Ubuntu - OpenCV 源码安装与测试

Author： AIHGF
发布时间：January 3, 2019
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Categories：操作系统

Ubuntu16.04 中，OpenCV 多版本的升级与安装.

1. OpenCV 编译安装

1.1. 查看 Ubuntu 当前的 OpenCV 版本

pkg-config --modversion opencv
# 2.4.9.1

在 /usr/bin 和 /usr/include路径里包含了默认 OpenCV 版本的相关文件.

1.2. 依赖库安装

[1] - 官方必须依赖库

sudo apt-get update
sudo apt-get install cmake git
sudo apt-get install build-essential \
                     libgtk2.0-dev \
                     pkg-config \
                     libavcodec-dev \
                     libavformat-dev

[2] - 官方建议依赖库

sudo apt-get install python-dev \
                     libtbb2 \
                     libtbb-dev \
                     libjpeg-dev \
                     libpng-dev \
                     libtiff-dev \
                     libjasper-dev \
                     libdc1394-22-dev

[3] - OPENGL 支持依赖库

sudo apt-get install freeglut3-dev \
                     mesa-common-dev \
                     libgtkglext1 \
                     libgtkglext1-dev

[4] - 视频解码支持依赖库

sudo apt-get install checkinstall \
                     yasm \
                     libgstreamer0.10-dev \
                     libgstreamer-plugins-base0.10-dev \
                     libv4l-dev \
                     libtbb-dev \
                     libqt4-dev \
                     libgtk2.0-dev \
                     libmp3lame-dev \
                     libtheora-dev \
                     libvorbis-dev \
                     libxvidcore-dev \
                     x264 \
                     v4l-utils

[5] - 其它可能依赖项

sudo apt-get install libgphoto2-dev \
                     libavresample-dev \ 
                     liblapacke-dev \
                     gtk+-3.0 \
                     libgtk-3-dev \ 
                     libeigen3-dev \ 
                     tesseract-ocr \
                     liblept5 \
                     leptonica-progs \
                     libleptonica-dev

1.3. OpenCV 源码下载

下载路径：

https://github.com/opencv/opencv/releases

1.4. OpenCV 3.4 编译安装

假设路径为 ROOT_DIR = /opt/opencv3.4/

cd $ROOT_DIR
mkdir build
cd build 
cmake -D CMAKE_BUILD_TYPE=RELEASE \
      -D CMAKE_INSTALL_PREFIX=/usr/local/opencv34 ..
# cmake -D WITH_TBB=ON 
#         -D BUILD_NEW_PYTHON_SUPPORT=ON \
#        -D WITH_V4L=ON \
#        -D INSTALL_C_EXAMPLES=ON \
#        -D INSTALL_PYTHON_EXAMPLES=ON \
#        -D BUILD_EXAMPLES=ON \
#        -D WITH_QT=ON \
#        -D WITH_OPENGL=ON ..
make -j4
sudo make install

在编译安装时，ippicv 库的下载文件 - ippicv_2019_lnx_intel64_general_20180723.tgz 速度特别慢.

因此，采用离线下载文件，再进行编译.

ippicv_2019_lnx_intel64_general_20180723.tgz 文件下载：
百度网盘链接: https://pan.baidu.com/s/1mVTSdn6hTgo8P3ASKauyDg 提取码: hiux

假设 ippicv_2019_lnx_intel64_general_20180723.tgz放置于 ROOT_DIR/3rdparty/ippicv/ 路径，

并修改 ROOT_DIR/3rdparty/ippicv/ippicv.cmake 文件(47 行)：

修改前：

41  set(THE_ROOT "${OpenCV_BINARY_DIR}/3rdparty/ippicv")
42  ocv_download(FILENAME ${OPENCV_ICV_NAME}
43               HASH ${OPENCV_ICV_HASH}
44               URL
45                 "${OPENCV_IPPICV_URL}"
46                 "$ENV{OPENCV_IPPICV_URL}"
47                 "https://raw.githubusercontent.com/opencv/opencv_3rdparty/${IPPICV_COMMIT}/ippicv/"
48               DESTINATION_DIR "${THE_ROOT}"
49               ID IPPICV
50               STATUS res
51               UNPACK RELATIVE_URL)

