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My notes on how to install caffe on Ubuntu

Caffe Installation

Note on how to install caffe on Ubuntu. Sucessfully install using CPU, more information for GPU see this link


  • verify all the preinstallation according to CUDA guide e.g.
lspci | grep -i nvidia
uname -m && cat /etc/*release
 gcc --version
  • install CUDA on Ubuntu, following this site to install CUDA. We get .deb file and dpkg from CUDA download page (add CUDA path to .bashrc, see below)
sudo dpkg -i cuda-repo-ubuntu1404_6.5-14_amd64.deb
sudo apt-get update
sudo apt-get install cuda
  • More to do see post installion at this link where we change directory to ~/NVIDIA_CUDA-6.5_Samples then type make. Afterward, run deviceQuery under ~/NVIDIA_CUDA-6.5_Samples

  • install BLAS (from libopenblas) and git (and unzip for opencv)

sudo apt-get install libopenblas-dev git unzip
  • install opencv, follow this site where I use this bash script to install opencv
chmod +x 
  • install Anaconda from this link then run

(add Anaconda path to .bashrc, see below)

  • install Boost using this command:
sudo apt-get install libboost-all-dev
  • install others by following Caffe documentation
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev protobuf-compiler
  • Get latest version of protobuf using pip
pip install protobuf
  • Then clone caffe and follow the instruction
git clone
cp Makefile.config.example Makefile.config
# Adjust Makefile.config (for example, if using Anaconda Python)
make all
make test
make runtest
  • Note that we apply this to anaconda according to Caffe issue
rm ~/anaconda/lib/libm.*
  • And I also do something like in /usr/lib/x86_64-linux-gnu/:
sudo cp
sudo cp

(according to this issue on Caffe)

  • After that we can make python interface for caffe - make pycaffe (in caffe/python)

###Customization Caffe

  • This is what I added to .bashrc
# CUDA                                                                                                     
export PATH=/usr/local/cuda-6.5/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-6.5/lib64:$LD_LIBRARY_PATH
export PATH
# Anaconda
export PATH=/home/ubuntu/anaconda/bin:$PATH
# Caffe Root
export CAFFE_ROOT=/home/ubuntu/caffe

###Error Found

  • According to tutorial When running ./examples/mnist/, I got following error:
libdc1394 error: Failed to initialize libdc1394
I0109 02:31:21.168457 30295 caffe.cpp:99] Use GPU with device ID 0
F0109 02:31:21.168894 30295 common.cpp:53] CPU-only Mode: cannot make GPU call.
  • Above problem solved by changing solver_mode: GPU to CPU in /caffe/examples/mnist/lenet_solver.prototxt
  • More installation: pip install protobuf

###To do list

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