorial_config_reference_install_root}

To install produced binaries root location should be configured. Default value depends on distribution, in Ubuntu it is usually set to `/usr/local`. It can be changed during configuration:
```.sh
cmake -DCMAKE_INSTALL_PREFIX=/opt/opencv ../opencv
```
This path can be relative to current working directory, in the following example it will be set to `<absolute-path-to-build>/install`:
```.sh
cmake -DCMAKE_INSTALL_PREFIX=install ../opencv
```

After building the library, all files can be copied to the configured install location using the following command:
```.sh
cmake --build . --target install
```

To install binaries to the system location (e.g. `/usr/local`) as a regular user it is necessary to run the previous command with elevated privileges:
```.sh
sudo cmake --build . --target install
```

@note
On some platforms (Linux) it is possible to remove symbol information during install. Binaries will become 10-15% smaller but debugging will be limited:
```.sh
cmake --build . --target install/strip
```


## Components and locations {#tutorial_config_reference_install_comp}

Options cane be used to control whether or not a part of the library will be installed:

| Option | Default | Description |
| ------ | ------- | ----------- |
| `INSTALL_C_EXAMPLES` | _OFF_ | Install C++ sample sources from the _samples/cpp_ directory. |
| `INSTALL_PYTHON_EXAMPLES` | _OFF_ | Install Python sample sources from the _samples/python_ directory. |
| `INSTALL_ANDROID_EXAMPLES` | _OFF_ | Install Android sample sources from the _samples/android_ directory. |
| `INSTALL_BIN_EXAMPLES` | _OFF_ | Install prebuilt sample applications (`BUILD_EXAMPLES` must be enabled). |
| `INSTALL_TESTS` | _OFF_ | Install tests (`BUILD_TESTS` must be enabled). |
| `OPENCV_INSTALL_APPS_LIST` | _all_ | Comma- or semicolon-separated list of prebuilt applications to install (from _apps_ directory) |

Following options allow to modify components' installation locations relatively to install prefix. Default values of these options depend on platform and other options, please check the _cmake/OpenCVInstallLayout.cmake_ file for details.

| Option | Components |
| ------ | ----------- |
| `OPENCV_BIN_INSTALL_PATH` | applications, dynamic libraries (_win_) |
| `OPENCV_TEST_INSTALL_PATH` | test applications |
| `OPENCV_SAMPLES_BIN_INSTALL_PATH` | sample applications |
| `OPENCV_LIB_INSTALL_PATH` | dynamic libraries, import libraries (_win_) |
| `OPENCV_LIB_ARCHIVE_INSTALL_PATH` | static libraries |
| `OPENCV_3P_LIB_INSTALL_PATH` | 3rdparty libraries |
| `OPENCV_CONFIG_INSTALL_PATH` | cmake config package |
| `OPENCV_INCLUDE_INSTALL_PATH` | header files |
| `OPENCV_OTHER_INSTALL_PATH` | extra data files |
| `OPENCV_SAMPLES_SRC_INSTALL_PATH` | sample sources |
| `OPENCV_LICENSES_INSTALL_PATH` | licenses for included 3rdparty components |
| `OPENCV_TEST_DATA_INSTALL_PATH` | test data |
| `OPENCV_DOC_INSTALL_PATH` | documentation |
| `OPENCV_JAR_INSTALL_PATH` | JAR file with Java bindings |
| `OPENCV_JNI_INSTALL_PATH` | JNI part of Java bindings |
| `OPENCV_JNI_BIN_INSTALL_PATH` | Dynamic libraries from the JNI part of Java bindings |

Following options can be used to change installation layout for common scenarios:

| Option | Default | Description |
| ------ | ------- | ----------- |
| `INSTALL_CREATE_DISTRIB` | _OFF_ | Tune multiple things to produce Windows and Android distributions. |
| `INSTALL_TO_MANGLED_PATHS` | _OFF_ | Adds one level to several installation locations to allow side-by-side installations. For example, headers will be installed to _/usr/include/opencv-5.x.y_ instead of _/usr/include/opencv5_ with this option enabled. |