修改后：

41  set(THE_ROOT "${OpenCV_BINARY_DIR}/3rdparty/ippicv")
42  ocv_download(FILENAME ${OPENCV_ICV_NAME}
43               HASH ${OPENCV_ICV_HASH}
44               URL
45                 "${OPENCV_IPPICV_URL}"
46                 "$ENV{OPENCV_IPPICV_URL}"
47                 "file: ROOT_DIR/3rdparty/ippicv/ippicv_2019_lnx_intel64_general_20180723.tgz"
48               DESTINATION_DIR "${THE_ROOT}"
49               ID IPPICV
50               STATUS res
51               UNPACK RELATIVE_URL)

修改后，下载 ippicv文件时，会自动从本地文件加载.

1.5. OpenCV 4.0.1 (最新版本) 编译安装

假设路径为 ROOT_DIR = /opt/opencv-4.0.1/

cd $ROOT_DIR
mkdir build
cd build 
cmake -D CMAKE_BUILD_TYPE=RELEASE \
      -D BUILD_NEW_PYTHON_SUPPORT=ON \
      -D CMAKE_INSTALL_PREFIX=/usr/local/opencv-4.0.1 \
      -D OPENCV_GENERATE_PKGCONFIG=ON ..
#cmake -D CMAKE_BUILD_TYPE=RELEASE \
#      -D CMAKE_INSTALL_PREFIX=/usr/local/opencv-4.0.1 \
#      -D WITH_CUDA=ON \
#      -D OPENCV_EXTRA_MODULES_PATH=/opt/opencv_contrib/modules 
#      -D WITH_CUBLAS=1 \
#      -D ENABLE_FAST_MATH=1 \
#      -D CUDA_FAST_MATH=1 \
#      -D WITH_CUFFT=ON \
#      -D WITH_NVCUVID=ON \
#      -D WITH_V4L=ON \
#      -D WITH_LIBV4L=ON \
#      -D WITH_OPENGL=ON \
#      -D WITH_FFMPEG=ON \
#      -D BUILD_TIFF=ON \
#      -D WITH_LAPACK=OFF..
#     -D INSTALL_C_EXAMPLES=ON \
#     -D BUILD_EXAMPLES=ON ..
make
sudo make install

1.5.1 OpenCV 4.0.1 CUDA 编译问题

[1] - -DWITH_CUDA=ON 需要设置 -DOPENCV_EXTRA_MODULES_PATH=<opencv_contrib>/modules

[2] - 如果没有contrib, make 的时候会出现错误：gpu_mat.cu:47:2: error: #error "opencv_cudev is required".

Github - opencv_contrib

[3] - 在 opencv_contrib/modules/face 中会要下载 face_landmark_model.dat 文件(69M)，也会遇到下载慢的问题，可以采用类似于 ippicv 库的处理方式.

face_landmark_model.mat 下载路径：
https://github.com/opencv/opencv_3rdparty/tree/contrib_face_alignment_20170818

在opencv_contrib/modules/face/CMakeLists.txt 文件：

set(__commit_hash "8afa57abc8229d611c4937165d20e2a2d9fc5a12")
set(__file_hash "7505c44ca4eb54b4ab1e4777cb96ac05")
ocv_download(
    FILENAME face_landmark_model.dat
    HASH ${__file_hash}
    URL
      "${OPENCV_FACE_ALIGNMENT_URL}"
      "$ENV{OPENCV_FACE_ALIGNMENT_URL}"
      "https://raw.githubusercontent.com/opencv/opencv_3rdparty/${__commit_hash}/"
    DESTINATION_DIR "${CMAKE_BINARY_DIR}/${OPENCV_TEST_DATA_INSTALL_PATH}/cv/face/"
    ID "data"
    RELATIVE_URL
    STATUS res
)
if(NOT res)
  message(WARNING "Face: Can't get model file for face alignment.")
endif()

将离线下载的 face_landmark_model.dat 放到 /opt/opencv-4.0.1/build/share/opencv4/testdata/cv/face/ 路径中.

