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NVIDIA TX2上配置OpenCV3+Pytorch

NVIDIA TX2上配置OpenCV3+Pytorch

作者: Qfffffff_ | 来源:发表于2019-11-18 16:03 被阅读0次

    Tips:

    最初环境为TX2刷机后环境。此时Python为Python 2.7.11+
    YOLO2适用于Python3 + OpenCV3。配置时需注意。

    一、设置Python默认版本 - Python2与Python3切换

    1、此时python环境为2.7.11+

    python
    Python 2.7.11+(default,Apr 17 2016,14:00:29)
    

    2、进入/usr/bin,并执行两条命令

    cd /usr/bin
    user@ubuntu:/usr/bin$ sudo update-alternatives --install /usr/bin/python python /usr/bin/python2 100
    update-alternatives: using /usr/bin/python2 to provide /usr/bin/python (python) in auto mode
    user@ubuntu:/usr/bin$ sudo update-alternatives --install /usr/bin/python python /usr/bin/python3 150
    update-alternatives: using /usr/bin/python3 to provide /usr/bin/python (python) in auto mode
    

    3、再次查看已经变成3.5了

    user@ubuntu:/usr/bin$ python
    Python 3.5.2 (default, Nov 17 2016, 17:05:23) 
    

    4、怎么随意切换

    user@ubuntu:/usr/bin$ sudo update-alternatives --config python
    There are 2 choices for the alternative python (providing /usr/bin/python).
    
      Selection    Path              Priority   Status
    ------------------------------------------------------------
    * 0            /usr/bin/python3   150       auto mode
      1            /usr/bin/python2   100       manual mode
      2            /usr/bin/python3   150       manual mode
    
    Press <enter> to keep the current choice[*], or type selection number: 1
    update-alternatives: using /usr/bin/python2 to provide /usr/bin/python (python) in manual mode
    
    #数字前面有*号表示是当前使用版本,输入1切换到2.7,再次查看如下
    
    user@ubuntu:/usr/bin$ sudo update-alternatives --config python
    There are 2 choices for the alternative python (providing /usr/bin/python).
    
      Selection    Path              Priority   Status
    ------------------------------------------------------------
      0            /usr/bin/python3   150       auto mode
    * 1            /usr/bin/python2   100       manual mode
      2            /usr/bin/python3   150       manual mode
    
    Press <enter> to keep the current choice[*], or type selection number:
    

    二、配置相关库文件(python3)

    1、安装pip/numpy/scipy/matplotlib等

    # 安装python3-dev,安装这个包,以后安装各种python扩展包,可以省很多事情
    sudo apt-get install python3-dev
    
    # 使用apt-get安装
    sudo apt-get install python3-pip
    sudo apt-get install python3-numpy
    sudo apt-get install python3-scipy
    sudo apt-get install python3-matplotlib
    
    

    2、安装cython/h5py等(YOLO2需要)

    sudo pip3 install cython
    sudo apt-get install libhdf5-dev
    sudo pip3 install h5py
    

    3、cffi库的安装

    # 1// 能简单粗暴的安装最好
    sudo apt-get install cffi
    
    # 2// 如果不行呢 反正QFF可以这样装
    sudo apt-get install python3-dev libffi-dev
    sudo pip3 install cffi
    

    三、配置OpenCv3.3.1 with python 3.5

    1、安装各种依赖库

    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、cmake配置编译

    # 建立一个build文件夹
    cd ~/opencv
    mkdir build
    cd build  
    
    # 编译配置opencv
    cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D PYTHON3_EXECUTABLE=/usr/bin/python3 -D PYTHON_INCLUDE_DIR=/usr/include/python3.5 -D PYTHON_LIBRARY=/usr/lib/x86_64-linux-gnu/libpython3.5m.so -D PYTHON3_NUMPY_INCLUDE_DIRS=/usr/local/lib/python3.5/dist-packages/numpy/core/include -D INSTALL_PYTHON_EXAMPLES=ON -D INSTALL_C_EXAMPLES=OFF -D OPENCV_EXTRA_MODULES_PATH=~/opencv_contrib/modules -D PYTHON_EXECUTABLE=/usr/lib/python3 -D BUILD_EXAMPLES=ON ..
    
    # ok之后
    make -j7
    sudo make install
    

    3、Install procedure for pyTorch on NVIDIA Jetson TX1/TX2

    #!/bin/bash
    #
    # pyTorch install script for NVIDIA Jetson TX1/TX2,
    # from a fresh flashing of JetPack 2.3.1 / JetPack 3.0 / JetPack 3.1
    #
    # for the full source, see jetson-reinforcement repo:
    #   https://github.com/dusty-nv/jetson-reinforcement/blob/master/CMakePreBuild.sh
    #
    # note:  pyTorch documentation calls for use of Anaconda,
    #        however Anaconda isn't available for aarch64.
    #        Instead, we install directly from source using setup.py
    sudo apt-get install python-pip
    
    # upgrade pip
    pip install -U pip
    pip --version
    # pip 9.0.1 from /home/ubuntu/.local/lib/python2.7/site-packages (python 2.7)
    
    # clone pyTorch repo
    git clone http://github.com/pytorch/pytorch
    cd pytorch
    git submodule update --init
    
    # install prereqs
    sudo pip install -U setuptools
    sudo pip install -r requirements.txt
    
    # Develop Mode:
    python setup.py build_deps
    sudo python setup.py develop
    
    # Install Mode:  (substitute for Develop Mode commands)
    #sudo python setup.py install
    
    # Verify CUDA (from python interactive terminal)
    # import torch
    # print(torch.__version__)
    # print(torch.cuda.is_available())
    # a = torch.cuda.FloatTensor(2)
    # print(a)
    # b = torch.randn(2).cuda()
    # print(b)
    # c = a + b
    # print(c)
    

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