Я использую GTX 1080 с поддержкой UBUNUTU 16.04 Xenial для глубокого обучения. Тем не менее, я столкнулся с небольшой проблемой при сборе кофе из источника BLVC или NVIDIA. После установки всех зависимостей и связывания глобальных переменных Im все еще не хватает чего-то для компиляции caffe. Я создал OpenCV 3.1.0 и OpenBLAS и т. Д. Теперь клонирование с https://github.com/BVLC/caffe и ввода
cd caffe
mkdir build
cd build
cmake ..
дает мне следующую ошибку -
-- The C compiler identification is GNU 5.4.0
-- The CXX compiler identification is GNU 5.4.0
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Boost version: 1.58.0
-- Found the following Boost libraries:
-- system
-- thread
-- filesystem
-- Looking for include file pthread.h
-- Looking for include file pthread.h - found
-- Looking for pthread_create
-- Looking for pthread_create - not found
-- Looking for pthread_create in pthreads
-- Looking for pthread_create in pthreads - not found
-- Looking for pthread_create in pthread
-- Looking for pthread_create in pthread - found
-- Found Threads: TRUE
-- Found GFlags: /usr/include
-- Found gflags (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libgflags.so)
-- Found Glog: /usr/include
-- Found glog (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libglog.so)
-- Found PROTOBUF: /usr/lib/x86_64-linux-gnu/libprotobuf.so
-- Found PROTOBUF Compiler: /usr/bin/protoc
CMake Error at /usr/local/share/cmake-3.2/Modules/FindPackageHandleStandardArgs.cmake:138 (message):
Could NOT find HDF5 (missing: HDF5_INCLUDE_DIRS)
Call Stack (most recent call first):
/usr/local/share/cmake-3.2/Modules/FindPackageHandleStandardArgs.cmake:374 (_FPHSA_FAILURE_MESSAGE)
/usr/local/share/cmake-3.2/Modules/FindHDF5.cmake:360 (find_package_handle_standard_args)
cmake/Dependencies.cmake:27 (find_package)
CMakeLists.txt:43 (include)
-- Configuring incomplete, errors occurred!
See also "/home/xhuv/testcaffe/caffe/build/CMakeFiles/CMakeOutput.log".
See also "/home/xhuv/testcaffe/caffe/build/CMakeFiles/CMakeError.log".
Я использую Python 3.5.2. :: Anaconda 4.2.0 (64-разрядная версия), также установлена ??версия Python версии 2.7. Я отредактировал в Makefile.configсоответствии со следующим
## 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 := 3
# 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
# 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 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_50,code=compute_50
# BLAS choice:
# atlas for ATLAS (default)
# mkl for MKL
# open for OpenBlas
BLAS := open
# Custom (MKL/ATLAS/OpenBLAS) include and lib directories.
# Leave commented to accept the defaults for your choice of BLAS
# (which should work)!
BLAS_INCLUDE := /usr/local/include
BLAS_LIB := /usr/local/lib
# 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)/anaconda2
PYTHON_INCLUDE := $(ANACONDA_HOME)/include
$(ANACONDA_HOME)/include/python2.7
$(ANACONDA_HOME)/lib/python2.7/site-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
LIBRARY_DIRS += /usr/lib/x86_64-linux-gnu/
LIBRARY_DIRS += $(ANACONDA_HOME)/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
# 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
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 ?= @
# shared object suffix name to differentiate branches
LIBRARY_NAME_SUFFIX := -nv
Какая может быть возможная ошибка? Пожалуйста помоги!!
python,ubuntu,cmake,caffe,