1.6. 环境变量设置

配置 OpenCV 编译环境：

编辑或新建 /etc/ld.so.conf.d/opencv.conf:

sudo gedit /etc/ld.so.conf.d/opencv.conf

文件尾部添加如下内容：

/usr/local/opencv-4.0.1/lib

生效配置文件：

sudo ldconfig

sudo gedit ~/.bashrc

在该文件尾部添加如下行内容：

export PKG_CONFIG_PATH=/usr/local/opencv-4.0.1/lib/pkgconfig:$PKG_CONFIG_PATH
export LD_LIBRARY_PATH=/usr/local/opencv-4.0.1/lib:$LD_LIBRARY_PATH

环境变量生效：

source ~/.bashrc

查看opencv版本及库信息：

pkg-config --modversion opencv4
# 4.0.1
pkg-config --libs opencv4
pkg-config --cflags opencv4

1.7. OpenCV 的 `cmake` 使用

使用 cmake 工具时，在 CMakeLists.txt 文件中添加一下内容：

set(OpenCV_DIR /usr/local/opencv-4.0.1/share/OpenCV)
find_package(OpenCV 4.0.1 REQUIRED)
include_directories(SYSTEM ${OpenCV_INCLUDE_DIRS} /usr/local/opencv-4.0.1/include)

1.8. Python 接口

sudo ln -s \
    /usr/local/opencv-4.0.1/lib/python2.7/dist-packages/cv2/python-2.7/cv2.so \
    /usr/local/lib/python2.7/dist-packages/cv2/cv2.so
sudo ln -s \
    /usr/local/opencv-4.0.1/lib/python3.5/dist-packages/cv2.cpython-35m-x86_64-linux-gnu.so \
    /usr/local/lib/python3.5/dist-packages/cv2/cv2.cpython-35m-x86_64-linux-gnu.so

2. OpenCV 测试

以 opencv-4.0.1 为例.

假设项目路径为：/path/to/opencv_demo/:

2.1. 例 - 显示图片

新建 opencv_test.cpp 文件：

#include <iostream>
#include <opencv2/opencv.hpp>

using namespace cv;
using namespace std;

int main(int argc, char** argv)
{

    if ( argc != 2 )
    {
        cout << "Need to load an image ..." << endl;
        return -1;
    }
    Mat image;
    image = imread( argv[1], 1 );
    if ( image.empty() )
    {
        cout<<"No image data!"<< endl;
        return -1;
    }
    namedWindow("Display Image", WINDOW_AUTOSIZE );
    imshow("Display Image", image);
    waitKey(0);
    return 0;
}

新建 CMakeLists.txt 文件：

cmake_minimum_required(VERSION 2.8)
project( DisplayImage )
set(OpenCV_DIR /usr/local/opencv-4.0.1/lib/cmake/opencv4)
find_package(OpenCV REQUIRED )
add_executable( opencv_test opencv_test.cpp )
target_link_libraries( opencv_test ${OpenCV_LIBS} )

执行：

cmake . -DCMAKE_CXX_FLAGS="-std=c++11" # opencv4.0 需要 c++ 11 支持
make
./opencv_test test.jpg

显示图片.

