pycaffe on ubuntu

[punkyoon]

Python 필수

$ sudo apt-get install python3-pip
$ sudo apt-get install python3-dev

[punkyoon]

Install packages

$ sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev libgflags-dev libgoogle-glog-dev liblmdb-dev protobuf-compiler cmake
$ sudo apt-get install --no-install-recommends libboost-all-dev
$ sudo apt-get install libatlas-base-dev

Clone caffe

$ git clone https://github.com/BVLC/caffe
$ cd caffe
$ cp Makefile.config.example Makefile.config

Install python packages (Python 3)

$ cd python
$ sudo pip3 install -r requirements.txt

Modify Makefile.config

../caffe/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

# 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 through *_61 lines for compatibility.
# For CUDA < 8.0, comment the *_60 and *_61 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_52,code=sm_52 \
                -gencode arch=compute_60,code=sm_60 \
                -gencode arch=compute_61,code=sm_61 \
                -gencode arch=compute_61,code=compute_61

# 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

# Uncomment to use Python 3 (default is Python 2)
PYTHON_LIBRARIES := boost_python3 python3.5m
PYTHON_INCLUDE := /usr/include/python3.5m \
                 /usr/local/lib/python3.5/dist-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

# NCCL acceleration switch (uncomment to build with NCCL)
# https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0)
# USE_NCCL := 1

# 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 ?= @

Build caffe

build command

$ make all
$ make test
$ make pycaffe

bashrc setting

$ sudo vim ~/.bashrc

~/.bashrc

...
export PYTHONPATH=$HOME/Downloads/caffe/python:$PYTHONPATH
...

source ~/.bashrc

LAST CHECK

import caffe

import caffe에서 에러가 나는경우..

Error message 1

raise ValueError, "Can't create weekday with n == 0"
                    ^
SyntaxError: invalid syntax

아래의 명령을 입력해서 dateutil을 최신 버전으로 업그레이드 해준다.

$ sudo pip3 uninstall python-dateutil
$ sudo pip3 install python-dateutil

Error message 2

Linking CXX shared library segment.so
/usr/bin/ld: cannot find -lboost_python3

아래의 명령을 입력해서 lboost_python3을 찾을 수 있도록 만들어준다.

$ cd /usr/lib/x86_64-linux-gnu/
$ sudo ln -s libboost_python-py35.so libboost_python3.so

[punkyoon]

Install OpenCV3 with opencv_contrib

전제조건 : numpy가 설치되어 있어야 한다....

opencv 3.3.0

$ git clone https://github.com/opencv/opencv.git
$ cd opencv
$ git checkout 3.3.0
$ mkdir build
$ cd build
$ cmake -D CMAKE_BUILD_TYPE=RELEASE \
      -D CMAKE_INSTALL_PREFIX=/usr/local \
      -D INSTALL_C_EXAMPLES=OFF \
      -D INSTALL_PYTHON_EXAMPLES=OFF \
      -D WITH_TBB=ON \
      -D WITH_V4L=ON \
      -D WITH_OPENGL=ON \
      -D PYTHON_EXECUTABLE=/usr/bin/python \
      -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules \
      -D BUILD_EXAMPLES=ON ..
$ sudo make -j4 all
$ sudo make install
$ sudo sh -c 'echo "/usr/local/lib" >> /etc/ld.so.conf.d/opencv.conf'
$ sudo  ldconfig
$ find /usr/local/lib/ -type f -name "cv2*.so"

++ (참고) python 3.5의 경우...

/usr/local/lib/python3.5/dist-packages/cv2.cpython-35m-x86_64-linux-gnu.so

opencv_contrib 3.3.0

$ git clone https://github.com/opencv/opencv_contrib.git
$ cd opencv_contrib
$ git checkout 3.3.0

LAST CHECK

import cv2
print(cv2.__version__)

[punkyoon]

Ref.

OpenCV

https://www.learnopencv.com/install-opencv3-on-ubuntu/

pycaffe

https://lynlab.co.kr/blog/18/

https://chunml.github.io/ChunML.github.io/project/Installing-Caffe-CPU-Only/

BVLC/caffe#5658

https://askubuntu.com/questions/629654/building-caffe-failed-to-see-hdf5-h

BVLC/caffe#3671

BVLC/caffe#3671

https://github.com/milq/milq/blob/master/scripts/bash/install-opencv.sh

http://webnautes.tistory.com/1030

[punkyoon]

https://yunsangq.github.io/articles/2017-02/caffe