Ubuntu 18.04配置OpenCV 4.2.0

星晨雾雨 發表於 2019-12-27 22:06:00

<div class="toc"><div class="toc-container-header">目录</div><ul><li>Step 1: 安装OpenCV的依赖包</li><li>Step 2: 下载OpenCV 4.2.0和OpenCV Contrib 4.2.0</li><li>Step 3: 使用cmake构建库</li><li>Step 4: 使用make构建库</li><li>Step 5: 修改<code>opencv4.pc</code>文件</li><li>Step 6: 在<code>.bashrc</code>文件中添加<code>PKG_CONFIG_PATH</code></li><li>Step 7: 使用C++代码进行验证</li></ul></div>
本文主要介绍在Ubuntu 18.04中从源码安装配置OpenCV，并使用一个简单的例子验证是否安装成功；
具体安装配置步骤，参考文章见：https://cv-tricks.com/installation/opencv-4-1-ubuntu18-04/
与上述链接中提供的教程不同的是：
<ul>
<li>部分依赖包安装可能需要修改</li>
<li>本文安装配置OpenCV版本为4.2，支持使用CUDA对DNN模块加速计算</li>
<li>本文不涉及Python接口配置，仅配置为C++使用，所以会跳过步骤Step2~5</li>
</ul>
<h2 id="step-1-安装opencv的依赖包">Step 1: 安装OpenCV的依赖包</h2>
一步一步的安装下面的所有依赖包：
<pre><code class="language-shell">sudo apt-get update -y # Update the list of packages
sudo apt-get remove -y x264 libx264-dev # Remove the older version of libx264-dev and x264
sudo apt-get install -y build-essential checkinstall cmake pkg-config yasm
sudo apt-get install -y git gfortran
sudo add-apt-repository -y "deb http://security.ubuntu.com/ubuntu xenial-security main"
sudo apt-get install -y libjpeg8-dev libjasper-dev libpng12-dev
sudo apt-get install -y libtiff5-dev
sudo apt-get install -y libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev
sudo apt-get install -y libxine2-dev libv4l-dev
sudo apt-get install -y libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev
sudo apt-get install -y qt5-default libgtk2.0-dev libtbb-dev
sudo apt-get install -y libatlas-base-dev
sudo apt-get install -y libfaac-dev libmp3lame-dev libtheora-dev
sudo apt-get install -y libvorbis-dev libxvidcore-dev
sudo apt-get install -y libopencore-amrnb-dev libopencore-amrwb-dev
sudo apt-get install -y x264 v4l-utils

# Some Optional Dependencies
sudo apt-get install -y libprotobuf-dev protobuf-compiler
sudo apt-get install -y libgoogle-glog-dev libgflags-dev
sudo apt-get install -y libgphoto2-dev libeigen3-dev libhdf5-dev doxygen
</code></pre>
在安装上述依赖包的过程中，可能会存在一些错误提示，这里我将自己遇到的问题列出，并给出解决方案; 
错误1：
<pre><code>E: Unable to locate package libjasper-dev
</code></pre>
执行：
<pre><code>sudo add-apt-repository "deb http://security.ubuntu.com/ubuntu xenial-security main"
sudo apt-get update
</code></pre>
再次执行安装依赖包就行；
错误2：
<pre><code>E: Unable to locate package libgstreamer0.10-dev
</code></pre>
执行:
<pre><code>sudo apt install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev
</code></pre>
即可；
<h2 id="step-2-下载opencv-420和opencv-contrib-420">Step 2: 下载OpenCV 4.2.0和OpenCV Contrib 4.2.0</h2>
<pre><code>OpenCV 4.2.0:
https://github.com/opencv/opencv/releases/tag/4.2.0

