1.安装前的预备工作
依次按照一下命令安装:
1 sudo apt-get install libprotobuf-dev
2 sudo apt-get install libleveldb-dev
3 sudo apt-get install libsnappy-dev
4 sudo apt-get install libopencv-dev
5 sudo apt-get install libhdf5-serial-dev
6 sudo apt-get install protobuf-compiler
7 sudo apt-get install --no-install-recommends libboost-all-dev
8 sudo apt-get install libatlas-base-dev
9 sudo apt-get install python-dev
10 sudo apt-get install libgflags-dev
11 sudo apt-get install libgoogle-glog-dev
12 sudo apt-get install liblmdb-dev
2.下载caffe源码
在github上下载
git clone https://github.com/BVLC/caffe.git
接着装caffe要求装的一些依赖库(如requirements.txt【$caffe_root/python】中的内容所示):
Cython>=0.19.2
numpy>=1.7.1
scipy>=0.13.2
scikit-image>=0.9.3
matplotlib>=1.3.1
ipython>=3.0.0
h5py>=2.2.0
leveldb>=0.191
networkx>=1.8.1
nose>=1.3.0
pandas>=0.12.0
python-dateutil>=1.4,<2
protobuf>=2.5.0
python-gflags>=2.0
pyyaml>=3.10
Pillow>=2.3.0
six>=1.1.0
可以自己一个一个装,也可以通过以下命令:
1 pip install -r requirements.txt
3.编译caffe
3.1 使用Cmake编译
进入caffe根目录,创建一个build文件夹并进入
1 mkdir build && cd build
进行cmake
接着make
3.2 使用make编译(我使用的这种)
首先因为我们需要的是CPU版本的caffe,因此需要对Makefile进行修改,我们先创建一个副本
1 cp Makefile.config.example Makefile.config
接着对内容进行修改
我们去掉CPU_ONLY前面的注释
# CPU-only switch (uncomment to build without GPU support).
# CPU_ONLY := 1
修改为
# CPU-only switch (uncomment to build without GPU support).
CPU_ONLY := 1
接着python的文件路径需要我们修改
# 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
修改为
PYTHON_INCLUDE := /usr/include/python2.7 \
/usr/local/lib/python2.7/dist-packages/numpy/core/include
hdf5库的路径也需要添加
# Whatever else you find you need goes here.
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
修改为
# Whatever else you find you need goes here.
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5
同时Makefile中的关于hdf5的内容也需要修改
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_hl hdf5
修改为
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial
不然可能会出现以下错误
/usr/bin/ld: cannot find -lhdf5_hl
/usr/bin/ld: cannot find -lhdf5
collect2: error: ld returned 1 exit status
接着开始编译过程
make pycaffe
make all
make test
make runtest
可在其后加上-j"$(nproc)"以加快速度
可能在进行make runtest时出现一些错误,但若前三个命令没有错误出现,就不妨碍使用(暂时没发现什么妨碍的地方)
4.配置环境变量
在.bashrc中配置环境变量
在后面加上
export PYTHONPATH=/your path/caffe/python:$PYTHONPATH
接着
5.测试
Python 2.7.12 (default, Dec 4 2017, 14:50:18)
[GCC 5.4.0 20160609] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import caffe
>>> dir(caffe)
['AdaDeltaSolver', 'AdaGradSolver', 'AdamSolver', 'Classifier', 'Detector', 'Layer', 'NCCL', 'NesterovSolver', 'Net', 'NetSpec', 'RMSPropSolver', 'SGDSolver', 'TEST', 'TRAIN', 'Timer', '__builtins__', '__doc__', '__file__', '__name__', '__package__', '__path__', '__version__', '_caffe', 'classifier', 'detector', 'get_solver', 'has_nccl', 'init_log', 'io', 'layer_type_list', 'layers', 'log', 'net_spec', 'params', 'proto', 'pycaffe', 'set_device', 'set_mode_cpu', 'set_mode_gpu', 'set_multiprocess', 'set_random_seed', 'set_solver_count', 'set_solver_rank', 'solver_count', 'solver_rank', 'to_proto']
>>>
没问题,OK~
官方github:https://github.com/BVLC/caffe
官方安装文档:http://caffe.berkeleyvision.org/installation.html
参考:https://blog.csdn.net/muzilinxi90/article/details/53673184
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