Ubuntu 16.04 or 15.10 Installation Guide
The following guide includes the how-to instructions for the installation of BVLC/Caffe in Ubuntu 16.04 (preliminary procedure does not function with the current Cuda Toolkit) or 15.10 Linux (works well). This also includes the KUbuntu 16.04 or 15.10 and the related distributions.
Execute these commands first:
sudo apt-get update
sudo apt-get upgrade
sudo apt-get install build-essential cmake git pkg-config
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libhdf5-serial-dev protobuf-compiler
sudo apt-get install libatlas-base-dev
sudo apt-get install --no-install-recommends libboost-all-dev
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev
(Python general)
sudo apt-get install python-pip
(Python 2.7 development files)
sudo apt-get install python-dev
sudo apt-get install python-numpy python-scipy
(or, Python 3.5 development files)
sudo apt-get install python3-dev
sudo apt-get install python3-numpy python3-scipy
(OpenCV 2.4)
sudo apt-get install libopencv-dev
(or, OpenCV 3.1 - see the instructions below)
For the instructions on how to use the OpenCV version 3.1, please see https://github.com/BVLC/caffe/wiki/Ubuntu-16.04-or-15.10-OpenCV-3.1-Installation-Guide
The configuration settings will differ for OpenCV 3.1 as you can see above, but here we continue with the basic settings that imply the version 2.x.
Go to the https://github.com/BVLC/caffe and download zip archive. Unpack it to ~/bin/ or any other location. Enter the caffe-master directory in the terminal window.
Copy the Makefile.config.example to Makefile.config like this:
cp Makefile.config.example Makefile.config
and open it for editing (with a text editor). I use the kate editor for this purpose, so the command that I execute goes as follows. You first need to install the kate editor with:
sudo apt-get install kate
and then you can edit the configuration file with:
kate ./Makefile.config &
The following line in the configuration file tells the program to use CPU only for the computations.
CPU_ONLY := 1
This is the typical setting for a computer without any NVIDIA graphics card and it is typical for the installation of Caffe inside the typical virtual machine. (Notice that there is a special type of virtual machine inside the Ubuntu host machine that can access the physical NVIDIA graphics card directly. See https://github.com/NVIDIA/nvidia-docker)
Change the line accordingly by commenting it out (# CPU_ONLY := 1) if you have an NVIDIA graphics card with the proprietary driver, CUDA toolkit and CUDNN installed. The Makefile.config should contain the following lines, so find them and fill them in.
PYTHON_INCLUDE := /usr/include/python2.7 /usr/lib/python2.7/dist-packages/numpy/core/include
(For ways to create an isolated Python environment, explore the topic of virtual environments here: http://docs.python-guide.org/en/latest/dev/virtualenvs/)
WITH_PYTHON_LAYER := 1
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
Now lets continue with the instructions for version 15.10.
Execute the additional commands:
find . -type f -exec sed -i -e 's^"hdf5.h"^"hdf5/serial/hdf5.h"^g' -e 's^"hdf5_hl.h"^"hdf5/serial/hdf5_hl.h"^g' '{}' \;
cd /usr/lib/x86_64-linux-gnu
sudo ln -s libhdf5_serial.so.8.0.2 libhdf5.so
sudo ln -s libhdf5_serial_hl.so.8.0.2 libhdf5_hl.so
In Ubuntu 16.04, the file versions are different. Visit /usr/lib/x86_64-linux-gnu/ and list the contents. The versions are 10.1.0 and 10.0.2 respectively.
Now lets return to the unpacked Caffe directory caffe-master and enter these commands:
cd python
for req in $(cat requirements.txt); do pip install $req; done
NOTE: If the Ubuntu operating system was updated, perhaps the Python layer needs to be updated and recompiled, because the Python module no longer works. Perform this step again in that case.
