다음과 같은 카페를 설치하려고합니다.이 가이드하지만 모두 만들면 오류가 발생합니다.
[ 89%] Linking CXX executable convert_imageset
/usr/bin/ld: CMakeFiles/convert_imageset.dir/convert_imageset.cpp.o: undefined reference to symbol '_ZN6google15SetUsageMessageERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE'
//usr/lib/x86_64-linux-gnu/libgflags.so.2: error adding symbols: DSO missing from command line
collect2: error: ld returned 1 exit status
tools/CMakeFiles/convert_imageset.dir/build.make:133: recipe for target 'tools/convert_imageset' failed
make[2]: *** [tools/convert_imageset] Error 1
CMakeFiles/Makefile2:657: recipe for target 'tools/CMakeFiles/convert_imageset.dir/all' failed
make[1]: *** [tools/CMakeFiles/convert_imageset.dir/all] Error 2
Makefile:127: recipe for target 'all' failed
make: *** [all] Error 2
cmake를 사용할 때 또는
CXX/LD -o .build_release/tools/compute_image_mean.bin
/usr/bin/ld: .build_release/tools/compute_image_mean.o: undefined reference to symbol '_ZN6google15SetUsageMessageERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE'
//usr/lib/x86_64-linux-gnu/libgflags.so.2: error adding symbols: DSO missing from command line
collect2: error: ld returned 1 exit status
Makefile:627: recipe for target '.build_release/tools/compute_image_mean.bin' failed
make: *** [.build_release/tools/compute_image_mean.bin] Error 1
make를 사용할 때.
현재 다음과 같은 CmakeList.txt가 있습니다.
cmake_minimum_required(VERSION 2.8.7)
if(POLICY CMP0046)
cmake_policy(SET CMP0046 NEW)
endif()
if(POLICY CMP0054)
cmake_policy(SET CMP0054 NEW)
endif()
# ---[ Caffe project
project(Caffe C CXX)
# ---[ Caffe version
set(CAFFE_TARGET_VERSION "1.0.0" CACHE STRING "Caffe logical version")
set(CAFFE_TARGET_SOVERSION "1.0.0" CACHE STRING "Caffe soname version")
add_definitions(-DCAFFE_VERSION=${CAFFE_TARGET_VERSION})
list(APPEND LIBRARIES "/usr/lib/x86_64-linux-gnu/libglog.so.0")
# ---[ Using cmake scripts and modules
list(APPEND CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake/Modules)
include(ExternalProject)
include(GNUInstallDirs)
include(cmake/Utils.cmake)
include(cmake/Targets.cmake)
include(cmake/Misc.cmake)
include(cmake/Summary.cmake)
include(cmake/ConfigGen.cmake)
# ---[ Options
caffe_option(CPU_ONLY "Build Caffe without CUDA support" OFF) # TODO: rename to USE_CUDA
caffe_option(USE_CUDNN "Build Caffe with cuDNN library support" ON IF NOT CPU_ONLY)
caffe_option(USE_NCCL "Build Caffe with NCCL library support" OFF)
caffe_option(BUILD_SHARED_LIBS "Build shared libraries" ON)
caffe_option(BUILD_python "Build Python wrapper" ON)
set(python_version "2" CACHE STRING "Specify which Python version to use")
caffe_option(BUILD_matlab "Build Matlab wrapper" OFF IF UNIX OR APPLE)
caffe_option(BUILD_docs "Build documentation" ON IF UNIX OR APPLE)
caffe_option(BUILD_python_layer "Build the Caffe Python layer" ON)
caffe_option(USE_OPENCV "Build with OpenCV support" ON)
caffe_option(USE_LEVELDB "Build with levelDB" ON)
caffe_option(USE_LMDB "Build with lmdb" ON)
caffe_option(ALLOW_LMDB_NOLOCK "Allow MDB_NOLOCK when reading LMDB files (only if necessary)" OFF)
caffe_option(USE_OPENMP "Link with OpenMP (when your BLAS wants OpenMP and you get linker errors)" OFF)
