Ubuntu 16.04 + Opencv3.0 + gtx1080 + caffe(SSD) + ROS(Kinetic)

this part records the process of installing opencv and caffe on ubuntu 16.04 with gtx1080 gpu.

Installing ubuntu16.04
since we didn’t succeed in installing ubuntu14.04 on this server,so we installed the ubuntu16.04.
Installing the nvidia driver
- check what driver should we install sudo ubuntu-drivers devices
- add the repository sudo add-apt-repository ppa:graphics-drivers
- install driver (change the driver num according to your own server)
  
  sudo apt-get update
  sudo apt-get install nvidia-367 mesa-common-dev freeglut3-dev
- reboot to effect the driver
- test the driver by nvidia-smi
Installing cuda8.0
- download the cuda8.0 from the NVIDIA official website,recommend the run file instead of deb
- install the cuda,e.g. sh cuda_8.0.27_linux.run,notice that:
  - DON’T INSTALL THE DRIVER IN THE RUN FILE,it will overide the driver we installed just now.
  - DON’T INSTALL THE OPENGL LIB,you cannot log in even with the correct password.
- add the cuda/bin and lib to the PATH AND PROFILE
  
  sudo vim /etc/profile
  export PATH=/usr/local/cuda/bin:$PATH
  
  sudo vim /etc/ld.so.conf.d/cuda.conf
  /usr/local/cuda/lib64
- test the example in ~/NVIDIA *. note that the gcc/g++ version in ubuntu 16.04 is >=5.3,maybe cause some errors,so we modified the /usr/local/cuda/include/host_config.h to support 5.3 version gcc/g++.
  
  sudo vim /usr/local/cuda/include/host_config.h
  find the if _GNUC_ > 5,change the 5 to 6
  cd ~/Nvidia(tab)
  make -j16
  cd bin/…/
  ./deviceQuery
if you get the pass result,install corectly.

Installing Opencv3.0
there are two things we need to pay attention to in installing opencv3.0:

build opencv without rebuilding the tiff lib
modified src file to support cuda8.0

Installing steps are summarized below:

download the installing shell script from private cloud disk(code: wysa)
install dependencies sudo sh dependencies.sh
run the opencv3_0_0.sh to get src file sudo sh opencv3_0_0.sh,note that maybe we will stop at the downloading ippcv,we can pre-download this file from here and put it in OpenCV-master/3rdparty/ippicv/downloads/Linux-xxxx/
since in ubuntu16.04,the libtiff version is 5,not 4. so we need to modified the opencv3_0_0.sh to ignore the installation of libtiff4-dev as follows. simply delete the libtiff4-dev and add -D WITH_TIFF=ON in cmake command

original opencv3_0_0.sh

arch=$(uname -m)
if [ "$arch" == "i686" -o "$arch" == "i386" -o "$arch" == "i486" -o "$arch" == "i586" ]; then
flag=1
else
flag=0
fi
echo "Installing OpenCV 3.0.0"
mkdir OpenCV
cd OpenCV
echo "Removing any pre-installed ffmpeg and x264"
sudo apt-get -y remove ffmpeg x264 libx264-dev
echo "Installing Dependenices"
sudo apt-get -y install libopencv-dev
sudo apt-get -y install build-essential checkinstall cmake pkg-config yasm
sudo apt-get -y install libtiff4-dev libjpeg-dev libjasper-dev
sudo apt-get -y install libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev
sudo apt-get -y install python-dev python-numpy
sudo apt-get -y install libtbb-dev
sudo apt-get -y install libqt4-dev libgtk2.0-dev
sudo apt-get -y install libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev
sudo apt-get -y install x264 v4l-utils ffmpeg
sudo apt-get -y install libgtk2.0-dev
echo "Downloading OpenCV 3.0.0"
wget -O opencv-3.0.0.zip http://sourceforge.net/projects/opencvlibrary/files/opencv-unix/3.0.0/opencv-3.0.0.zip/download
echo "Installing OpenCV 3.0.0"
unzip opencv-3.0.0.zip
cd opencv-3.0.0
mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_OPENGL=ON ..
make -j4
sudo make install
sudo sh -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf'
sudo ldconfig
echo "OpenCV 3.0.0 ready to be used"

modified opencv3_0_0.sh

arch=$(uname -m)
if [ "$arch" == "i686" -o "$arch" == "i386" -o "$arch" == "i486" -o "$arch" == "i586" ]; then
flag=1
else
flag=0
fi
echo "Installing OpenCV 3.0.0"
mkdir OpenCV
cd OpenCV
echo "Removing any pre-installed ffmpeg and x264"
sudo apt-get -y remove ffmpeg x264 libx264-dev
echo "Installing Dependenices"
sudo apt-get -y install libopencv-dev
sudo apt-get -y install build-essential checkinstall cmake pkg-config yasm
sudo apt-get -y install libjpeg-dev libjasper-dev
sudo apt-get -y install libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev
sudo apt-get -y install python-dev python-numpy
sudo apt-get -y install libtbb-dev
sudo apt-get -y install libqt4-dev libgtk2.0-dev
sudo apt-get -y install libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev
sudo apt-get -y install x264 v4l-utils ffmpeg
sudo apt-get -y install libgtk2.0-dev
echo "Downloading OpenCV 3.0.0"
wget -O opencv-3.0.0.zip http://sourceforge.net/projects/opencvlibrary/files/opencv-unix/3.0.0/opencv-3.0.0.zip/download
echo "Installing OpenCV 3.0.0"
unzip opencv-3.0.0.zip
cd opencv-3.0.0
mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_OPENGL=ON -D WITH_TIFF=ON ..
make -j4
sudo make install
sudo sh -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf'
sudo ldconfig
echo "OpenCV 3.0.0 ready to be used"