2.2. 例 - SURF 特征点检测

新建 surf_test.cpp 文件：

#include <iostream>
#include <vector>
#include <opencv2/xfeatures2d.hpp>
#include <opencv2/highgui.hpp>

using namespace cv;
using namespace std;

int main(int argc, char** argv)
{
    Mat img1 = imread(argv[1], 1);
    Mat img2 = imread(argv[2], 1);
    if ((img1.data == NULL)||(img2.data == NULL))
    {
        cout << "No images exist" << endl;
        return -1;
    }
    Ptr<Feature2D> surf = xfeatures2d::SURF::create(1000);

    vector<KeyPoint> keypoints_1, keypoints_2;
    Mat descriptors_1, descriptors_2;

    surf->detectAndCompute(img1, Mat(), keypoints_1, descriptors_1 );
    surf->detectAndCompute(img2, Mat(), keypoints_2, descriptors_2 );
    drawKeypoints(img1, keypoints_1, img1);
    drawKeypoints(img2, keypoints_2, img2);

    namedWindow("img1",0);
    resizeWindow("img1",500,500);
    imshow("img1", img1);

    namedWindow("img2",0);
    resizeWindow("img2",500,500);
    imshow("img2", img2);

    FlannBasedMatcher matcher;
    std::vector< DMatch > matches;
    matcher.match( descriptors_1, descriptors_2, matches );
    double max_dist = 0; double min_dist = 100;

    for( int i = 0; i < descriptors_1.rows; i++ )
    { 
        double dist = matches[i].distance;
        if( dist < min_dist ) min_dist = dist;
        if( dist > max_dist ) max_dist = dist;
    }
    printf("-- Max dist : %f \n", max_dist );
    printf("-- Min dist : %f \n", min_dist );

    std::vector< DMatch > good_matches;
    for( int i = 0; i < descriptors_1.rows; i++ )
    { 
        if( matches[i].distance <= max(2*min_dist, 0.02) )
        { 
            good_matches.push_back( matches[i]); 
        }
    }

    Mat img_matches;
    drawMatches( img1, keypoints_1, img2, keypoints_2,
                 good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
                 vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

    namedWindow("Good Matches",0);
    resizeWindow("Good Matches",800,800);
    imshow( "Good Matches", img_matches );

    for( int i = 0; i < (int)good_matches.size(); i++ )
    { 
        printf( "-- Good Match [%d] Keypoint 1: %d  -- Keypoint 2: %d  \n",
        i, good_matches[i].queryIdx, good_matches[i].trainIdx ); 
    }

    waitKey(0);
    return 0;
}

新建 CMakeLists.txt 文件：

set(CMAKE_CXX_FLAGS "-std=c++11")    
cmake_minimum_required(VERSION 2.8)
project( SURF_test )
set(OpenCV_DIR /usr/local/opencv-4.0.1/lib/cmake/opencv4)
find_package( OpenCV REQUIRED )
add_executable( SURF_test surf_test.cpp )
target_link_libraries( SURF_test ${OpenCV_LIBS} )

执行：

cmake .
make
./surf_test c1.jpg c2.jpg

Last modification：January 18th, 2019 at 02:22 pm

Ubuntu - OpenCV 源码安装与测试

AIHGF • 2019 年 01 月 03 日

Ubuntu16.04 中，OpenCV 多版本的升级与安装.

1. OpenCV 编译安装

1.1. 查看 Ubuntu 当前的 OpenCV 版本

pkg-config --modversion opencv
# 2.4.9.1

在 /usr/bin 和 /usr/include路径里包含了默认 OpenCV 版本的相关文件.

1.2. 依赖库安装

[1] - 官方必须依赖库

sudo apt-get update
sudo apt-get install cmake git
sudo apt-get install build-essential \
                     libgtk2.0-dev \
                     pkg-config \
                     libavcodec-dev \
                     libavformat-dev

[2] - 官方建议依赖库

sudo apt-get install python-dev \
                     libtbb2 \
                     libtbb-dev \
                     libjpeg-dev \
                     libpng-dev \
                     libtiff-dev \
                     libjasper-dev \
                     libdc1394-22-dev

[3] - OPENGL 支持依赖库

sudo apt-get install freeglut3-dev \
                     mesa-common-dev \
                     libgtkglext1 \
                     libgtkglext1-dev

