In this tutorial, I will detail the steps for installing Caffe on a non-GPU(CPU) machine with Ubuntu 14.04 OS. Once we are done with the installation, we’ll also test the GOOGLE INCEPTIONISM (deepdream) code which uses Caffe. This is a follow up post to my last post – Generating images with Google’s “INCEPTIONISM” – deepdream where I had shared some awesome images generated using deepdream code. So, let’s get our hands dirty straight away :smile:.

Firstly, let’s make a directory named deep-learning in the $HOME folder where we will download all the packages.

cd ~
mkdir deep-learning
cd deep-learning

1. Installing the dependencies

To successfully compile Caffe we need to install a few packages first. Execute the below command in the terminal. (These commands will require root access)

NOTE -> Since we will not be using GPUs, we do not require CUDA installation.

# General Dependencies
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

# BLAS -- for better CPU performance
sudo apt-get install libatlas-base-dev

# Python -- It comes preinstalled on Ubuntu 14.04
# Required if you want to use Python wrappers for Caffe
sudo apt-get install the python-dev

# Remaining dependencies
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev

2. Compile and Install Caffe

The Caffe repository is hosted on GitHub. To clone the repository enter the below command in the terminal.

cd ~/deep-learning
git clone
cd caffe

The Makefile.config.example contains the template for configuration file. We’ll use it to write the Makefile.config configuration file.

cp Makefile.config.example Makefile.config

In the Makefile.config file we need to set options if we want to use a CPU or a GPU. Open your favorite editor and uncomment the line CPU_ONLY := 1(most probably, line number 8) as shown below.


After setting the configuration, the next step is to make Caffe or brew Caffe :smile: .

make all
make test
make runtest


If you get an OpenCV undefined reference error in make all as shown below follow the instructions below else move to the section 3.

.build_release/lib/ undefined reference to `cv::imread(cv::String const&, int)'
.build_release/lib/ undefined reference to `cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)'
.build_release/lib/ undefined reference to `cv::imdecode(cv::_InputArray const&, int)'
collect2: error: ld returned 1 exit status
make: *** [.build_release/tools/caffe.bin] Error 1

(Check this issue) for more details. In order to fix the errror, append opencv_imgcodecs on line 176(most probably) as shown below.

LIBRARIES += glog gflags protobuf leveldb snappy \
mdb boost_system hdf5_hl hdf5 m \
opencv_core opencv_highgui opencv_imgproc opencv_imgcodecs

Now clear of the contents of build. This is important else the error will persist.

rm -rf ./build/*

Now rerun the previous commands.

make all
make test
make runtest

3. Adding PYTHON support

To add PYTHON support, run the below commands in the terminal. We need Python support to run the deepdream code.

cd ~/deep-learning/caffe
make pycaffe
echo export PYTHONPATH=~/deep-learning/caffe/python:$PYTHONPATH >> ~/.bashrc

4. Running the INCEPTIONISM code

Read the INCEPTIONISM post by Google Research here

To run the INCEPTIONISM code follow the below instructions.

4.1. Download the GoogLeNet model and clone the deepdream GitHub repository.

cd ~/deep-learning
mv bvlc_googlenet.caffemodel caffe/models/bvlc_googlenet/
git clone

4.2. Install the dependencies

sudo pip install "ipython[all]" 
sudo pip install numpy
sudo pip install scipy
sudo pip install protobuf
sudo pip install skimage

4.3. Run the IPython Notebook

cd ~/deep=learning/deepdream
ipython notebook 

Now the IPython notebook dashboard will open up in your default browser as shown below.

Snapshot of IPython Notebook Dashboard
Figure 1: Snapshot of IPython Notebook Dashboard [PNG]

In the list of files, click on dream.ipynb and you will get an output as shown in the figure below.

Snapshot of IPython Notebook
Figure 2: Snapshot of IPython Notebook [PNG]

So, this is it ! Use this IPython Notebook to play with the deepdream code to generate some awesome images. I hope you liked the post and THANK YOU :smile: for reading.

  1. Caffe GitHub repository
  2. deepdream GitHub repository
  3. GoogLeNet Caffe Model