Windows10下Caffe+CUDA+cuDNN+matcaffe+pycaffe安裝

GitHub Windows版Caffe分支 Windows Caffe

安裝環(huán)境

cuDNN安裝

  1. 安裝CUDA
  2. 下載cuDNN并解壓壓縮包
  3. 將解壓后的文件夾cuda下的文件分別復(fù)制到CUDA安裝目錄
cuDNN目錄 CUDA安裝目錄
cuda\bin C:\Program Files\NVIDIA GPU Computing Tookit\CUDA\v8.0\bin
cuda\include C:\Program Files\NVIDIA GPU Computing Tookit\CUDA\v8.0\include
cuda\lib\x64 C:\Program Files\NVIDIA GPU Computing Tookit\CUDA\v8.0\lib\x64

安裝Caffe

  1. D盤新建目錄CaffeBuild
  2. 打開(kāi)cmd(命令提示符)切換到CaffeBuild目錄
> d:
> cd CaffeBuild
  1. 下載Caffe
D:\CaffeBuild> git clone https://github.com/BVLC/caffe.git
D:\CaffeBuild> cd caffe
D:\CaffeBuild> git checkout windows
  1. 修改配置
    D:\CaffeBuild\caffe\scripts下修改build_win.cmd文件,使用Sublime打開(kāi)
    第8,9,14行
:: Default values
if DEFINED APPVEYOR (
    echo Setting Appveyor defaults
    if NOT DEFINED MSVC_VERSION set MSVC_VERSION=14
    if NOT DEFINED WITH_NINJA set WITH_NINJA=0
    if NOT DEFINED CPU_ONLY set CPU_ONLY=0
    if NOT DEFINED CUDA_ARCH_NAME set CUDA_ARCH_NAME=Auto
    if NOT DEFINED CMAKE_CONFIG set CMAKE_CONFIG=Release
    if NOT DEFINED USE_NCCL set USE_NCCL=0
    if NOT DEFINED CMAKE_BUILD_SHARED_LIBS set CMAKE_BUILD_SHARED_LIBS=0
    if NOT DEFINED PYTHON_VERSION set PYTHON_VERSION=3
    if NOT DEFINED BUILD_PYTHON set BUILD_PYTHON=1
    if NOT DEFINED BUILD_PYTHON_LAYER set BUILD_PYTHON_LAYER=1
    if NOT DEFINED BUILD_MATLAB set BUILD_MATLAB=1
    if NOT DEFINED PYTHON_EXE set PYTHON_EXE=python
    if NOT DEFINED RUN_TESTS set RUN_TESTS=1
    if NOT DEFINED RUN_LINT set RUN_LINT=1
    if NOT DEFINED RUN_INSTALL set RUN_INSTALL=1

第29行

:: Set python 3.5 with conda as the default python
    if !PYTHON_VERSION! EQU 3 (
        set CONDA_ROOT=D:\Anaconda3
    )

第74行

:: Change to 1 to use Ninja generator (builds much faster)
    if NOT DEFINED WITH_NINJA set WITH_NINJA=0

第87行

:: Change to 3 if using python 3.5 (only 2.7 and 3.5 are supported)
    if NOT DEFINED PYTHON_VERSION set PYTHON_VERSION=3

第91行

:: Change these options for your needs.
    if NOT DEFINED BUILD_PYTHON set BUILD_PYTHON=1
    if NOT DEFINED BUILD_PYTHON_LAYER set BUILD_PYTHON_LAYER=1
    if NOT DEFINED BUILD_MATLAB set BUILD_MATLAB=1

第167行添加

:: Configure using cmake and using the caffe-builder dependencies
:: Add -DCUDNN_ROOT=C:/Projects/caffe/cudnn-8.0-windows10-x64-v5.1/cuda ^
:: below to use cuDNN
cmake -G"!CMAKE_GENERATOR!" ^
      -DBLAS=Open ^
      -DCMAKE_BUILD_TYPE:STRING=%CMAKE_CONFIG% ^
      -DBUILD_SHARED_LIBS:BOOL=%CMAKE_BUILD_SHARED_LIBS% ^
      -DBUILD_python:BOOL=%BUILD_PYTHON% ^
      -DBUILD_python_layer:BOOL=%BUILD_PYTHON_LAYER% ^
      -DBUILD_matlab:BOOL=%BUILD_MATLAB% ^
      -DCUDNN_ROOT=C:\Program Files\NVIDIA GPU Computiong Toolkit\CUDA\v8.0 ^
      -DCPU_ONLY:BOOL=%CPU_ONLY% ^
      -DCOPY_PREREQUISITES:BOOL=1 ^
      -DINSTALL_PREREQUISITES:BOOL=1 ^
      -DUSE_NCCL:BOOL=!USE_NCCL! ^
      -DCUDA_ARCH_NAME:STRING=%CUDA_ARCH_NAME% ^
      "%~dp0\.."
  1. 執(zhí)行腳本
D:\CaffeBuild\caffe> scripts\build_win.cmd

