环境:GTX1060(notebook) Ubuntu16.04-Desktop Anaconda3.0虚拟环境下的python2.7 CUDA8.0 CUDNN6.0
由于编译安装OpenCV 3比较复杂,直接使用sudo apt-get install libopencv-dev 安装的2.4
根据官方说明http://caffe.berkeleyvision.org/installation.html安装。附上我的caffe Makefile.config。注意:根据https://developer.nvidia.com/cuda-gpus查询显卡的计算能力为6.1,CUDA_ARCH那里没有把任意一行注释
## 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
# This code is taken from https://github.com/sh1r0/caffe-android-lib
# USE_HDF5 := 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.
# For CUDA >= 9.0, comment the *_20 and *_21 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 := /media/yuf/Data/software/matlab/Matlab/runfile
# 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)/.conda/envs/normal-py27
PYTHON_INCLUDE := /home/yuf/anaconda3/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/lib
PYTHON_LIB := /home/yuf/anaconda3/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
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /home/yuf/anaconda3/pkgs/hdf5-1.10.2-hba1933b_1/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 $LIBRARY_DIRS.)
# USE_PKG_CONFIG := 1
# N.B. both build and distribute dirs are cleared on `make clean`
BUILD_DIR := build
DISTRIBUTE_DIR := distribute
# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171
# DEBUG := 1
# The ID of the GPU that 'make runtest' will use to run unit tests.
TEST_GPUID := 0
# enable pretty build (comment to see full commands)
Q ?= @
参考链接:http://www.voidcn.com/article/p-zfjsbvbo-bee.html
=======================更新(matlab接口问题)=======================
环境Matlab2014a
在刚刚的caffe目录下make matcaffe编译matlab接口
我使用的gcc为自带的5.4版本,会警告使用4.7版本,并报错:error: no matching function for call to remove_if......
但是换完后反而会出现如protobuf找不到的情况,最后换回了5.4,修改Makefile,在CXXFLAGS += -MMD -MP下一行添加:
CXXFLAGS += -std=c++11
编译成功
运行make mattest
可能报错:
MATLAB/R2014a/bin/glnxa64/../../sys/os/glnxa64/: version GLIBCXX_3.4.20
not found
将原libstdc++.so.6备份
复制系统文件到matlab路径下 cp /usr/lib/x86_64-linux-gnu/libstdc++.so.6 path/to/matlab/sys/os/glnxa64/libstdc++.so.6.sys
建立链接 ln -s path/to/matlab/sys/os/glnxa64/libstdc++.so.6.sys path/to/matlab/sys/os/glnxa64/libstdc++.so.6
再运行又报错:
matlab/+caffe/private/caffe_.mexa64: undefined symbol: _ZN2cv8imencodeERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERKNS_11_InputArrayERSt6vectorIhSaIhEERKSB_IiSaIiEE
将path/to/matlab/bin/glnxa64下的libopencv_imgproc.so.2.4,libopencv_highgui.so.2.4,libopencv_core.so.2.4备份
复制系统文件到matlab路径下 cp /usr/lib/x86_64-linux-gnu/libopencv_imgproc.so.2.4 path/to/matlab/bin/glnxa64/libopencv_imgproc.so.2.4.sys
建立链接 ln -s path/to/matlab/bin/glnxa64/libopencv_imgproc.so.2.4.sys path/to/matlab/bin/glnxa64/libopencv_imgproc.so.2.4
另外两个类似
修改链接后需要执行sudo ldconfig
再运行又报错:
path/to/matlab/bin/glnxa64/libharfbuzz.so.0: undefined symbol: FT_Face_GetCharVariantIndex
先运行export LD_PRELOAD=$LD_PRELOAD:/usr/lib/x86_64-linux-gnu/libfreetype.so.6即可
将matlab下的+caffe拷贝到matlab工程目录下运行应该是正常的(同样要在运行./matlab之前使用同一用户执行上述命令或者加到bashrc中)
补充:caffe : /wrap_python.hpp:50:23: fatal error: pyconfig.h: No such file or dir
export CPLUS_INCLUDE_PATH=/你的anconda路径/include/python2.7
使用python3时,将Makefile中PYTHON_LIBRARIES改为/usr/lib/x86_64-linux-gnu/路径下boost_python文件的版本
如:PYTHON_LIBRARIES ?= boost_python-py35 python3.6m
参考链接:https://blog.youkuaiyun.com/fangbinwei93/article/details/52865461
http://www.cnblogs.com/laiqun/p/6031925.html
http://www.cnblogs.com/Erdos001/p/4593029.html
https://blog.youkuaiyun.com/weixin_28949825/article/details/79427512
https://blog.youkuaiyun.com/weixin_37251044/article/details/79158823
https://blog.youkuaiyun.com/sinat_35406909/article/details/84198140
更:
ImportError: libcudart.so.8.0: cannot open shared object file: No such file or directory
确认已经在路径下,如/usr/local/cuda/lib64
参考https://blog.youkuaiyun.com/u011636567/article/details/77162217
sudo ldconfig /usr/local/cuda/lib64
更:
可以使用这样的命令
pip install torch==0.4.1 -f https://download.pytorch.org/whl/cu80/stable
更:
未定义的引用“TIFFReadRGBAStrip@LIBTIFF_4.0”