OpenCV Contib 4.2.0:
https://github.com/opencv/opencv_contrib/releases/tag/4.2.0
</code></pre>
假如将两个压缩包保存到<code>/home/username/opencv4.2/</code>，进行解压；
如，我将下载得到的文件放在了<code>opencv4.2</code>这个文件夹中，修改成<code>"/home/username/opencv4.2/"</code>;
最后目录结构如下：
<pre><code>/home/username/opencv4.2/
opencv-4.2.0/
opencv_contrib-4.2.0/
ippicv_2019_lnx_intel64_general_20180723.tgz
</code></pre>
相关问题提前说明:
下面几个问题可能出现在安装的不同阶段中,视情况而定;
问题一:
因为网络的原因,如果下载<code>opencv</code>和<code>opencv-contrib</code>时速度比较慢或者下载失败,则可以通过下面链接寻找相应的压缩包(感谢老铁):
<pre><code>https://www.bzblog.online/wordpress/index.php/2020/03/09/opencvdownload/
</code></pre>
问题二:
另外，在编译的时候需要<code>ippicv_2019_lnx_intel64_general_20180723.tgz</code>这个文件，下载的时候会特别慢。这里提供一个链接:
<pre><code>链接：https://pan.baidu.com/s/16afQkmJ0Hu9BenxmJy_1cQ 提取码：Uy22
</code></pre>
问题三:
再另外,在编译的过程中,出现错误
<pre><code>fatal error: boostdesc_bgm.i: No such file or directory
</code></pre>
该问题同样是因为网络的原因,提供链接下载:
<pre><code>链接：https://pan.baidu.com/s/1ihQggYXevvgw7kcMKT8Uvg 提取码：9491
</code></pre>
下载完成后,将带有不同关键字符<code>*-vgg*</code>与<code>*-boost*</code>的文件放入文件夹中;
<pre><code class="language-shell">├── boostdesc_bgm_bi.i
├── boostdesc_bgm_hd.i
├── boostdesc_bgm.i
├── boostdesc_binboost_064.i
├── boostdesc_binboost_128.i
├── boostdesc_binboost_256.i
├── boostdesc_lbgm.i
├── vgg_generated_120.i
├── vgg_generated_48.i
├── vgg_generated_64.i
└── vgg_generated_80.i

</code></pre>
拷贝到:
<pre><code>mv ./* opencv_contrib-4.2.0/modules/xfeatures2d/src/
</code></pre>
问题四:
如果在编译过程中出现下面错误:
<pre><code>opencv_contrib-4.2.0/modules/xfeatures2d/test/test_features2d.cpp:51:10: fatal error: features2d/test/test_detectors_regression.impl.hpp: No such file or directory
</code></pre>
或许你可以发现在文件夹<code>opencv_contrib-4.2.0/modules/xfeatures2d/test</code>中没有下面这个文件
<pre><code>test_detectors_regression.impl.hpp
</code></pre>
那么,它在哪里呢?它在<code>opencv-4.2.0/modules/features2d/test</code>中`;
因此,修改文件夹<code>opencv_contrib-4.2.0/modules/xfeatures2d/test</code>下的文件:
<pre><code>test_features2d.cpp
</code></pre>
将:
<pre><code>#include "features2d/test/test_detectors_regression.impl.hpp"
#include "features2d/test/test_descriptors_regression.impl.hpp"
</code></pre>
修改成:
<pre><code>#include "/home/***/opencv-4.2.0/modules/features2d/test/test_detectors_regression.impl.hpp"
#include "/home/***/opencv-4.2.0/modules/features2d/test/test_descriptors_regression.impl.hpp"
</code></pre>
同理,也需要修改另外一个文件:
<pre><code>test_rotation_and_scale_invariance.cpp
</code></pre>
同理,如果出现以下问题,也需要修改相应文件:
<pre><code>opencv-4.2.0/samples/gpu/surf_keypoint_matcher.cpp:11:10: fatal error: opencv2/xfeatures2d/cuda.hpp: No such file or directory
</code></pre>
那么这个文件在哪呢?是在<code>opencv_contrib-4.2.0/modules/xfeatures2d/include/opencv2/xfeatures2d</code>下,因此,需要修改文件夹<code>opencv-4.2.0/samples/gpu/</code>下的文件:
<pre><code>surf_keypoint_matcher.cpp
</code></pre>
将:
<pre><code>#include "opencv2/xfeatures2d/cuda.hpp"
</code></pre>
修改成:
<pre><code class="language-c++">#include "/home/***/opencv_contrib-4.2.0/modules/xfeatures2d/include/opencv2/xfeatures2d/cuda.hpp"
</code></pre>
问题五:
出现如下问题:
<pre><code>CMakeFiles/example_gpu_surf_keypoint_matcher.dir/surf_keypoint_matcher.cpp.o: In function `main':
surf_keypoint_matcher.cpp:(.text.startup.main+0x352): undefined reference to `cv::cuda::SURF_CUDA::SURF_CUDA()'
surf_keypoint_matcher.cpp:(.text.startup.main+0x579): undefined reference to `cv::cuda::SURF_CUDA::operator()(cv::cuda::GpuMat const&, cv::cuda::GpuMat const&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, bool)'
surf_keypoint_matcher.cpp:(.text.startup.main+0x60d): undefined reference to `cv::cuda::SURF_CUDA::operator()(cv::cuda::GpuMat const&, cv::cuda::GpuMat const&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, bool)'
surf_keypoint_matcher.cpp:(.text.startup.main+0x6af): undefined reference to `cv::cuda::SURF_CUDA::defaultNorm() const'
surf_keypoint_matcher.cpp:(.text.startup.main+0x7ca): undefined reference to `cv::cuda::SURF_CUDA::downloadKeypoints(cv::cuda::GpuMat const&, std::vector<cv::KeyPoint, std::allocator<cv::KeyPoint> >&)'
surf_keypoint_matcher.cpp:(.text.startup.main+0x7ea): undefined reference to `cv::cuda::SURF_CUDA::downloadKeypoints(cv::cuda::GpuMat const&, std::vector<cv::KeyPoint, std::allocator<cv::KeyPoint> >&)'
surf_keypoint_matcher.cpp:(.text.startup.main+0x800): undefined reference to `cv::cuda::SURF_CUDA::downloadDescriptors(cv::cuda::GpuMat const&, std::vector<float, std::allocator<float> >&)'
surf_keypoint_matcher.cpp:(.text.startup.main+0x812): undefined reference to `cv::cuda::SURF_CUDA::downloadDescriptors(cv::cuda::GpuMat const&, std::vector<float, std::allocator<float> >&)'
collect2: error: ld returned 1 exit status
samples/gpu/CMakeFiles/example_gpu_surf_keypoint_matcher.dir/build.make:124: recipe for target 'bin/example_gpu_surf_keypoint_matcher' failed
make: *** Error 1
CMakeFiles/Makefile2:23667: recipe for target 'samples/gpu/CMakeFiles/example_gpu_surf_keypoint_matcher.dir/all' failed
make: *** Error 2

