openpose环境搭建（centos7）

蔚落 2022-02-01 13:49 688阅读 0赞

以 nvidia/cuda:9.0-cudnn7-devel-centos7 为基础镜像

基础环境 centos7 cuda9 cudnn7

**安装anaconda3**

wget  https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-5.3.0-Linux-x86\_64.sh -O ~/anaconda.sh && \\

/bin/bash ~/anaconda.sh -b -p /home/root/anaconda3 && \\

rm ~/anaconda.sh && \\

echo "export PATH=/home/root/anaconda3/bin:$PATH" >> ~/.bashrc

**安装opencv**

yum install opencv-devel

pkg-config --modversion opencv

如果输出了opencv2.4 的版本信息，说明安装成功

**安装boost\_1\_58\_0  cmake-3.10.2**

**安装caffe依赖 **

yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel

yum install gflags-devel glog-devel lmdb-devel

yum install openblas-devel

pip install numpy

pip install pandas

下载caffe 在/openpose/3rdparty

git clone https://github.com/BVLC/caffe.git

sudo cp Makefile.config.example Makefile.config

在文件中替换一下几个地方： 
    将
    #USE_CUDNN := 1
    修改成： 
    USE_CUDNN := 1
    ...
     
    #如果此处是OpenCV2，则不用修改
    将
    #OPENCV_VERSION := 3 
    修改为： 
    OPENCV_VERSION := 3
     
    ...
    将
    #WITH_PYTHON_LAYER := 1 
    修改为 
    WITH_PYTHON_LAYER := 1
    ...
     
    INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
    LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib 
    修改为： 
    INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial
    LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu /usr/lib/x86_64-linux-gnu/hdf5/serial       
    ...
     
    CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
            -gencode arch=compute_20,code=sm_21 \
            -gencode arch=compute_30,code=sm_30 \
            -gencode arch=compute_35,code=sm_35 \
            -gencode arch=compute_50,code=sm_50 \
            -gencode arch=compute_52,code=sm_52 \
            -gencode arch=compute_60,code=sm_60 \
            -gencode arch=compute_61,code=sm_61 \
            -gencode arch=compute_61,code=compute_61
    修改为
    CUDA_ARCH := -gencode arch=compute_30,code=sm_30 \
            -gencode arch=compute_35,code=sm_35 \
            -gencode arch=compute_50,code=sm_50 \
            -gencode arch=compute_52,code=sm_52 \
            -gencode arch=compute_60,code=sm_60 \
            -gencode arch=compute_61,code=sm_61 \
            -gencode arch=compute_61,code=compute_61
    ...
    3、然后修改 caffe 目录下的 Makefile 文件：
    
    ...
    将：
    NVCCFLAGS +=-ccbin=$(CXX) -Xcompiler-fPIC $(COMMON_FLAGS)
    替换为：
    NVCCFLAGS += -D_FORCE_INLINES -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS)
    ...
     
    ...
    将：
    LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_hl hdf5
    改为：
    LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial

完整示例如下：

## Refer to http://caffe.berkeleyvision.org/installation.html
    # Contributions simplifying and improving our build system are welcome!
    
    # cuDNN acceleration switch (uncomment to build with cuDNN).
    USE_CUDNN := 1
    
    # CPU-only switch (uncomment to build without GPU support).
    # CPU_ONLY := 1
    
    # uncomment to disable IO dependencies and corresponding data layers
    # USE_OPENCV := 0
    # USE_LEVELDB := 0
    # USE_LMDB := 0
    # This code is taken from https://github.com/sh1r0/caffe-android-lib
    # USE_HDF5 := 0
    
    # uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary)
    #       You should not set this flag if you will be reading LMDBs with any
    #       possibility of simultaneous read and write
    # ALLOW_LMDB_NOLOCK := 1
    
    # Uncomment if you're using OpenCV 3
    # OPENCV_VERSION := 3
    
    # To customize your choice of compiler, uncomment and set the following.
    # N.B. the default for Linux is g++ and the default for OSX is clang++
    # CUSTOM_CXX := g++
    
    # CUDA directory contains bin/ and lib/ directories that we need.
    CUDA_DIR := /usr/local/cuda
    # On Ubuntu 14.04, if cuda tools are installed via
    # "sudo apt-get install nvidia-cuda-toolkit" then use this instead:
    # CUDA_DIR := /usr
    
    # CUDA architecture setting: going with all of them.
    # For CUDA < 6.0, comment the *_50 through *_61 lines for compatibility.
    # For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility.
    # For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility.
    CUDA_ARCH :=    -gencode arch=compute_30,code=sm_30 \
                    -gencode arch=compute_35,code=sm_35 \
                    -gencode arch=compute_50,code=sm_50 \
                    -gencode arch=compute_52,code=sm_52 \
                    -gencode arch=compute_60,code=sm_60 \
                    -gencode arch=compute_61,code=sm_61 \
                    -gencode arch=compute_61,code=compute_61
    
    # BLAS choice:
    # atlas for ATLAS (default)
    # mkl for MKL
    # open for OpenBlas
    BLAS :=open
    # Custom (MKL/ATLAS/OpenBLAS) include and lib directories.
    # Leave commented to accept the defaults for your choice of BLAS
    # (which should work)!
    #BLAS_INCLUDE := /path/to/your/blas
    #BLAS_LIB := /path/to/your/blas
    
    # Homebrew puts openblas in a directory that is not on the standard search path
    # BLAS_INCLUDE := $(shell brew --prefix openblas)/include
    # BLAS_LIB := $(shell brew --prefix openblas)/lib
    
    # This is required only if you will compile the matlab interface.
    # MATLAB directory should contain the mex binary in /bin.
    