for req in $(cat requirements.txt); do pip install $req; done
In case of any problems, try:
for req in $(cat requirements.txt); do sudo -H pip install $req --upgrade; done
The build process will fail in Ubuntu 16.05 due to the GCC 5.x compiler, when compiling Cuda 7.5 sources. The updated version of Cuda Toolkit is required! The workaround is pending... You may try to use an older compiler. This is how it might go:
sudo apt-get install g++-4.9 gcc-4.9 libgcc-4.9
sudo update-alternatives --remove-all gcc
sudo update-alternatives --remove-all g++
sudo update-alternatives --remove-all cc
sudo update-alternatives --remove-all c++
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 10
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.9 20
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-5 10
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-4.9 20
sudo update-alternatives --install /usr/bin/cc cc /usr/bin/gcc 30
sudo update-alternatives --set cc /usr/bin/gcc
sudo update-alternatives --install /usr/bin/c++ c++ /usr/bin/g++ 30
sudo update-alternatives --set c++ /usr/bin/g++
sudo update-alternatives --query gcc
sudo update-alternatives --query g++
sudo update-alternatives --query cc
sudo update-alternatives --query c++
No, this does not help the Ubuntu 16.04 for now. You could try to pass an argument (CXX_FLAGS) to the compiler -D_FORCE_INLINES by editing the CMAKE files (for example: set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -D_FORCE_INLINES")) or makefiles. The procedure is not specified. This should work, or you must wait for an updated Cuda Toolkit sources to compile with the associated software in Ubuntu 16.04 such as Caffe, Torch and Theano.
Next, in any case execute:
cd ..
(now you are in caffe-master directory)
make all
make test
make runtest
make pycaffe -should be finished already, so you can omit this one
make distribute
In order to make the Python work with Caffe, open the file ~/.bashrc for editing in your favorite text editor. There, add the following line at the end of file:
export PYTHONPATH=/path/to/caffe-master/python:$PYTHONPATH
You can also execute that same line immediately as a command for immediate effects.
In order to use the Caffe binaries, libraries, or include files, they need to be reachable through the search path, so one solution is to copy them into their respective directories: from the distribute directory to the /usr/bin or /usr/lib or /usr/include.
- Models download not covered in these instructions. See https://github.com/BVLC/caffe/wiki/Model-Zoo *
For most Linux programs compiled from source, you can attempt to build a package that can be installed and uninstalled with a single click.
sudo apt-get install checkinstall
Now, when you execute the:
sudo checkinstall
and fill out a form with some easy questions, you will have the package made automatically. However, this uses the command "make install" in the background, which will fail, because the Caffe project does not have the target "install" configured in the Makefile.
In Ubuntu desktop, enable the use of proprietary drivers in the Software & Updates Center for your desktop and install the NVIDIA graphics driver first from the main Ubuntu package repository. See https://help.ubuntu.com/community/BinaryDriverHowto/Nvidia
Alternatively, the best option is to use the Muon package manager (especially in Kubuntu 16.04). There you will find the NVIDIA driver and Cuda Toolkit packages. They are given through the standard Canonical and Canonical Partners software sources (repositories). Before this installation occurs, you may need to install the Muon manager itself with the following command:
sudo apt-get install muon
and discover which driver number you need with:
sudo ubuntu-drivers devices
If you don't use Muon, download the CUDA toolkit network installer and the CUDNN package from the NVIDIA site, after registering and filling out the forms. https://developer.nvidia.com/cuda-downloads
Install the cuda toolkit 7.5 version manually in the terminal as instructed at the website.
sudo dpkg -i cuda-repo-ubuntu1504_7.5-18_amd64.deb
sudo apt-get update
sudo apt-get install cuda
Download and install .deb package for the CUDNN 5 library from https://developer.nvidia.com/cudnn.
Alternatively, put all the downloaded and unpacked CUDNN version 4 files manually starting with the search path directory where the CUDA toolkit is, each file in its own respective directory. That directory could be /usr/local/cuda or /usr if you installed from the Muon package manager. CUDNN 4 works with Caffe.
Example of unpacking and installing the CUDNN 4 archive. The unpacked directory content should be copied from /lib64 directory to /usr/lib/x86_64-linux-gnu/ and from /include directory to /usr/include/.
You can check your Ubuntu environment variables after the reboot, by executing the command:
export
Edit the Makefile.config in Caffe directory accordingly (as described in the config file itself) and recompile the Caffe to support the GPU computation. To recompile, first execute "make clean".