耐心等待,希望別報(bào)錯(cuò):)

下載依賴包可能因?yàn)榫W(wǎng)絡(luò)原因會(huì)失敗
網(wǎng)盤下載并放到下面這個(gè)目錄下,其中users后面的路徑改成你電腦的用戶名
C:\Users\shuai\.caffe\dependencies\download
這個(gè)依賴包只適合這個(gè)環(huán)境,其他環(huán)境需要搞定網(wǎng)絡(luò)后重新運(yùn)行腳本


#報(bào)錯(cuò)
'"C:\Program Files (x86)\Microsoft Visual Studio 14.0\Common7\Tools\..\..\VC\vcvarsall.bat"' 不是內(nèi)部或外部命令,也不是 可運(yùn)行的程序
或批處理文件。
-- The C compiler identification is unknown
-- The CXX compiler identification is unknown
CMake Error at CMakeLists.txt:18 (project):
  No CMAKE_C_COMPILER could be found.

 CMake Error at CMakeLists.txt:18 (project):
  No CMAKE_CXX_COMPILER could be found.

-- Configuring incomplete, errors occurred!
See also "E:/CaffeBuild/caffe/build/CMakeFiles/CMakeOutput.log".
See also "E:/CaffeBuild/caffe/build/CMakeFiles/CMakeError.log".
ERROR: Configure failed

解決方法:打開(kāi)VS2015安裝程序,選擇修改,勾選編程語(yǔ)言下的Visual C++

勾選Visual C++

裝了兩次都出現(xiàn)下面這個(gè)錯(cuò)誤

#報(bào)錯(cuò)
CMake Error at cmake/Utils.cmake:69 (string):   
string sub-command STRIP requires two arguments.

解決方法:修改caffe\cmake下Utils.cmake,第69行加引號(hào)

# Function merging lists of compiler flags to single string.
# Usage:
#   caffe_merge_flag_lists(out_variable <list1> [<list2>] [<list3>] ...)
function(caffe_merge_flag_lists out_var)
  set(__result "")
  foreach(__list ${ARGN})
    foreach(__flag ${${__list}})
      string(STRIP ${__flag} __flag)
      set(__result "${__result} ${__flag}")
    endforeach()
  endforeach()
  string(STRIP "${__result}" __result)
  set(${out_var} ${__result} PARENT_SCOPE)
endfunction()

如果安裝成功則在caffe\build\tools\Release下有可執(zhí)行文件

Python接口

打開(kāi)Anaconda下的Anaconda Prompt

conda config --add channels conda-forge
conda config --add channels willyd
conda install --yes cmake ninja numpy scipy protobuf==3.1.0 six scikit-image pyyaml pydotplus graphviz

E:\CaffeBuild\caffe\python下caffe文件夾復(fù)制到E:\Anaconda3\Lib\site-packages

在cmd中輸入python,執(zhí)行import caffe,若沒(méi)有報(bào)錯(cuò),則Python接口成功配置

MATLAB接口

E:\caffeBuild\caffe\matlab目錄下MATLAB中運(yùn)行>> caffe.run_tests()
E:\CaffeBuild\caffe\matlab\+caffe\private\Release下的caffe_mexw64復(fù)制到E:\CaffeBuild\caffe\matlab\+caffe\private
修改matlab+caffe\Net.m第72行

function delete (self)
    if self.isvalid
        caffe_('delete_net', self.hNet_self);
    end
end

下載模型,cmd在caffe根目錄下執(zhí)行

python scripts\download_model_binary.py models\bvlc_reference_caffenet

打開(kāi)MATLAB,打開(kāi)E:\CaffeBuild\caffe\matlab\demo\classification_demo.m
命令行窗口執(zhí)行

im = imread('E:\CaffeBuild\caffe\examples\images\cat.jpg');

執(zhí)行classification_demo.m
在MATLAB命令窗口執(zhí)行help caffe,如果不報(bào)錯(cuò),則MATLAB接口配置成功

最后編輯于
?著作權(quán)歸作者所有,轉(zhuǎn)載或內(nèi)容合作請(qǐng)聯(lián)系作者
【社區(qū)內(nèi)容提示】社區(qū)部分內(nèi)容疑似由AI輔助生成,瀏覽時(shí)請(qǐng)結(jié)合常識(shí)與多方信息審慎甄別。
平臺(tái)聲明:文章內(nèi)容(如有圖片或視頻亦包括在內(nèi))由作者上傳并發(fā)布,文章內(nèi)容僅代表作者本人觀點(diǎn),簡(jiǎn)書(shū)系信息發(fā)布平臺(tái),僅提供信息存儲(chǔ)服務(wù)。

相關(guān)閱讀更多精彩內(nèi)容

友情鏈接更多精彩內(nèi)容