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Install Caffe (w/o GPU) on OS X El Capitan (10.11.6) using Homebrew Python (2.7.12_2)
# Install Caffe (w/o GPU) on OS X El Capitan (10.11.6) using Homebrew Python (2.7.12_2)
#
# Pulled together from several sources:
# - https://gist.github.com/kylemcdonald/0698c7749e483cd43a0e
# - https://gist.github.com/doctorpangloss/f8463bddce2a91b949639522ea1dcbe4
# - http://installing-caffe-the-right-way.wikidot.com/start
# Dependencies
# - XCode 8
# - Also need command line tools for XCode 7.3.1 since CUDA doesn't support XCode 8, which you can get here - https://developer.apple.com/download
# search for Command_Line_Tools_OS_X_10.11_for_Xcode_7.3.1.dmg
# - CUDA toolkit 8.0 (https://developer.nvidia.com/cuda-toolkit)
# - Homebrew python, tested against v2.7.12_2
#
# Install dependiences via brew
# might need to uninstall previous installs
brew tap homebrew/science
brew install -vd snappy leveldb gflags glog szip lmdb
brew install hdf5 opencv
brew upgrade libpng
brew install protobuf boost boost-python
# Setup virtual environment using the brewed python
mkvirtualenv --python /usr/local/bin/python caffe
# Activate virtual environment if not activated already
workon caffe
# Also allow access the global packages
toggleglobalsitepackages
# Clone the caffe repo into a directory
mkdir /somewhere/create/a/directory
cd to/the/directory/created/above
git clone git@github.com:BVLC/caffe.git
# Change into repo
cd caffe/
# Create config
cp Makefile.config.example Makefile.config
# Edit Makefile, particularly these bits
# Make sure to double check all the paths
# See config in this gist
# # CPU-only switch (uncomment to build without GPU support).
# CPU_ONLY := 1
# ...
# # CUDA directory contains bin/ and lib/ directories that we need.
# CUDA_DIR := /usr/local/cuda
# ...
# BLAS := atlas
# BLAS_INCLUDE := /Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.12.sdk/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/Headers
# BLAS_LIB := /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A
# ...
# PYTHON_INCLUDE := /usr/include/python2.7 \
# /usr/local/lib/python2.7/site-packages/numpy/core/include
# ...
# PYTHON_LIB := /usr/local/Cellar/python/2.7.12_2/Frameworks/Python.framework/Versions/2.7/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 += $(shell brew --prefix numpy)/lib
# ...
# # Uncomment to support layers written in Python (will link against Python libs)
# WITH_PYTHON_LAYER := 1
#
# switch to older xcode tools and build & test
sudo xcode-select --switch /Library/Developer/CommandLineTools
make -j4 all
make -j4 all
make -j4 runtest # cross finger
# If passed, install pycaffe
pip install --requirement python/requirements.txt
make -j4 pycaffe
# Test
python -c "import caffe"
# Add to PYTHONPATH
export PYTHONPATH=<caffe-home>/python:$PYTHONPATH
# Distribute [TODO]
# revert back to xcode 8 command line tools
sudo xcode-select -r
## 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 := /Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.12.sdk/System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/Headers
BLAS_LIB := /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A
# 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/local/lib/python2.7/site-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/local/Cellar/python/2.7.12_2/Frameworks/Python.framework/Versions/2.7/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
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
# 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 ?= @
@tanmayGIT
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Hello, all goes well but when I did "make -j4 pycaffe" it gives this error and I could not solve it

ld: library not found for -lboost_python
clang: error: linker command failed with exit code 1 (use -v to see invocation)
make: *** [.build_release/lib/libcaffe.so.1.0.0] Error 1
make: *** Waiting for unfinished jobs....

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