[4] - 视频解码支持依赖库

sudo apt-get install checkinstall \
                     yasm \
                     libgstreamer0.10-dev \
                     libgstreamer-plugins-base0.10-dev \
                     libv4l-dev \
                     libtbb-dev \
                     libqt4-dev \
                     libgtk2.0-dev \
                     libmp3lame-dev \
                     libtheora-dev \
                     libvorbis-dev \
                     libxvidcore-dev \
                     x264 \
                     v4l-utils

[5] - 其它可能依赖项

sudo apt-get install libgphoto2-dev \
                     libavresample-dev \ 
                     liblapacke-dev \
                     gtk+-3.0 \
                     libgtk-3-dev \ 
                     libeigen3-dev \ 
                     tesseract-ocr \
                     liblept5 \
                     leptonica-progs \
                     libleptonica-dev

1.3. OpenCV 源码下载

下载路径：

https://github.com/opencv/opencv/releases

1.4. OpenCV 3.4 编译安装

假设路径为 ROOT_DIR = /opt/opencv3.4/

cd $ROOT_DIR
mkdir build
cd build 
cmake -D CMAKE_BUILD_TYPE=RELEASE \
      -D CMAKE_INSTALL_PREFIX=/usr/local/opencv34 ..
# cmake -D WITH_TBB=ON 
#         -D BUILD_NEW_PYTHON_SUPPORT=ON \
#        -D WITH_V4L=ON \
#        -D INSTALL_C_EXAMPLES=ON \
#        -D INSTALL_PYTHON_EXAMPLES=ON \
#        -D BUILD_EXAMPLES=ON \
#        -D WITH_QT=ON \
#        -D WITH_OPENGL=ON ..
make -j4
sudo make install

在编译安装时，ippicv 库的下载文件 - ippicv_2019_lnx_intel64_general_20180723.tgz 速度特别慢.

因此，采用离线下载文件，再进行编译.

ippicv_2019_lnx_intel64_general_20180723.tgz 文件下载：
百度网盘链接: https://pan.baidu.com/s/1mVTSdn6hTgo8P3ASKauyDg 提取码: hiux

假设 ippicv_2019_lnx_intel64_general_20180723.tgz放置于 ROOT_DIR/3rdparty/ippicv/ 路径，

并修改 ROOT_DIR/3rdparty/ippicv/ippicv.cmake 文件(47 行)：

修改前：

41  set(THE_ROOT "${OpenCV_BINARY_DIR}/3rdparty/ippicv")
42  ocv_download(FILENAME ${OPENCV_ICV_NAME}
43               HASH ${OPENCV_ICV_HASH}
44               URL
45                 "${OPENCV_IPPICV_URL}"
46                 "$ENV{OPENCV_IPPICV_URL}"
47                 "https://raw.githubusercontent.com/opencv/opencv_3rdparty/${IPPICV_COMMIT}/ippicv/"
48               DESTINATION_DIR "${THE_ROOT}"
49               ID IPPICV
50               STATUS res
51               UNPACK RELATIVE_URL)

修改后：

41  set(THE_ROOT "${OpenCV_BINARY_DIR}/3rdparty/ippicv")
42  ocv_download(FILENAME ${OPENCV_ICV_NAME}
43               HASH ${OPENCV_ICV_HASH}
44               URL
45                 "${OPENCV_IPPICV_URL}"
46                 "$ENV{OPENCV_IPPICV_URL}"
47                 "file: ROOT_DIR/3rdparty/ippicv/ippicv_2019_lnx_intel64_general_20180723.tgz"
48               DESTINATION_DIR "${THE_ROOT}"
49               ID IPPICV
50               STATUS res
51               UNPACK RELATIVE_URL)

修改后，下载 ippicv文件时，会自动从本地文件加载.

