Ubuntu18.04安装集锦2（caffe，GPU版本）

主要参考文献：https://blog.csdn.net/CAU_Ayao/article/details/83536320
1、终端输入

sudo apt install caffe-cuda

这个语句能够在Ubuntu18.04上安装还caffe
但是安装的caffe不完善

2、安装依赖库

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

3、首先我们要从GitHub的远端下载caffe的源码

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

4、配置Makefile.config文件

cd caffe
sudo cp Makefile.config.example Makefile.config
sudo vim Makefile.config

进入Makefile.config后，点击 i 可以进行编辑，点击ESC退出，输入：wq 保存并退出

USE_CUDNN:= 1  （取消这行的注释）
OPENCV_VERSION :=3  （取消这行的注释）

BLAS:= atlas 注销,   换成    BLAS := open.

将 这两行删除掉      -gencode arch=compute_20,code=20 \
                                     -gencode arch=compute_21,code=sm_21 \
删除后剩余的部分是这样子的：
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

将Python2环境注销,换成Anaconda3下的Python环境.

# 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 \      **（注释掉）**
                /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)/anaconda3  **（去掉注释，设置为anaconda3）**
 PYTHON_INCLUDE := $(ANACONDA_HOME)/include \             **（去掉注释，设置为自己的python3.7）**
                $(ANACONDA_HOME)/include/python3.7m \                **（去掉注释，设置为自己的python3.7）**
                $(ANACONDA_HOME)/lib/python3.7/site-packages/numpy/core/include （**去掉注释，设置为自己的python3.7）**

# Uncomment to use Python 3 (default is Python 2)
 PYTHON_LIBRARIES := boost_python3 python3.7m   （去掉注释，设置为自己的python）
# 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   （加上注释）
PYTHON_LIB := $(ANACONDA_HOME)/lib （去掉注释）

若要使用python来编写layer，则将#WITH_PYTHON_LAYER := 1取消注释.

将以下两句后边加上东西

INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib 

修改后为如下

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

OK啦～ vim命令行中输入：wq，可以保存并退出

5、配置Makefile文件

sudo vim Makefile

按 i 开始编辑

PYTHON_LIBRARIES ?= boost_python python2.7
修改为：
PYTHON_LIBRARIES ?= boost_python-py3 python3.7m

NVCCFLAGS +=-ccbin=$(CXX) -Xcompiler-fPIC $(COMMON_FLAGS)
修改为：
NVCCFLAGS += -D_FORCE_INLINES -ccbin=$(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
这个我的不太一样，我的原本的就没有hdf5_hl hdf5，所以我就直接换成hdf5_serial_hl hdf5_serial，但是在下边将有hdf5_hl hdf5这个换成了hdf5_serial_hl hdf5_serial

OK啦～ vim命令行中输入：wq，可以保存并退出

6、Caffe源码中安装Python的必要项

cd /home/li.guangyao/Programming/caffe/python 
pip install --upgrade python-dateutil
for req in $(cat requirements.txt); do pip install $req; done

这里要是出现如下错误

pandas 0.22.0 has requirement python-dateutil>=2, but you'll have python-dateutil 1.5 which is incompatible.
matplotlib 2.1.2 has requirement python-dateutil>=2.1, but you'll have python-dateutil 1.5 which is incompatible.
jupyter-client 5.2.2 has requirement python-dateutil>=2.1, but you'll have python-dateutil 1.5 which is incompatible.
bokeh 0.12.13 has requirement python-dateutil>=2.1, but you'll have python-dateutil 1.5 which is incompatible.
anaconda-client 1.6.9 has requirement python-dateutil>=2.6.1, but you'll have python-dateutil 1.5 which is incompatible.

则https://blog.csdn.net/CAU_Ayao/article/details/83538024按照这个修改一下重新执行for req in $(cat requirements.txt); do pip install $req; done结果图如下：

7、编译caffe

cd /home/luming/caffe
sudo make clean
sudo make all -j16 		//-j16表示使用16核处理器执行当前指令

结果图如下，这个过程我刚开始安装遇到过很多错误，在网上找找也会有答案，但最后一次重新安装可能按照之前顺序来的，make的很顺利，遇到错误别灰心，多来几次，哈哈哈哈哈

（1）这里有个问题，如果遇到以下错误：/usr/bin/ld: 找不到 -lboost_python3

CXX examples/cifar10/convert_cifar_data.cpp
AR -o .build_release/lib/libcaffe.a
LD -o .build_release/lib/libcaffe.so.1.0.0
/usr/bin/ld: 找不到 -lboost_python3
collect2: error: ld returned 1 exit status
Makefile:585: recipe for target '.build_release/lib/libcaffe.so.1.0.0' failed
make: *** [.build_release/lib/libcaffe.so.1.0.0] Error 1

可以参考https://blog.csdn.net/u012505617/article/details/88556621
https://blog.csdn.net/bodybo/article/details/79962814两个文字的内容结合
（2）在编译caffe时，遇到以下问题：

/usr/local/lib/libopencv_imgcodecs.so.3.2.0: undefined reference to `TIFFReadDirectory@LIBTIFF_4.0'
/usr/local/lib/libopencv_imgcodecs.so.3.2.0: undefined reference to `TIFFWriteEncodedStrip@LIBTIFF_4.0'

可以参考https://blog.csdn.net/qiqzhang/article/details/83051203（亲测）

sudo make test -j16 

结果如下：

sudo make runtest -j16

如果遇到.build_release/tools/caffe
.build_release/tools/caffe: error while loading shared libraries: libhdf5_hl.so.100: cannot open shared object file: No such file or directory
Makefile:545: recipe for target ‘runtest’ failed
make: *** [runtest] Error 127

参照https://blog.csdn.net/CAU_Ayao/article/details/83538794完美解决
结果如下：

sudo make pycaffe -j16 		//配置pycaffe
vim ~/.bashrc
export PYTHONPATH=~/Programming/caffe/python:$PYTHONPATH
source ~/.bashrc

8、测试是否成功

import caffe