Installation Script for Caffe & DeepDream on Debian 8

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Hi All,

I've made a script that does most of the install on Debian 8. Details below.

If you have any issues, feel free to reply to this post and i will reply as soon as i can

The script contains 3 files, as follows:

"dp.sh"

#!/bin/bash

sudo apt-get install ipython python-pil python-numpy python-scipy libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev python-dev libgflags-dev libgoogle-glog-dev liblmdb-dev protobuf-compiler libblas-common libblas-dev libblas-doc libblas-test libblas3 libblas3gf hdf5-helpers hdf5-tools libhdf5-8 libhdf5-8-dbg libhdf5-cpp-8 libhdf5-cpp-8-dbg libhdf5-dev libhdf5-doc libhdf5-mpi-dev libhdf5-mpich-8 libhdf5-mpich-8-dbg libhdf5-mpich-dev libhdf5-mpich2-dev libhdf5-openmpi-8 libhdf5-openmpi-8-dbg libhdf5-openmpi-dev libhdf5-serial-dev libhdf5-8 libhdf5-8-dbg libhdf5-dev libpdl-io-hdf5-perl libatlas-base-dev libatlas-dev libatlas-doc libatlas-test libatlas3-base libatlas3gf-base python-protobuf python-snappy libgflags-dev leveldb-doc snappy lmdb-utils lmdb-doc lmdb-dbg liblmdb0 liblmdb-dev nvidia-cuda-toolkit curl ipython-notebook Cython python-dateutil python-gflags python-numpy-dbg python-numpy-doc python-numpydoc python3-numpy python3-numpy-dbg python-scipy-dbg python-scipy-doc python-sciscipy python3-scipy python3-scipy-dbg python-matplotlib python-matplotlib-data python-matplotlib-dbg python-matplotlib-doc python-matplotlib-venn python3-matplotlib python3-matplotlib-dbg python3-matplotlib-venn python-h5py python-h5py-doc python3-h5py golang-goleveldb-dev libleveldb-api-java libleveldb-cil-dev libleveldb-dbg libleveldb-java libleveldb1 libleveldb1.2-cil python-leveldb python3-leveldb python-networkx python-networkx-doc python3-networkx python-django-nose python-nose python-nose-doc python-nose-parameterized python-nose-testconfig python-nose-timer python-nose-yanc python-nose2 python-nose2-cov python-nose2-doc python-nosehtmloutput python-nosexcover python-openstack.nose-plugin python-rednose python3-django-nose python3-nose python3-nose-parameterized python3-nose-timer python3-nose2 python3-nose2-cov python3-nosexcover python3-openstack.nose-plugin python3-rednose python-pandas python-pandas-doc python-pandas-lib python3-pandas python3-pandas-lib python-pil.imagetk python-sane python-pyocr python3-pyocr python-pil python-syck python-pip python-yaml

sudo apt-get install --no-install-recommends libboost-all-dev

sudo apt-get update

sudo apt-get upgrade

cd /usr/lib/x86_64-linux-gnu

sudo ln -s libhdf5_serial.so.8.0.2 libhdf5.so

sudo cp libhdf5.so libhdf5.so.10 

sudo ln -s libhdf5_serial_hl.so.8.0.2 libhdf5_hl.so

sudo cp libhdf5_hl.so libhdf5_hl.so.10 

# PROTOBUF

cd ~/Downloads

sudo rm master.zip

wget https://github.com/google/protobuf/releases/download/v2.6.1/protobuf-2.6.1.tar.gz

tar -zxvf protobuf-2.6.1.tar.gz

cd protobuf-2.6.1/

sudo ./configure

sudo make

sudo make check

sudo make install

# SCIKIT

sudo pip install -U scikit-image

# CAFFE

cd ~/Downloads

sudo rm master.zip

wget https://github.com/BVLC/caffe/archive/master.zip

unzip master.zip

cp ~/Downloads/Makefile.config ~/Downloads/caffe-master

cd caffe-master/

sudo make all -j8

sudo make test

sudo make runtest

sudo make pycaffe

sudo make distribute

# DEEPDREAM

cd ~/Downloads

sudo rm master.zip

wget https://github.com/google/deepdream/archive/master.zip

unzip master.zip

sudo rm master.zip

# FINAL UPDATES

sudo apt-get update

sudo apt-get upgrade

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

# 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 \

# 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

# 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

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 ?= @

README

1. Download and install Anaconda from https://store.continuum.io/cshop/anaconda/

2. Place Makefile.config and dp.sh in ~/Downloads type in "./dp.sh"

3. Run "export PYTHONPATH=/home/USERID/Downloads/caffe-master/python:$PYTHONPATH"

4. Run "sudo python /home/USERID/Downloads/caffe-master/scripts/download_model_binary.py /home/USERID/Downloads/caffe-master/models/bvlc_googlenet/"

5. Run "cd deepdream-master/"

6. Run "ipython notebook ./dream.ipynb"

7. Change the following:

"model_path = '../caffe/models/bvlc_googlenet/' # substitute your path here" TO model_path = '/home/USERID/Downloads/caffe-master/models/bvlc_googlenet/' # substitute your path here

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*** NOTE: USERID IN THE README IS YOUR DEBIAN USERID ***