1.5. OpenCV 4.0.1 (最新版本) 编译安装

假设路径为 ROOT_DIR = /opt/opencv-4.0.1/

cd $ROOT_DIR
mkdir build
cd build 
cmake -D CMAKE_BUILD_TYPE=RELEASE \
      -D BUILD_NEW_PYTHON_SUPPORT=ON \
      -D CMAKE_INSTALL_PREFIX=/usr/local/opencv-4.0.1 \
      -D OPENCV_GENERATE_PKGCONFIG=ON ..
#cmake -D CMAKE_BUILD_TYPE=RELEASE \
#      -D CMAKE_INSTALL_PREFIX=/usr/local/opencv-4.0.1 \
#      -D WITH_CUDA=ON \
#      -D OPENCV_EXTRA_MODULES_PATH=/opt/opencv_contrib/modules 
#      -D WITH_CUBLAS=1 \
#      -D ENABLE_FAST_MATH=1 \
#      -D CUDA_FAST_MATH=1 \
#      -D WITH_CUFFT=ON \
#      -D WITH_NVCUVID=ON \
#      -D WITH_V4L=ON \
#      -D WITH_LIBV4L=ON \
#      -D WITH_OPENGL=ON \
#      -D WITH_FFMPEG=ON \
#      -D BUILD_TIFF=ON \
#      -D WITH_LAPACK=OFF..
#     -D INSTALL_C_EXAMPLES=ON \
#     -D BUILD_EXAMPLES=ON ..
make
sudo make install

1.5.1 OpenCV 4.0.1 CUDA 编译问题

[1] - -DWITH_CUDA=ON 需要设置 -DOPENCV_EXTRA_MODULES_PATH=<opencv_contrib>/modules

[2] - 如果没有contrib, make 的时候会出现错误：gpu_mat.cu:47:2: error: #error "opencv_cudev is required".

Github - opencv_contrib

[3] - 在 opencv_contrib/modules/face 中会要下载 face_landmark_model.dat 文件(69M)，也会遇到下载慢的问题，可以采用类似于 ippicv 库的处理方式.

face_landmark_model.mat 下载路径：
https://github.com/opencv/opencv_3rdparty/tree/contrib_face_alignment_20170818

在opencv_contrib/modules/face/CMakeLists.txt 文件：

set(__commit_hash "8afa57abc8229d611c4937165d20e2a2d9fc5a12")
set(__file_hash "7505c44ca4eb54b4ab1e4777cb96ac05")
ocv_download(
    FILENAME face_landmark_model.dat
    HASH ${__file_hash}
    URL
      "${OPENCV_FACE_ALIGNMENT_URL}"
      "$ENV{OPENCV_FACE_ALIGNMENT_URL}"
      "https://raw.githubusercontent.com/opencv/opencv_3rdparty/${__commit_hash}/"
    DESTINATION_DIR "${CMAKE_BINARY_DIR}/${OPENCV_TEST_DATA_INSTALL_PATH}/cv/face/"
    ID "data"
    RELATIVE_URL
    STATUS res
)
if(NOT res)
  message(WARNING "Face: Can't get model file for face alignment.")
endif()

将离线下载的 face_landmark_model.dat 放到 /opt/opencv-4.0.1/build/share/opencv4/testdata/cv/face/ 路径中.

1.6. 环境变量设置

配置 OpenCV 编译环境：

编辑或新建 /etc/ld.so.conf.d/opencv.conf:

sudo gedit /etc/ld.so.conf.d/opencv.conf

文件尾部添加如下内容：

/usr/local/opencv-4.0.1/lib

生效配置文件：

sudo ldconfig

sudo gedit ~/.bashrc

在该文件尾部添加如下行内容：

export PKG_CONFIG_PATH=/usr/local/opencv-4.0.1/lib/pkgconfig:$PKG_CONFIG_PATH
export LD_LIBRARY_PATH=/usr/local/opencv-4.0.1/lib:$LD_LIBRARY_PATH

环境变量生效：

source ~/.bashrc

查看opencv版本及库信息：

pkg-config --modversion opencv4
# 4.0.1
pkg-config --libs opencv4
pkg-config --cflags opencv4

