安裝筆記， caffe 、 opencv等

時間 2019-11-24

標籤安裝筆記 caffe opencv 简体版

原文原文鏈接

一、 php

　　1.1 opencv static linuxhtml

mkdir build & cd buildpython

　　cmake .. -LH 這句話用來查看編譯選項若是不知道編譯啥能夠用這個查看一下~linux

cmake \
-D CMAKE_INSTALL_PREFIX=/work/lib/opencv/ubuntu14/2.4.13 \
-D BUILD_SHARED_LIBS=OFF \
-D WITH_CUDA=OFF \
-D WITH_OPENCL=OFF \
-D BUILD_PERF_TESTS=OFF \
-D BUILD_TESTS=OFF \
-D BUILD_opencv_world=ON \
-D WITH_FFMPEG:BOOL=OFF \
-D BUILD_opencv_videoio=OFF \
-D BUILD_JPEG=ON \
-D BUILD_PNG=ON \
..git

注：若是要加入contrib ，則須要加入以下選項：github

-D OPENCV_EXTRA_MODULES_PATH="../../contrib/modules" 即web

若是要加入libpng libjpegbootstrap

-D BUILD_JPEG=ON \
-D BUILD_PNG=ON \

若須要編譯dnn 則須要cmake版本3.5.1 以上，這裏是cmake 3.6.0 下載連接ubuntu

https://download.csdn.net/download/u011258240/11122952app


可能出現的錯誤:
　　1.In-source builds are not allowed   ：  刪掉CMakeCache.txt  而後從新編譯
　　2. ipp 下載失敗    打開\build\CMakeDownloadLog.txt   就能夠看到下載連接了   下載下來便可

　　1.2. opencv + win10
　　取消勾選 JAVA python cuda test ， 添加 install 安裝目錄 ，  configure  ， generate

3.4的依賴

Libs: -L${exec_prefix}/lib/x86_64-linux-gnu

-lopencv_dnn -lopencv_ml -lopencv_objdetect -lopencv_shape -lopencv_stitching -lopencv_superres -lopencv_videostab -lopencv_calib3d -lopencv_features2d -lopencv_highgui -lopencv_videoio -lopencv_imgcodecs -lopencv_video -lopencv_photo -lopencv_imgproc -lopencv_flann -lopencv_core

-L${exec_prefix}/share/OpenCV/3rdparty/lib/x86_64-linux-gnu

-littnotify -llibprotobuf -lzlib -llibjpeg -llibwebp -llibpng -llibtiff -llibjasper -lIlmImf -lippiw -lippicv -ldl -lm -lpthread -lrt -lz



2. caffe

編譯機器

1. 安裝依賴

sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev libgflags-dev libgoogle-glog-dev liblmdb-dev protobuf-compiler libatlas-base-dev cmake python-pip

2. 安裝 numpy

pip install numpy

3 安裝caffe動態庫

　　下載caffe源碼

　　　　wget https://github.com/BVLC/caffe/archive/1.0.tar.gz

　　cd caffe-1.0.0

　　cp Makefile.config.example Makefile.config

　　更改Makefile.config

第八行 CPU_ONLY := 1 打開，表示只使用CPU，若是你用GPU 這一步就不用作了。

修改 cmake/Dependencies.cmake

最頂部加入：

set(CMAKE_PREFIX_PATH ${CMAKE_PREFIX_PATH} "/work/lib/opencv/3.3")
find_package(OpenCV 3.3.0 REQUIRED)

mkdir build

cd build

cmake ../ -DBUILD_SHARED_LIBS=1 -DCMAKE_INSTALL_PREFIX=install

　　#### cmake . -DBUILD_SHARED_LIBS=1 -DCMAKE_INSTALL_PREFIX=install

【可選項】修改caffe 源碼，使其不要在控制檯打印一大堆東西, 將src/caffe/common.cpp GlobalInit 源碼替換爲以下

void GlobalInit(int* pargc, char*** pargv) {
{
　　// Google flags.
　　::gflags::ParseCommandLineFlags(pargc, pargv, true);
　　::google::InitGoogleLogging(*(pargv)[0]);
　　google::SetLogDestination(google::WARNING,"");
}

　　make

　　make install

cd MTCNN_Caffe

cmake .

make

運行機器：

apt-get install libgoogle-glog-dev libopencv-dev

3. CUDA

3.1cuda sdk

　　　https://developer.nvidia.com/cuda-toolkit-archive

1. `sudo dpkg -i cuda-repo-ubuntu1404-10-0-local-10.0.130-410.48_1.0-1_amd64.deb`
2. `sudo apt-key add /var/cuda-repo-<version>/7fa2af80.pub`
3. `sudo apt-get update`
4. `sudo apt-get install cuda`

3.2 驅動下載

https://www.nvidia.cn/Download/Find.aspx?lang=cn

nvidia-smi #查看當前驅動
ubuntu-drivers devices #查看系統建議安裝的驅動
apt-get isntall nvidia-430 #安裝驅動