    # NOTE: this is required only if you will compile the python interface.
    # We need to be able to find Python.h and numpy/arrayobject.h.
    #PYTHON_INCLUDE := /usr/include/python2.7 \
                    /usr/lib/python2.7/dist-packages/numpy/core/include
    # Anaconda Python distribution is quite popular. Include path:
    # Verify anaconda location, sometimes it's in root.
    ANACONDA_HOME := /home/root/anaconda
    PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
    
    # Uncomment to use Python 3 (default is Python 2)
    PYTHON_LIBRARIES := boost_python python3.7m
    # PYTHON_INCLUDE := /usr/include/python3.5m \
    #                 /usr/lib/python3.5/dist-packages/numpy/core/include
    
    # We need to be able to find libpythonX.X.so or .dylib.
    #PYTHON_LIB := /usr/lib
    # PYTHON_LIB += $(shell brew --prefix numpy)/lib
    
    # Uncomment to support layers written in Python (will link against Python libs)
    WITH_PYTHON_LAYER := 1
    INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
    LIBRARY_DIRS :=  /usr/local/lib /usr/lib /usr/lib64
    
    # INCLUDE_DIRS += $(shell brew --prefix)/include
    # LIBRARY_DIRS += $(shell brew --prefix)/lib
    
    # NCCL acceleration switch (uncomment to build with NCCL)
    # https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0)
    # USE_NCCL := 1
    
    # Uncomment to use `pkg-config` to specify OpenCV library paths.
    # (Usually not necessary -- OpenCV libraries are normally installed in one of thh
    e above $LIBRARY_DIRS.)
    # USE_PKG_CONFIG := 1
    
    # N.B. both build and distribute dirs are cleared on `make clean`
    BUILD_DIR := build
    DISTRIBUTE_DIR := distribute
    
    # Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/cc
    affe/issues/171
    # DEBUG := 1
    
    # The ID of the GPU that 'make runtest' will use to run unit tests.
    TEST_GPUID := 0
    
    # enable pretty build (comment to see full commands)
    Q ?= @

在caffe目录下执行

1.  `# 就是cpu的核心数，j8也就是八核`
2.  `sudo make all -j8`

或者

1.  mkdir build 
2.  cd build 
3.  `cmake -DBLAS=open ..`

**安装openpose**

git clone https://github.com/CMU-Perceptual-Computing-Lab/openpose.git

在3rdparty/caffe/cmake下 修改Dependencies.cmake

# ---[ BLAS
    if(NOT APPLE)
      set(BLAS "Atlas" CACHE STRING "Selected BLAS library")
      set_property(CACHE BLAS PROPERTY STRINGS "Atlas;Open;MKL")
    
      if(BLAS STREQUAL "Atlas" OR BLAS STREQUAL "atlas")
        find_package(OpenBLAS REQUIRED)
        list(APPEND Caffe_INCLUDE_DIRS PUBLIC ${OpenBLAS_INCLUDE_DIR})
        list(APPEND Caffe_LINKER_LIBS PUBLIC ${OpenBLAS_LIB})
      elseif(BLAS STREQUAL "Open" OR BLAS STREQUAL "open")
        find_package(OpenBLAS REQUIRED)
        list(APPEND Caffe_INCLUDE_DIRS PUBLIC ${OpenBLAS_INCLUDE_DIR})
        list(APPEND Caffe_LINKER_LIBS PUBLIC ${OpenBLAS_LIB})
      elseif(BLAS STREQUAL "MKL" OR BLAS STREQUAL "mkl")
        find_package(MKL REQUIRED)
        list(APPEND Caffe_INCLUDE_DIRS PUBLIC ${MKL_INCLUDE_DIR})
        list(APPEND Caffe_LINKER_LIBS PUBLIC ${MKL_LIBRARIES})
        list(APPEND Caffe_DEFINITIONS PUBLIC -DUSE_MKL)
      endif()

此处是因为atlas一直有问题，修改成open一直失败，野路子偷天换日修改。

开启build\_python ON 将会自动编译python包

将model的各种模型放入相应的位置，/openpose/models/getModels.sh

mkdir build

cd build

cmake ..

make -j \`nproc\`

make install

在build/python/openpose下看到pyopenpose.cpython-37m-x86\_64-linux-gnu.so表示安装完成

vi ~/.bashrc

export PYTHONPATH=$PYTHONPATH:/home/root/openpose/build/python
    export LD_LIBRARY_PATH=/usr/lib64:$LD_LIBRARY_PATH
    export PATH=/usr/local/bin/cmake:$PATH
    export PATH=/home/root/anaconda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin

source ~/.bashrc

输入python

\[root@07a2640b80bf models\]\# python  
Python 3.7.0 (default, Jun 28 2018, 13:15:42)   
\[GCC 7.2.0\] :: Anaconda, Inc. on linux  
Type "help", "copyright", "credits" or "license" for more information.  
>>> from openpose import pyopenpose  
>>>

无报错表示安装成功