# ---[ Dependencies
include(cmake/Dependencies.cmake)
# ---[ Flags
if(UNIX OR APPLE)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fPIC -Wall")
endif()
caffe_set_caffe_link()
if(USE_libstdcpp)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -stdlib=libstdc++")
message("-- Warning: forcing libstdc++ (controlled by USE_libstdcpp option in cmake)")
endif()
# ---[ Warnings
caffe_warnings_disable(CMAKE_CXX_FLAGS -Wno-sign-compare -Wno-uninitialized)
# ---[ Config generation
configure_file(cmake/Templates/caffe_config.h.in "${PROJECT_BINARY_DIR}/caffe_config.h")
# ---[ Includes
set(Caffe_INCLUDE_DIR ${PROJECT_SOURCE_DIR}/include)
set(Caffe_SRC_DIR ${PROJECT_SOURCE_DIR}/src)
include_directories(${PROJECT_BINARY_DIR})
# ---[ Includes & defines for CUDA
# cuda_compile() does not have per-call dependencies or include pathes
# (cuda_compile() has per-call flags, but we set them here too for clarity)
#
# list(REMOVE_ITEM ...) invocations remove PRIVATE and PUBLIC keywords from collected definitions and include pathes
if(HAVE_CUDA)
# pass include pathes to cuda_include_directories()
set(Caffe_ALL_INCLUDE_DIRS ${Caffe_INCLUDE_DIRS})
list(REMOVE_ITEM Caffe_ALL_INCLUDE_DIRS PRIVATE PUBLIC)
cuda_include_directories(${Caffe_INCLUDE_DIR} ${Caffe_SRC_DIR} ${Caffe_ALL_INCLUDE_DIRS})
# add definitions to nvcc flags directly
set(Caffe_ALL_DEFINITIONS ${Caffe_DEFINITIONS})
list(REMOVE_ITEM Caffe_ALL_DEFINITIONS PRIVATE PUBLIC)
list(APPEND CUDA_NVCC_FLAGS ${Caffe_ALL_DEFINITIONS})
endif()
# ---[ Subdirectories
add_subdirectory(src/gtest)
add_subdirectory(src/caffe)
add_subdirectory(tools)
add_subdirectory(examples)
add_subdirectory(python)
add_subdirectory(matlab)
add_subdirectory(docs)
# ---[ Linter target
add_custom_target(lint COMMAND ${CMAKE_COMMAND} -P ${PROJECT_SOURCE_DIR}/cmake/lint.cmake)
# ---[ pytest target
if(BUILD_python)
add_custom_target(pytest COMMAND python${python_version} -m unittest discover -s caffe/test WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}/python )
add_dependencies(pytest pycaffe)
endif()
# ---[ uninstall target
configure_file(
${CMAKE_CURRENT_SOURCE_DIR}/cmake/Uninstall.cmake.in
${CMAKE_CURRENT_BINARY_DIR}/cmake/Uninstall.cmake
IMMEDIATE @ONLY)
add_custom_target(uninstall
COMMAND ${CMAKE_COMMAND} -P
${CMAKE_CURRENT_BINARY_DIR}/cmake/Uninstall.cmake)
# ---[ Configuration summary
caffe_print_configuration_summary()
# ---[ Export configs generation
caffe_generate_export_configs()
다음 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_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/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
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/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 ?= @
편집: 처음에는 cmake ..도 오류가 발생했다는 것을 알지 못했지만 여기에는 다음과 같습니다. /usr/local/share/OpenCV/OpenCVConfig.cmake:108(메시지): OpenCV 정적 라이브러리가 CUDA로 컴파일되었습니다. 9.0 지원. 동일한 버전을 사용하거나 CUDA 8.0 호출 스택으로 OpenCV를 다시 빌드하십시오(가장 최근 호출부터): cmake/Dependency.cmake:97 (find_package) CMakeLists.txt:46 (include)
이는 opencv에 문제가 있음을 시사합니다. 이미 opencv를 다시 빌드하려고 시도했지만 아무것도 수행하지 않았습니다. opencv가 cuda 8을 사용하도록 강제하는 방법을 아는 사람이 있습니까?
이것은 우분투 16.04에만 해당됩니다. 이것이 컴파일되도록 수정하는 방법을 아는 사람이 있나요? 아니면 추가할 수 있는 추가 정보가 있나요?