</code></pre>
解决方案:
打开文件:
<pre><code>vim opencv-4.2.0/build/samples/gpu/CMakeFiles/example_gpu_surf_keypoint_matcher.dir/link.txt
</code></pre>
在文件中--字符串:
<pre><code>CMakeFiles/example_gpu_surf_keypoint_matcher.dir/surf_keypoint_matcher.cpp.o
</code></pre>
后面,加上一句:
<pre><code>/home/***/opencv-4.2.0/build/modules/xfeatures2d/CMakeFiles/opencv_xfeatures2d.dir/src/surf.cuda.cpp.o
</code></pre>
注意:找到你本机下的文件路径;
服了啊,为什么第一次弄的时候没有出这么多问题,
感谢各位无私奉献的老铁;当然如果网络给力,上面提供的链接不一定用的上;
<h2 id="step-3-使用cmake构建库">Step 3: 使用cmake构建库</h2>
执行：
<pre><code class="language-shell">cd /home/username/opencv4.2/opencv-4.2.0
mkdir build
cd build
</code></pre>
执行：
<pre><code class="language-shell">cmake -D CMAKE_BUILD_TYPE=RELEASE \
 -D CMAKE_INSTALL_PREFIX=/usr/local \
 -D INSTALL_C_EXAMPLES=ON \
 -D CUDA_ARCH_BIN='7.5' \
 -D WITH_CUDA=ON \
 -D WITH_TBB=ON \
 -D WITH_V4L=ON \
 -D WITH_QT=ON \
 -D WITH_OPENGL=ON \
 -D OPENCV_EXTRA_MODULES_PATH=/home/username/opencv4.2/opencv_contrib-4.2.0/modules \
 -D BUILD_EXAMPLES=ON \
 -D OPENCV_GENERATE_PKGCONFIG=YES ..
</code></pre>
上述步骤需要修改的地方有两处：
<pre><code class="language-shell">CUDA_ARCH_BIN='7.5'
</code></pre>
<blockquote>
由于OpenCV 4.2支持使用CUDA对DNN模块进行加速计算，所以这里配置CUDA；在此之前需要自行配置好NVIDIA显卡的驱动与CUDA；
</blockquote>
其中<code>7.5</code>指的是显卡的计算能力，我的是GTX 1660Ti，对应的计算力为7.5;
这里提供一个链接，可以参考：NVIDA CUDA显卡计算能力对应表
第二处需要修改的地方是：
<pre><code class="language-shell">OPENCV_EXTRA_MODULES_PATH=/home/username/opencv4.2/opencv_contrib-4.2.0/modules
</code></pre>
这里修改成你本机的<code>opencv_contrib-4.2.0/modules</code>的位置
<h2 id="step-4-使用make构建库">Step 4: 使用make构建库</h2>
查看CPU核心数：
<pre><code class="language-shell">nproc
</code></pre>
如，我的CPU核心数为12，执行
<pre><code class="language-shell">cd /home/username/opencv4.2/build
make -j12
</code></pre>
等待一段时候，出现<code>Configuration Done</code>即可，
执行：
<pre><code class="language-shell">sudo make install
</code></pre>
再次等待一段时候后，执行:
<pre><code class="language-shell">sudo sh -c 'echo "/usr/local/lib" >> /etc/ld.so.conf.d/opencv.conf'
sudo ldconfig
</code></pre>
<h2 id="step-5-修改opencv4pc文件">Step 5: 修改<code>opencv4.pc</code>文件</h2>
如果上述配置成功，则会在<code>/usr/local/lib/</code>文件夹中出现一个<code>pkgconfig</code>文件夹，里面有一个<code>opencv.pc</code>文件，内容大致如下：
<pre><code class="language-vim"># Package Information for pkg-config

prefix=/usr/local
exec_prefix=${prefix}
libdir=${exec_prefix}/lib
includedir_old=${prefix}/include/opencv4/opencv2
includedir_new=${prefix}/include/opencv4

