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  • ubuntu 16.04 安装Opencv-3.2.0_GPU 与 opencv_contrib-3.2.0

    1.准备依赖库

    sudo apt-get install build-essential
    sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
    sudo apt-get install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev
    

    2.下载对应的版本的Opencv与Opencv_contrib并解压,将Opencv_contrib解压到Opencv文件夹中,以便编译

    ※Opencv_contrib要在官网下载,版本号要对应,否则编译会出很多问题

    Opencv: https://opencv.org/releases.html
    Opencv_contrib: https://github.com/opencv/opencv_contrib/releases?after=3.4.3

    3.Cmake构建并编译安装

    cd opencv-3.2.0
    mkdir build
    cd build
    cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=/home/×××/opencv-3.2.0/opencv_contrib/modules/ ..
    sudo make -j8  (8指8线程,尽量用sudo获取权限)
    sudo make install
    

    安装完成  

    检测是否安装成功

    python -c "import cv2; print cv2.__version__"
    

    ERROR:

    1.遇到:nvcc fatal:Unsupported gpu architecture 'compute_20

    解决办法:

    cmake命令加上

    -D CUDA_GENERATION=Kepler 
    

    2.遇到

    CMake Error: The following variables are used in this project, but they are set to NOTFOUND.  Please set them or make sure they are set and tested correctly in the CMake files:  CUDA_nppi_LIBRARY (ADVANCED)

    解决办法:

    在Opencv文件夹:

    (1)找到FindCUDA.cmake文件

    find_cuda_helper_libs(nppi)
    >>
    find_cuda_helper_libs(nppial)
    find_cuda_helper_libs(nppicc)
    find_cuda_helper_libs(nppicom)
    find_cuda_helper_libs(nppidei)
    find_cuda_helper_libs(nppif)
    find_cuda_helper_libs(nppig)
    find_cuda_helper_libs(nppim)
    find_cuda_helper_libs(nppist)
    find_cuda_helper_libs(nppisu)
    find_cuda_helper_libs(nppitc)
    unset(CUDA_nppi_LIBRARY CACHE)
    >>
    unset(CUDA_nppial_LIBRARY CACHE)
    unset(CUDA_nppicc_LIBRARY CACHE)
    unset(CUDA_nppicom_LIBRARY CACHE)
    unset(CUDA_nppidei_LIBRARY CACHE)
    unset(CUDA_nppif_LIBRARY CACHE)
    unset(CUDA_nppig_LIBRARY CACHE)
    unset(CUDA_nppim_LIBRARY CACHE)
    unset(CUDA_nppist_LIBRARY CACHE)
    unset(CUDA_nppisu_LIBRARY CACHE)
    unset(CUDA_nppitc_LIBRARY CACHE)
    
    set(CUDA_npp_LIBRARY "${CUDA_nppc_LIBRARY};${CUDA_nppi_LIBRARY};${CUDA_npps_LIBRARY}")
    >>
    set(CUDA_npp_LIBRARY "${CUDA_nppc_LIBRARY};${CUDA_nppial_LIBRARY};${CUDA_nppicc_LIBRARY};${CUDA_nppicom_LIBRARY};${CUDA_nppidei_LIBRARY};
    ${CUDA_nppif_LIBRARY};${CUDA_nppig_LIBRARY};${CUDA_nppim_LIBRARY};${CUDA_nppist_LIBRARY};${CUDA_nppisu_LIBRARY};${CUDA_nppitc_LIBRARY};${CUDA_npps_LIBRARY}")
    

    (2)找到文件OpenCVDetectCUDA.cmake

    注释掉#

    if(CUDA_GENERATION STREQUAL "Fermi")
    set(__cuda_arch_bin "2.0")
    

    ③在 opencvmodulescudevincludeopencv2cudevcommon.hpp中添加头文件

    #include <cuda_fp16.h>
    

    3.遇到××××××.hpp无法找到文件opencv2/xfeatures2d/cuda.hpp

    解决办法:

    在opencv/modules/stitching/CMakeLists.txt文件中加入xfeatures2d/include的指定路径,即

    INCLUDE_DIRECTORIES("××××××[绝对路径]××××××/opencv_contrib/modules/xfeatures2d/include")

    重新编译即可

    4.如果网络不好,出现ippicv_linux_20151201.tgz无法在终端下载的情况,则可以先单独下载ippicv_linux_20151201.tgz之后,把其移动到终端所提示的路径(终端会提示该路径找不到文件如果同样有其他类似的文件无法下载,方法同上。

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  • 原文地址:https://www.cnblogs.com/haijian/p/10863180.html
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