我的環境cuda10、python2.7、opencv3.4.6
我主要步驟是參考https://blog.csdn.net/sinat_23619409/article/details/86466700，包括安裝依賴項、配置config文件、編譯所需命令。
這次編譯的caffe源是ssd版本的源，是 https://github.com/weiliu89/caffe/tree/ssd
這裏把我的Makefile.config貼出來：
## 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 := /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/lzc/anaconda3
#####PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
##### $(ANACONDA_HOME)/include/python3.6m \
##### $(ANACONDA_HOME)/lib/python3.6/site-packages/numpy/core/include
# Uncomment to use Python 3 (default is Python 2)
#####PYTHON_LIBRARIES := boost_python3 python3.6m
# 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
LINKFLAGS := -Wl,-rpath,/home/lzc/anaconda3/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 /usr/lib/x86_64-linux-gnu /usr/lib/x86_64-linux-gnu/hdf5/serial
# 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 ?= @
我編譯的時候報了N個錯誤，這裏把經歷的一些錯誤貼出來：
0、這個問題肯定會有，一定及時改，不然需要全部重新編譯！！！import caffe時報錯爲undefined symbol: _ZN5boost6python6detail11init_moduleER11PyModuleDefPFvvE：https://github.com/BVLC/caffe/issues/6547
1、Caffe編譯過程中出現C++11問題：https://blog.csdn.net/m_buddy/article/details/88085425
2、Caffe HDF5 header version與HDF5 library不匹配：https://blog.csdn.net/a137376864/article/details/78703879?depth_1.utm_source=distribute.pc_relevant.none-task&utm_source=distribute.pc_relevant.none-task
3、libcudart.so.10.0: cannot open shared object file: No such file or directory 的解決辦法：https://blog.csdn.net/wendygelin/article/details/88528055
和
https://blog.csdn.net/qq_38451119/article/details/81007904
4、caffe編譯報錯lib/libpng16.so.16: undefined reference to `inflateValidate@ZLIB_1.2.9'：https://blog.csdn.net/Dillon2015/article/details/79857892
和
https://www.cnblogs.com/zxj9487/p/11393546.html
5、pyconfig.h not such file or directory：https://blog.csdn.net/sdlypyzq/article/details/89967009?depth_1.utm_source=distribute.pc_relevant.none-task&utm_source=distribute.pc_relevant.none-task
6、編譯cmake時The dependency target "pycaffe" of target "pytest" does not exist，這個暫時沒有解決。。。
7、ImportError: dynamic module does not define module export function (PyInit__caffe)，此錯誤可能是python版本不對或者環境變量沒有設置好：https://blog.csdn.net/qq_31347869/article/details/94408733
和
https://blog.csdn.net/ShuqiaoS/article/details/83382191
8、Message type "caffe.LayerParameter" has no field named "permute_param"： https://www.cnblogs.com/huhuai/p/9459642.html