Name: OpenCV
Description: Open Source Computer Vision Library
Version: 4.2.0
Libs: -L${exec_prefix}/lib -lopencv_gapi -lopencv_stitching -lopencv_aruco -lopencv_bgsegm -lopencv_bioinspired -lopencv_ccalib -lopencv_cudabgsegm -lopencv_cudafeatures2d -lopencv_cudaobjdetect -lopencv_cudastereo -lopencv_cvv -lopencv_dnn_objdetect -lopencv_dnn_superres -lopencv_dpm -lopencv_highgui -lopencv_face -lopencv_freetype -lopencv_fuzzy -lopencv_hdf -lopencv_hfs -lopencv_img_hash -lopencv_line_descriptor -lopencv_quality -lopencv_reg -lopencv_rgbd -lopencv_saliency -lopencv_sfm -lopencv_stereo -lopencv_structured_light -lopencv_phase_unwrapping -lopencv_superres -lopencv_cudacodec -lopencv_surface_matching -lopencv_tracking -lopencv_datasets -lopencv_text -lopencv_dnn -lopencv_plot -lopencv_videostab -lopencv_cudaoptflow -lopencv_optflow -lopencv_cudalegacy -lopencv_videoio -lopencv_cudawarping -lopencv_xfeatures2d -lopencv_shape -lopencv_ml -lopencv_ximgproc -lopencv_video -lopencv_xobjdetect -lopencv_objdetect -lopencv_calib3d -lopencv_imgcodecs -lopencv_features2d -lopencv_flann -lopencv_xphoto -lopencv_photo -lopencv_cudaimgproc -lopencv_cudafilters -lopencv_imgproc -lopencv_cudaarithm -lopencv_core -lopencv_cudev
Libs.private: -lm -lpthread -L/usr/lib/x86_64-linux-gnu -lGL -lGLU -lcudart_static -ldl -lrt -lnppc -lnppial -lnppicc -lnppicom -lnppidei -lnppif -lnppig -lnppim -lnppist -lnppisu -lnppitc -lnpps -lcublas -lcudnn -lcufft -L-L/usr/local/cuda -llib64 -L-L/usr/lib -lx86_64-linux-gnu
Cflags: -I${includedir_old} -I${includedir_new}
</code></pre>
注意：需要将第6行修改为：
<pre><code class="language-vim">includedir_old=${prefix}/include/opencv4/opencv2
</code></pre>
如果没有自动生成，可以试着新建一个文件，将上述的内容复制进去，继续下一步；
<h2 id="step-6-在bashrc文件中添加pkg_config_path">Step 6: 在<code>.bashrc</code>文件中添加<code>PKG_CONFIG_PATH</code></h2>
执行:
<pre><code class="language-shell">sudo gedit ~/.bashrc
</code></pre>
在文件最后添加:
<pre><code>PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig
export PKG_CONFIG_PATH
</code></pre>
退出后，执行
<pre><code class="language-shell">source ~/.bashrc

# 判断路径时候添加成功，返回:/usr/local/lib/pkgconfig即可
echo $PKG_CONFIG_PATH
</code></pre>
<h2 id="step-7-使用c代码进行验证">Step 7: 使用C++代码进行验证</h2>
在任意目录下创建<code>test.cpp</code>文件，加入下面内容：
<pre><code class="language-c++">#include "opencv.hpp"

using namespace cv;
using namespace std;

int main( int argc, char** argv )
{
cout << "OpenCV version : " << CV_VERSION << endl;
cout << "Major version : " << CV_MAJOR_VERSION << endl;
cout << "Minor version : " << CV_MINOR_VERSION << endl;
cout << "Subminor version : " << CV_SUBMINOR_VERSION << endl;
}
</code></pre>
使用命令行在其文件夹下执行：
<pre><code class="language-shell"># 编译test.cpp程序，并生成可执行文件
g++ -std=c++11 test.cpp `pkg-config --libs --cflags opencv4` -o result

# 执行可执行文件
./result

</code></pre>
输出以下内容，即表明配置成功
<pre><code class="language-shell">OpenCV version : 4.2.0
Major version : 4
Minor version : 2
Subminor version : 0

</code></pre> 
来源：https://www.cnblogs.com/chenzhen0530/p/12109868.html

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Ubuntu 18.04配置OpenCV 4.2.0