1.7. OpenCV 的 `cmake` 使用

使用 cmake 工具时，在 CMakeLists.txt 文件中添加一下内容：

set(OpenCV_DIR /usr/local/opencv-4.0.1/share/OpenCV)
find_package(OpenCV 4.0.1 REQUIRED)
include_directories(SYSTEM ${OpenCV_INCLUDE_DIRS} /usr/local/opencv-4.0.1/include)

1.8. Python 接口

sudo ln -s \
    /usr/local/opencv-4.0.1/lib/python2.7/dist-packages/cv2/python-2.7/cv2.so \
    /usr/local/lib/python2.7/dist-packages/cv2/cv2.so
sudo ln -s \
    /usr/local/opencv-4.0.1/lib/python3.5/dist-packages/cv2.cpython-35m-x86_64-linux-gnu.so \
    /usr/local/lib/python3.5/dist-packages/cv2/cv2.cpython-35m-x86_64-linux-gnu.so

2. OpenCV 测试

以 opencv-4.0.1 为例.

假设项目路径为：/path/to/opencv_demo/:

2.1. 例 - 显示图片

新建 opencv_test.cpp 文件：

#include <iostream>
#include <opencv2/opencv.hpp>

using namespace cv;
using namespace std;

int main(int argc, char** argv)
{

    if ( argc != 2 )
    {
        cout << "Need to load an image ..." << endl;
        return -1;
    }
    Mat image;
    image = imread( argv[1], 1 );
    if ( image.empty() )
    {
        cout<<"No image data!"<< endl;
        return -1;
    }
    namedWindow("Display Image", WINDOW_AUTOSIZE );
    imshow("Display Image", image);
    waitKey(0);
    return 0;
}

新建 CMakeLists.txt 文件：

cmake_minimum_required(VERSION 2.8)
project( DisplayImage )
set(OpenCV_DIR /usr/local/opencv-4.0.1/lib/cmake/opencv4)
find_package(OpenCV REQUIRED )
add_executable( opencv_test opencv_test.cpp )
target_link_libraries( opencv_test ${OpenCV_LIBS} )

执行：

cmake . -DCMAKE_CXX_FLAGS="-std=c++11" # opencv4.0 需要 c++ 11 支持
make
./opencv_test test.jpg

显示图片.

2.2. 例 - SURF 特征点检测

新建 surf_test.cpp 文件：

#include <iostream>
#include <vector>
#include <opencv2/xfeatures2d.hpp>
#include <opencv2/highgui.hpp>

using namespace cv;
using namespace std;

int main(int argc, char** argv)
{
    Mat img1 = imread(argv[1], 1);
    Mat img2 = imread(argv[2], 1);
    if ((img1.data == NULL)||(img2.data == NULL))
    {
        cout << "No images exist" << endl;
        return -1;
    }
    Ptr<Feature2D> surf = xfeatures2d::SURF::create(1000);

    vector<KeyPoint> keypoints_1, keypoints_2;
    Mat descriptors_1, descriptors_2;

    surf->detectAndCompute(img1, Mat(), keypoints_1, descriptors_1 );
    surf->detectAndCompute(img2, Mat(), keypoints_2, descriptors_2 );
    drawKeypoints(img1, keypoints_1, img1);
    drawKeypoints(img2, keypoints_2, img2);

    namedWindow("img1",0);
    resizeWindow("img1",500,500);
    imshow("img1", img1);

    namedWindow("img2",0);
    resizeWindow("img2",500,500);
    imshow("img2", img2);

    FlannBasedMatcher matcher;
    std::vector< DMatch > matches;
    matcher.match( descriptors_1, descriptors_2, matches );
    double max_dist = 0; double min_dist = 100;

    for( int i = 0; i < descriptors_1.rows; i++ )
    { 
        double dist = matches[i].distance;
        if( dist < min_dist ) min_dist = dist;
        if( dist > max_dist ) max_dist = dist;
    }
    printf("-- Max dist : %f \n", max_dist );
    printf("-- Min dist : %f \n", min_dist );

    std::vector< DMatch > good_matches;
    for( int i = 0; i < descriptors_1.rows; i++ )
    { 
        if( matches[i].distance <= max(2*min_dist, 0.02) )
        { 
            good_matches.push_back( matches[i]); 
        }
    }