# Miscellaneous features {#tutorial_config_reference_misc}


| Option | Default | Description |
| ------ | ------- | ----------- |
| `OPENCV_ENABLE_NONFREE` | _OFF_ | Some algorithms included in the library are known to be protected by patents and are disabled by default. |
| `OPENCV_FORCE_3RDPARTY_BUILD`| _OFF_ | Enable all `BUILD_` options at once. |
| `OPENCV_IPP_ENABLE_ALL`| _OFF_ | Enable all `OPENCV_IPP_` options at once. |
| `ENABLE_CCACHE` | _ON_ (on Unix-like platforms) | Enable [ccache](https://en.wikipedia.org/wiki/Ccache) auto-detection. This tool wraps compiler calls and caches results, can significantly improve re-compilation time. |
| `ENABLE_PRECOMPILED_HEADERS` | _ON_ (for MSVC) | Enable precompiled headers support. Improves build time. |
| `BUILD_DOCS` | _OFF_ | Enable documentation build (_doxygen_, _doxygen_cpp_, _doxygen_python_, _doxygen_javadoc_ targets). [Doxygen](http://www.doxygen.org/index.html) must be installed for C++ documentation build. Python and [BeautifulSoup4](https://en.wikipedia.org/wiki/Beautiful_Soup_(HTML_parser)) must be installed for Python documentation build. Javadoc and Ant must be installed for Java documentation build (part of Java SDK). |
| `ENABLE_PYLINT` | _ON_ (when docs or examples are enabled) | Enable python scripts check with [Pylint](https://en.wikipedia.org/wiki/Pylint) (_check_pylint_ target). Pylint must be installed. |
| `ENABLE_FLAKE8` | _ON_ (when docs or examples are enabled) | Enable python scripts check with [Flake8](https://flake8.pycqa.org/) (_check_flake8_ target). Flake8 must be installed. |
| `BUILD_JAVA` | _ON_ | Enable Java wrappers build. Java SDK and Ant must be installed. |
| `BUILD_FAT_JAVA_LIB` | _ON_ (for static Android builds) | Build single _opencv_java_ dynamic library containing all library functionality bundled with Java bindings. |
| `BUILD_opencv_python3` | _ON_ | Build python3 bindings. Python with development files and numpy must be installed. |

TODO: need separate tutorials covering bindings builds


## Automated builds

Some features have been added specifically for automated build environments, like continuous integration and packaging systems.

| Option | Default | Description |
| ------ | ------- | ----------- |
| `ENABLE_NOISY_WARNINGS` | _OFF_ | Enables several compiler warnings considered _noisy_, i.e. having less importance than others. These warnings are usually ignored but in some cases can be worth being checked for. |
| `OPENCV_WARNINGS_ARE_ERRORS` | _OFF_ | Treat compiler warnings as errors. Build will be halted. |
| `ENABLE_CONFIG_VERIFICATION` | _OFF_ | For each enabled dependency (`WITH_` option) verify that it has been found and enabled (`HAVE_` variable). By default feature will be silently turned off if dependency was not found, but with this option enabled cmake configuration will fail. Convenient for packaging systems which require stable library configuration not depending on environment fluctuations. |
| `OPENCV_CMAKE_HOOKS_DIR` | _empty_ | OpenCV allows to customize configuration process by adding custom hook scripts at each stage and substage. cmake scripts with predefined names located in the directory set by this variable will be included before and after various configuration stages. Examples of file names: _CMAKE_INIT.cmake_, _PRE_CMAKE_BOOTSTRAP.cmake_, _POST_CMAKE_BOOTSTRAP.cmake_, etc.. Other names are not documented and can be found in the project cmake files by searching for the _ocv_cmake_hook_ macro calls. |
| `OPENCV_DUMP_HOOKS_FLOW` | _OFF_ | Enables a debug message print on each cmake hook script call. |

## Contrib Modules

Following build options are utilized in `opencv_contrib` modules, as stated [previously](#tutorial_config_reference_general_contrib), these extra modules can be added to your final build by setting `DOPENCV_EXTRA_MODULES_PATH` option.

| Option | Default | Description |
| ------ | ------- | ----------- |
| `WITH_CLP` | _OFF_ | Will add [coinor](https://projects.coin-or.org/Clp) linear programming library build support which is required in `videostab` module. Make sure to install the development libraries of coinor-clp. |


# Other non-documented options

`BUILD_ANDROID_PROJECTS`
`BUILD_ANDROID_EXAMPLES`
`ANDROID_HOME`
`ANDROID_SDK`
`ANDROID_NDK`
`ANDROID_SDK_ROOT`

`CMAKE_TOOLCHAIN_FILE`

`WITH_CAROTENE`
`WITH_KLEIDICV`
`WITH_CPUFEATURES`
`WITH_EIGEN`
`WITH_DIRECTX`
`WITH_VA`
`WITH_LAPACK`
`BUILD_ZLIB`
`BUILD_ITT`
`WITH_IPP`
`BUILD_IPP_IW`