modified the graphcuts.cpp to support cuda8.0

Installing cudnn
Installing the cudnn v5 for cuda8.0

tar xvzf cudnn-8.0-linux-x64-v5.0-ga.tgz
sudo cp cuda/include/cudnn.h /usr/local/cuda/include
sudo cp cuda/lib64/. /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
cd /usr/local/cuda/lib64/
sudo rm -rf libcudnn.so libcudnn.so.5
sudo ln -s libcudnn.so.5.1.5 libcudnn.so.5
sudo ln -s libcudnn.so.5 libcudnn.so
sudo ldconfig
Installing additionale package

package name	command
python-tk	`sudo apt-get install python-tk`

Installing caffe (using python2.7 not anaconda,otherwise maybe cause conflict between anaconda and system python)
- Basic dependience
  
  sudo apt-get update
  sudo apt-get install -y build-essential cmake git pkg-config
  sudo apt-get install -y libprotobuf-dev libleveldb-dev libsnappy-dev libhdf5-serial-dev protobuf-compiler
  sudo apt-get install -y libatlas-base-dev
  sudo apt-get install -y –no-install-recommends libboost-all-dev sudo apt-get install -y libgflags-dev libgoogle-glog-dev liblmdb-dev
  sudo apt-get install -y python-pip python-dev python-numpy python-scipy # (Python general)
  sudo apt-get install libopencv-dev
- git clone caffe and install python dependience
  
  git clone https://github.com/BVLC/caffe.git
  cd caffe-master/python
  for req in $(cat requirements.txt); do pip install $req; done
note which package isn’t installed correctly,re-install it.
- modified Makefile.config

## 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

# 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 lines for compatibility.
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_50,code=compute_50

# BLAS choice:
# atlas for ATLAS (default)
# mkl for MKL
# open for OpenBlas
BLAS := atlas
# 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.
# MATLAB_DIR := /usr/local
# MATLAB_DIR := /Applications/MATLAB_R2012b.app

# 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)/anaconda
# PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
        # $(ANACONDA_HOME)/include/python2.7 \
        # $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include \

# Uncomment to use Python 3 (default is Python 2)
# PYTHON_LIBRARIES := boost_python3 python3.5m
# 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 := $(ANACONDA_HOME)/lib

# Homebrew installs numpy in a non standard path (keg only)
# PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include
# PYTHON_LIB += $(shell brew --prefix numpy)/lib

# Uncomment to support layers written in Python (will link against Python libs)
WITH_PYTHON_LAYER := 1

# 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 \
               /usr/lib/x86_64-linux-gnu/hdf5/serial      

# If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies
# INCLUDE_DIRS += $(shell brew --prefix)/include
# LIBRARY_DIRS += $(shell brew --prefix)/lib

# Uncomment to use `pkg-config` to specify OpenCV library paths.
# (Usually not necessary -- OpenCV libraries are normally installed in one of the 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/caffe/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 ?= @

compile and test

cd ~/caffe-master
make all -j16
make test -j16
make runtest -j16
make pycaffe
test pycaffe

export PYTHONPATH=~/caffe-master/python:$PYTHONPATH
in python,import caffe

if no error occurs,we install caffe correctly

echo ‘export PYTHONPATH=~/caffe-master/python’ >> ~/.bashrc

Installing SSD
most part is the same as compiling caffe,record the process as below.
- git clone SSD (in home directory)
  
  git clone https://github.com/weiliu89/caffe.git
  cd caffe
  git checkout ssd
- modified the Makefile.config file (same as caffe’s Makefile.config,so we just copy it here)
  
  cp ~/caffe-master/Makefile.config ~/caffe/
- compile and test
  
  cd ~/caffe
  mkdir build
  cd build
  cmake ..
  make all -j16
  make install
  make runtest
  make pycaffe
ROS-Kinetic
Reference:
Ubuntu16.04 + cuda8.0 + GTX1080 + matlab14.04a + Opencv3.0 + caffe 安装教程
 GTX1070+CUDA8.0+Ubuntu16.04+Caffe+SSD 深度学习框架搭建细节一步到位版
 SSD的配置安装与测试

原文链接：https://www.f2er.com/ubuntu/355556.html

Ubuntu 16.04 + Opencv3.0 + gtx1080 + caffe(SSD) + ROS(Kinetic)

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