# caffe-gpu安装 anaconda环境


sudo apt-get install git 
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
sudo apt-get install --no-install-recommends libboost-all-dev
sudo apt-get install libatlas-base-dev
sudo apt-get install python-dev
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev


git clone htttps://github.com/bvlc/caffe.git
cd caffe
mv Makefile.config.example Makefile.config


# 修改Makefile.config
sudo gedit Makefile.config


1. USE_CUDNN := 1
2. OPENCV_VERSION := 3


# 这里建议不要用anaconda要不上面安装的库用不了了,编译就都是问题
3.PYTHON_INCLUDE := /usr/include/python3.5m \
  /usr/lib/python3.5/dist-packages/numpy/core/include
4. PYTHON_LIB := /usr/lib
5. WITH_PYTHON_LAYER := 1
6.INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib /usr/lib/x86_64-linux-gnu /usr/lib/x86_64-linux-gnu/hdf5/serial
7.因为我的是9.0还要注释下面两行：
# For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility.
CUDA_ARCH := # -gencode arch=compute_20,code=sm_20 \
     #  -gencode arch=compute_20,code=sm_21 \


# 修改Makefile
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial opencv_core opencv_highgui opencv_imgproc opencv_imgcodecs


#修改~/.bashrc
export PYTHONPATH=/home/XXX/caffe/python:$PYTHONPATH   # XXX为自己的用户名
LD_LIBRARY_PATH=$HOME/caffe/build/lib:/usr/lib/x86_64-linux-gnu:/usr/lib:$LD_LIBRARY_PATH



# 修改/etc/profile
export PATH=/usr/local/cuda-9.0/bin:$PATH
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/lib


make -j4
# 如果之前make过可以先执行make clean再重新make