Caffe的編譯（匹配顯示卡計算能力）
環境：GTX1060(notebook) Ubuntu16.04-Desktop Anaconda3.0虛擬環境下的python2.7 CUDA8.0 CUDNN6.0
由於編譯安裝OpenCV 3比較複雜，直接使用sudo apt-get install libopencv-dev 安裝的2.4
根據官方說明http://caffe.berkeleyvision.org/installation.html安裝。附上我的caffe Makefile.config。注意：根據https://developer.nvidia.com/cuda-gpus查詢顯示卡的計算能力為6.1，CUDA_ARCH那裡沒有巴任意一行註釋
## 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 $LIBRARY_DIRS.) # USE_PKG_CONFIG := 1 # N.B. both build and distribute dirs are cleared on `make clean` BUILD_DIR := build DISTRIBUTE_DIR := distribute # Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171 # DEBUG := 1 # The ID of the GPU that 'make runtest' will use to run unit tests. TEST_GPUID := 0 # enable pretty build (comment to see full commands) Q ?= @
參考連結：http://www.voidcn.com/article/p-zfjsbvbo-bee.html
=======================更新（matlab介面問題）=======================
環境Matlab2014a
在剛剛的caffe目錄下make matcaffe編譯matlab介面
我使用的gcc為自帶的5.4版本，會警告使用4.7版本，並報錯：error: no matching function for call to remove_if......
但是換完後反而會出現如protobuf找不到的情況，最後換回了5.4，修改Makefile，在CXXFLAGS += -MMD -MP下一行新增：
CXXFLAGS += -std=c++11
編譯成功
執行make mattest
可能報錯：
MATLAB/R2014a/bin/glnxa64/../../sys/os/glnxa64/: version GLIBCXX_3.4.20
not found
將原libstdc++.so.6備份
複製系統檔案到matlab路徑下 cp /usr/lib/x86_64-linux-gnu/libstdc++.so.6 path/to/matlab/sys/os/glnxa64/libstdc++.so.6.sys
建立連結 ln -s path/to/matlab/sys/os/glnxa64/libstdc++.so.6.sys path/to/matlab/sys/os/glnxa64/libstdc++.so.6
再執行又報錯：
matlab/+caffe/private/caffe_.mexa64: undefined symbol: _ZN2cv8imencodeERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERKNS_11_InputArrayERSt6vectorIhSaIhEERKSB_IiSaIiEE
將path/to/matlab/bin/glnxa64下的libopencv_imgproc.so.2.4，libopencv_highgui.so.2.4，libopencv_core.so.2.4備份
複製系統檔案到matlab路徑下 cp /usr/lib/x86_64-linux-gnu/libopencv_imgproc.so.2.4 path/to/matlab/bin/glnxa64/libopencv_imgproc.so.2.4.sys
建立連結 ln -s path/to/matlab/bin/glnxa64/libopencv_imgproc.so.2.4.sys path/to/matlab/bin/glnxa64/libopencv_imgproc.so.2.4
另外兩個類似
修改連結後需要執行sudo ldconfig
再執行又報錯：
path/to/matlab/bin/glnxa64/libharfbuzz.so.0: undefined symbol: FT_Face_GetCharVariantIndex
先執行export LD_PRELOAD=$LD_PRELOAD:/usr/lib/x86_64-linux-gnu/libfreetype.so.6即可
將matlab下的+caffe拷貝到matlab工程目錄下執行應該是正常的（同樣要在執行./matlab之前使用同一使用者執行上述命令或者加到bashrc中）
參考連結：https://blog.csdn.net/fangbinwei93/article/details/52865461
http://www.cnblogs.com/laiqun/p/6031925.html
http://www.cnblogs.com/Erdos001/p/4593029.html
https://blog.csdn.net/weixin_28949825/article/details/79427512