chartspopla.blogg.se - Cmake install prefix opencv

#CMAKE INSTALL PREFIX OPENCV CODE#

This library will be searched using cmake package mechanism, make sure it is installed correctly or manually set GDAL_DIR environment or cmake variable. It will have higher priority when opening files and can override other backends. GDAL is a higher level library which supports reading multiple file formats including PNG, JPEG and TIFF. In order to use JasPer, OpenJPEG must be disabled. Note OpenJPEG have higher priority than JasPer which is deprecated. Corresponding BUILD_* options will force building and using own libraries, they are enabled by default on some platforms, e.g.

PPM, PGM, PBM, PFM ( WITH_IMGCODEC_PXM, WITH_IMGCODEC_PFM)Īll libraries required to read images in these formats are included into OpenCV and will be built automatically if not found at the configuration stage.

Image reading and writing (imgcodecs module) Built-in formatsįollowing formats can be read by OpenCV without help of any third-party library: TODO: other options: WITH_OPENCL_SVM, WITH_OPENCLAMDFFT, WITH_OPENCLAMDBLAS, WITH_OPENCL_D3D11_NV, WITH_VA_INTEL

#CMAKE INSTALL PREFIX OPENCV CODE#

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. Some parameters of OpenCL integration can be modified using environment variables, e.g. During runtime a working OpenCL runtime is required, to check it run clinfo and/or opencv_version -opencl command. More information can be found in the brief introduction and OpenCL supportĪt the build time this feature does not have any prerequisites. Switch to the OpenCL execution branch happens if input and output image arguments are passed as opaque cv::UMat objects. This integration uses same functions at the user level as regular CPU implementations. Multiple OpenCL-accelerated algorithms are available via so-called "Transparent API (T-API)". TODO: other options: WITH_CUFFT, WITH_CUBLAS, WITH_NVCUVID? OpenCL support Some tutorials can be found in the corresponding section: GPU-Accelerated Computer Vision (cuda module) See also CUDA-accelerated Computer Vision To build opencv and opencv_contrib together check Build with extra modules. Note Since OpenCV version 4.0 all CUDA-accelerated algorithm implementations have been moved to the opencv_contrib repository. These parameters are not documented yet, please consult with the cmake/OpenCVDetectCUDA.cmake script for details. Additional options can be used to control build process, e.g. For cmake versions older than 3.9 OpenCV uses own cmake/FindCUDA.cmake script, for newer versions - the one packaged with CMake. CUDA toolkit must be installed from the official NVIDIA site as a prerequisite. Many algorithms have been implemented using CUDA acceleration, these functions are located in separate modules.

If BUILD_ option is disabled, 3rdparty library will be detected and enabled if found => HAVE_ set to ON if dependency is found.

If BUILD_ option is enabled, 3rdparty library will be built and enabled => HAVE_ set to ON.

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.

Options starting with BUILD_ enable or disable building and using 3rdparty library bundled with OpenCV.

Options starting with WITH_ enable or disable a dependency.

There are three kinds of options used to control dependencies of the library, they have different prefixes: cmake has special option allowing to print all available configuration parameters:Ĭmake -LH. There are many optional dependencies and features that can be turned on or off. | See also GCC instrumentation Build hardening Interprocedural optimization Link time optimization ThinLTO | | ENABLE_THIN_LTO | Clang | Enable thin LTO which incorporates intermediate bitcode to binaries allowing consumers optimize their applications later. | | ENABLE_LTO | GCC, Clang, MSVC | Enable Link Time Optimization (LTO). | | ENABLE_BUILD_HARDENING | GCC, Clang, MSVC | Enable compiler options which reduce possibility of code exploitation. | | OPENCV_ENABLE_MEMORY_SANITIZER | N/A | Enable several quirks in code to assist memory sanitizer. | | ENABLE_COVERAGE | GCC or Clang | Enable code coverage support. | Option | Compiler | Description | | ENABLE_PROFILING | GCC or Clang | Enable profiling compiler and linker options. opencv Note More details on CPU optimization options can be found in wiki: Profiling, coverage, sanitize, hardening, size optimizationįollowing options can be used to produce special builds with instrumentation or improved security.