3.3cuDNN 運行時庫和開發庫

https://developer.nvidia.com/rdp/cudnn-archive

cuda 和cudnn 的刪除 https://blog.csdn.net/wanzhen4330/article/details/81704474

3.4 不一樣版本cuda切換

ln -sf cuda-8.0/ cuda

3.5 不一樣cudnn版本切換 :

ln -sf /usr/lib/x86_64-linux-gnu/libcudnn.so.7 /etc/alternatives/libcudnn_so

ln -sf /usr/include/x86_64-linux-gnu/cudnn_v7.h /etc/alternatives/libcudnn

4. ubuntu14安裝tensorflow

#####cd tensorflow-1.13.1

pip install tensorflow

pip install tensorflow-gpu

5 RetinaNet 環境搭建

git clone https://github.com/fizyr/keras-retinanet.git

cd keras-retinanet

pip install numpy --user

pip install . --user

pip install --upgrade Pillow

訓練：

####keras_retinanet/bin/train.py pascal /root/darknet/VOCdevkit/VOC2007/

retinanet-train pascal /path/to/VOCdevkit/VOC2007

可能出現的錯誤：

1. Getting error: unknown file type '.pyx' when installing from source #13

解決辦法：

sudo apt-get remove python-setuptools
wget https://bootstrap.pypa.io/get-pip.py
sudo -H pip install -U pip setuptools

2. ImportError: libcublas.so.10.0: cannot open shared object file: No such file or directory

解決辦法：安裝CUDA 10.0

6. 搭建Tensorflow1.13 C++ 開發環境

　　6.1 linux

　　https://blog.csdn.net/gubenpeiyuan/article/details/80855644

版本須要按照如下來搭配，否則會出問題

https://www.tensorflow.org/install/source

192.168.1.208 tensorflow = 1.13.1

下載Tensorflow1.3.0 下載 bazel-0.4.5 cudnn6

tar -zxvf v1.3.0.tar.gz

./bazel-0.4.5-installer-linux-x86_64.sh

cd tensorflow*

bazel build --config=opt --config=cuda //tensorflow:libtensorflow_cc.so

可能出現的錯誤和解決方案：

bug: 'protobuf.bzl': no such package ... ...

fix: sed -i '\@https://github.com/google/protobuf/archive/0b059a3d8a8f8aa40dde7bea55edca4ec5dfea66.tar.gz@d' tensorflow/workspace.bzl

see it : https://github.com/tensorflow/tensorflow/issues/12979

　　6.2 Windows 安裝：（放棄了）

　　　　1) download swig exe : http://www.swig.org/

7. bazel 編譯 transform_graph (下載最新版的bazel 和 tensorflow)

　　bazel build tensorflow/tools/graph_transforms:transform_graph

8 交叉編譯opencv

https://docs.opencv.org/2.4/doc/tutorials/introduction/crosscompilation/arm_crosscompile_with_cmake.html

http://bbs.ebaina.com/forum.php?mod=viewthread&tid=38496&highlight=opencv

vi cmake/OpenCVCompilerOptions.cmake

最末尾添加:

if(ENABLE_NEON)
    add_extra_compiler_option("-mcpu=cortex-a7 -mfpu=neon")
endif()

vi CMakeList.txt

將NEON那行改成:

OCV_OPTION(ENABLE_NEON "Enable NEON instructions" ON )

cmake \
-D CMAKE_INSTALL_PREFIX=/work/lib/opencv/arm-hisi/2.4.13 \
-D BUILD_SHARED_LIBS=ON \
-D WITH_CUDA=OFF \
-D WITH_OPENCL=OFF \
-D BUILD_PERF_TESTS=OFF \
-D BUILD_TESTS=OFF \
-D BUILD_opencv_world=OFF \
-D WITH_FFMPEG:BOOL=OFF \
-D BUILD_opencv_videoio=OFF \
-D BUILD_JPEG=ON \
-D BUILD_PNG=ON \
-DCMAKE_TOOLCHAIN_FILE=../platforms/linux/arm-gnueabi.toolchain.cmake \
-DCMAKE_CXX_COMPILER=/opt/hisi-linux/x86-arm/arm-hisiv400-linux/bin/arm-hisiv400-linux-gnueabi-g++ \
-DCMAKE_C_COMPILER=/opt/hisi-linux/x86-arm/arm-hisiv400-linux/bin/arm-hisiv400-linux-gnueabi-gcc \
-DCMAKE_AR=/opt/hisi-linux/x86-arm/arm-hisiv400-linux/bin/arm-hisiv400-linux-gnueabi-ar \
-DCMAKE_LINKER=/opt/hisi-linux/x86-arm/arm-hisiv400-linux/bin/arm-hisiv400-linux-gnueabi-ld \
-DCMAKE_NM=/opt/hisi-linux/x86-arm/arm-hisiv400-linux/bin/arm-hisiv400-linux-gnueabi-nm \
-DCMAKE_OBJCOPY=/opt/hisi-linux/x86-arm/arm-hisiv400-linux/bin/arm-hisiv400-linux-gnueabi-objcopy \
-DCMAKE_OBJDUMP=/opt/hisi-linux/x86-arm/arm-hisiv400-linux/bin/arm-hisiv400-linux-gnueabi-objdump \
-DCMAKE_STRIP=/opt/hisi-linux/x86-arm/arm-hisiv400-linux/bin/arm-hisiv400-linux-gnueabi-strip \
..