    Mat img_matches;
    drawMatches( img1, keypoints_1, img2, keypoints_2,
                 good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
                 vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

    namedWindow("Good Matches",0);
    resizeWindow("Good Matches",800,800);
    imshow( "Good Matches", img_matches );

    for( int i = 0; i < (int)good_matches.size(); i++ )
    { 
        printf( "-- Good Match [%d] Keypoint 1: %d  -- Keypoint 2: %d  \n",
        i, good_matches[i].queryIdx, good_matches[i].trainIdx ); 
    }

    waitKey(0);
    return 0;
}

新建 CMakeLists.txt 文件：

set(CMAKE_CXX_FLAGS "-std=c++11")    
cmake_minimum_required(VERSION 2.8)
project( SURF_test )
set(OpenCV_DIR /usr/local/opencv-4.0.1/lib/cmake/opencv4)
find_package( OpenCV REQUIRED )
add_executable( SURF_test surf_test.cpp )
target_link_libraries( SURF_test ${OpenCV_LIBS} )

执行：

cmake .
make
./surf_test c1.jpg c2.jpg

Ubuntu - OpenCV 源码安装与测试

1. OpenCV 编译安装

1.1. 查看 Ubuntu 当前的 OpenCV 版本

1.2. 依赖库安装

1.3. OpenCV 源码下载

1.4. OpenCV 3.4 编译安装

1.5. OpenCV 4.0.1 (最新版本) 编译安装

1.5.1 OpenCV 4.0.1 CUDA 编译问题

1.6. 环境变量设置

1.7. OpenCV 的 `cmake` 使用

1.8. Python 接口

2. OpenCV 测试

2.1. 例 - 显示图片

2.2. 例 - SURF 特征点检测

※相关文章推荐※

※最新文章推荐※

Leave a Comment Cancel reply

Ubuntu - OpenCV 源码安装与测试

1. OpenCV 编译安装

1.1. 查看 Ubuntu 当前的 OpenCV 版本

1.2. 依赖库安装

1.3. OpenCV 源码下载

1.4. OpenCV 3.4 编译安装

1.5. OpenCV 4.0.1 (最新版本) 编译安装

1.5.1 OpenCV 4.0.1 CUDA 编译问题

1.6. 环境变量设置

1.7. OpenCV 的 `cmake` 使用

1.8. Python 接口

2. OpenCV 测试

2.1. 例 - 显示图片

2.2. 例 - SURF 特征点检测

1. OpenCV 编译安装

1.1. 查看 Ubuntu 当前的 OpenCV 版本

1.2. 依赖库安装

1.3. OpenCV 源码下载

1.4. OpenCV 3.4 编译安装

1.5. OpenCV 4.0.1 (最新版本) 编译安装

1.5.1 OpenCV 4.0.1 CUDA 编译问题

1.6. 环境变量设置

1.7. OpenCV 的 cmake 使用

1.8. Python 接口

2. OpenCV 测试

2.1. 例 - 显示图片

2.2. 例 - SURF 特征点检测

※相关文章推荐※

※最新文章推荐※

Leave a Comment Cancel reply

Ubuntu - OpenCV 源码安装与测试

1. OpenCV 编译安装

1.1. 查看 Ubuntu 当前的 OpenCV 版本

1.2. 依赖库安装

1.3. OpenCV 源码下载

1.4. OpenCV 3.4 编译安装

1.5. OpenCV 4.0.1 (最新版本) 编译安装

1.5.1 OpenCV 4.0.1 CUDA 编译问题

1.6. 环境变量设置

1.7. OpenCV 的 cmake 使用

1.8. Python 接口

2. OpenCV 测试

2.1. 例 - 显示图片

2.2. 例 - SURF 特征点检测

1.7. OpenCV 的 `cmake` 使用

1.7. OpenCV 的 `cmake` 使用