在tx2上安装opencv和cuDNN

用户1148523

发布于 2019-05-29 15:36:30

1.5K0

发布于 2019-05-29 15:36:30

文章被收录于专栏：FishFish

cuDNN

从 https://developer.nvidia.com/rdp/cudnn-archive 这个网址下载指定的cudnn版本，这里注意如果直接google然后下载的话只是最新版本，需要点击下面的Archived cuDNN Releases才能够找到以前版本的下载，然后选择cuDNN v×.× Library for Linux

下载下来一个压缩文件。将其解压到某个目录下执行：

sudo cp include/cudnn.h /usr/local/cuda/include
sudo cp lib64/libcudnn* /usr/local/cuda/lib64

然后可以查看cudnn的版本：

cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2

opencv

首先从https://opencv.org/releases.html 官网选择需要的opencv版本，然后下载source

下载好之后执行以下语句：

cd $HOME
sudo apt-get install -y \
    libglew-dev \
    libtiff5-dev \
    zlib1g-dev \
    libjpeg-dev \
    libpng12-dev \
    libjasper-dev \
    libavcodec-dev \
    libavformat-dev \
    libavutil-dev \
    libpostproc-dev \
    libswscale-dev \
    libeigen3-dev \
    libtbb-dev \
    libgtk2.0-dev \
    cmake \
    pkg-config
 
# Python 2.7
sudo apt-get install -y python-dev python-numpy python-py python-pytest -y
# GStreamer support
sudo apt-get install -y libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev 
 
cd $HOME/opencv
mkdir build
cd build
# Jetson TX2 
cmake \
    -DCMAKE_BUILD_TYPE=Release \
    -DCMAKE_INSTALL_PREFIX=/usr \
    -DBUILD_PNG=OFF \
    -DBUILD_TIFF=OFF \
    -DBUILD_TBB=OFF \
    -DBUILD_JPEG=OFF \
    -DBUILD_JASPER=OFF \
    -DBUILD_ZLIB=OFF \
    -DBUILD_EXAMPLES=ON \
    -DBUILD_opencv_java=OFF \
    -DBUILD_opencv_python2=ON \
    -DBUILD_opencv_python3=ON \
    -DENABLE_PRECOMPILED_HEADERS=OFF \
    -DWITH_OPENCL=OFF \
    -DWITH_OPENMP=OFF \
    -DWITH_FFMPEG=ON \
    -DWITH_GSTREAMER=ON \
    -DWITH_GSTREAMER_0_10=OFF \
    -DWITH_CUDA=ON \
    -DWITH_GTK=ON \
    -DWITH_VTK=OFF \
    -DWITH_TBB=ON \
    -DWITH_1394=OFF \
    -DWITH_OPENEXR=OFF \
    -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-8.0 \
    -DCUDA_ARCH_BIN=6.2 \
    -DCUDA_ARCH_PTX="" \
    -DINSTALL_C_EXAMPLES=ON \
    -DINSTALL_TESTS=ON \
    -DOPENCV_TEST_DATA_PATH=../opencv_extra/testdata \
    ../
 
# Consider using all 6 cores; $ sudo nvpmodel -m 2 or $ sudo nvpmodel -m 0
make -j4

//这里注意，需要注释build/data/cmake_install.cmake文件中的第75行的if语句，再执行下一步
sudo make install

然后检验是否安装成功: