Ros Kinetic 配置 OpenCV2和CV_bridge (Python, C++)

短命女 2022-01-07 00:37 572阅读 0赞

本篇介绍如何在Ros-kinetic环境下运用opencv2进行开发的配置，系统平台为64位Ubuntu16.04。

**需要系统环境：**

1.Ros kinetic版本，一般自带cv\_bridge, 若没有可以通过apt下载

sudo apt-get install ros-kinetic-cv-bridge

2.OpenCV 2.4.9版本，一般来说cv\_bridge依赖的OpenCV版本为2.4.8，亲测2.4.9可以用，安装可以参考https://blog.csdn.net/u013250416/article/details/78913126

2.1 先下载OpenCV的源码[http://opencv.org/downloads.html][http_opencv.org_downloads.html]并解压到任意目录

2.2 事先安装下列软件

sudo apt-get install build-essential cmake libgtk2.0-dev pkg-config python-dev python-numpy libavcodec-dev libavformat-dev libswscale-dev

2.3 进入cmake并编译

cd cmake
    cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local ..  
    sudo make install

2.4 测试

新建C++代码test.cpp：

1 #include <opencv2/core/core.hpp>
     2 #include <opencv2/imgproc/imgproc.hpp>
     3 #include <opencv2/highgui/highgui.hpp>
     4 #include <iostream>
     5 using namespace cv;
     6 using namespace std;
     7 int main (int argc, char **argv)
     8 {
     9     Mat image, image_gray;
    10     image = imread(argv[1], CV_LOAD_IMAGE_COLOR );
    11     if (argc != 2 || !image.data) {
    12         cout << "No image data\n";
    13         return -1;
    14     }
    15 
    16     cvtColor(image, image_gray, CV_RGB2GRAY);
    17     namedWindow("image", CV_WINDOW_AUTOSIZE);
    18     namedWindow("image gray", CV_WINDOW_AUTOSIZE);
    19 
    20     imshow("image", image);
    21     imshow("image gray", image_gray);
    22 
    23     waitKey(0);
    24     return 0;
    25 }

新建makefile文件：

CC = g++
    # 可执行文件
    TARGET = test
    # C文件
    SRCS = main.cpp
    # 目标文件
    OBJS = $(SRCS:.cpp=.o)
    # 库文件
    DLIBS = -lopencv_core -lopencv_imgproc -lopencv_highgui
    # 链接为可执行文件
    $(TARGET):$(OBJS)
        $(CC) -o $@ $^ $(DLIBS)  
    clean:
        rm -rf $(TARGET) $(OBJS)
    # 编译规则 $@代表目标文件 $< 代表第一个依赖文件
    %.o:%.cpp
        $(CC) -o $@ -c $<

make，产生了两个文件：test文件和test.o文件 ，并测试：

./test lena.bmp

注：程序运行的过程中，常见错误error while loading shared libraries: libopencv\_highgui.so.2.4: cannot open，解决方法：

1.用gedit打开/etc/ld.so.conf，注意要用sudo打开获得权限，不然无法修改，   
 如：sudo gedit /etc/ld.so.conf，在文件中加上一行 /usr/loacal/lib，/user/loacal是opencv安装路径 就是makefile中指定的安装路径   
 加了之后的变为

![1507862-20181024104345776-1926064732.png][]

2.再运行sudo ldconfig,   
 修改bash.bashrc文件，sudo gedit /etc/bash.bashrc   
 在文件末尾加入：   
 PKG\_CONFIG\_PATH=$PKG\_CONFIG\_PATH:/usr/local/lib/pkgconfig   
 export PKG\_CONFIG\_PATH   
 加后的图：

![1507862-20181024104414155-1561992070.png][]

source /etc/bash.bashrc

然后就可以正常运行了！

**Python环境配置：**

python下由于ros一般自带cv\_bridge,系统同样自带cv2，处理起来比较简单，当摄像机采出的图像以rostopic发布时，可以用以下代码进行测试：

1 import rospy
     2 from sensor_msgs.msg import Image
     3 import cv2
     4 from cv_bridge import CvBridge, CvBridgeError
     5 
     6 class Image_Receiver:
     7     def __init__(self):
     8         rospy.Subscriber('/camera/rgb/image_color', Image, callback=self.image_rgb_callback, queue_size=1000)
     9         self.cv_bridge = CvBridge()
    10         rospy.spin()
    11 
    12     def image_rgb_callback(self, data):
    13         cv_image = self.cv_bridge.imgmsg_to_cv2(data, "bgr8")
    14         (rows, cols, channnels) = cv_image.shape
    15         if cols > 60 and rows > 60:
    16             cv2.circle(cv_image, (50, 50), 10, 255)
    17         cv2.imshow("Image Window", cv_image)
    18         cv2.waitKey(3)
    19 
    20 if __name__ == '__main__':
    21     rospy.init_node('rgb_image_get_node')
    22     Image_Receiver()

**C++ QT环境配置：**

由于本人开发环境为qt，则需要在qmake执行.pro文件时同时加载ros和opencv2的环境，在.pro文件中添加以下依赖：

# ROS Depends
    INCLUDEPATH += /opt/ros/kinetic/include \
    
    DEPENDPATH += /opt/ros/kinetic/include \
    
    LIBS += -L/opt/ros/kinetic/lib \
            -L/usr/local/lib \
            -lroscpp \
            -lrospack \
            -lpthread \
            -lrosconsole \
            -lrosconsole_log4cxx \
            -lrosconsole_backend_interface \
            -lxmlrpcpp \
            -lroscpp_serialization \
            -lrostime \
            -lcpp_common \
            -lroslib \
            -ltf \
            -lyaml-cpp \
            -lkdl_conversions \
            -lcv_bridge \
            -lboost_system
    
    # OpenCV Depends
    LIBS += -lopencv_core \
            -lopencv_imgproc \
            -lopencv_highgui

编写测试代码如下：

#include <ros/ros.h>
    #include <sensor_msgs/Image.h>
    #include <cv_bridge/cv_bridge.h>
    class Image_Receiver
    {
    public:
        Image_Receiver()
        {
            subsRgbImage = nh.subscribe<sensor_msgs::Image>("/camera/rgb/image_color", 1000, &Image_Receiver::image_rgb_callback, this);
            ros::spin();
        }
        ~Image_Receiver()
        {
    
        }
        void image_rgb_callback(const sensor_msgs::Image::ConstPtr& data)
        {
            cv_bridge::CvImagePtr cv_ptr;
            try{
                cv_ptr = cv_bridge::toCvCopy(data, sensor_msgs::image_encodings::BGR8);
            } catch (cv_bridge::Exception& e) {
                std::cout << e.what() << std::endl;
            }
            receiveFlag = true;
        }
    
    private:
        sensor_msgs::Image::ConstPtr m_data;
        ros::NodeHandle nh;
        ros::Subscriber subsRgbImage;
        bool receiveFlag;
    };
    
    int main(int argc, char** argv)
    {
        ros::init(argc, argv, "image_receive_node");
        Image_Receiver image_receiver_instance;
        return 0;
    }

转载于:https://www.cnblogs.com/Asp1rant/p/9842304.html

[http_opencv.org_downloads.html]: http://jaist.dl.sourceforge.net/project/opencvlibrary/opencv-unix/2.4.9/opencv-2.4.9.zip
[1507862-20181024104345776-1926064732.png]: /images/20211227/4886237033d549c8a37a685b643e1ec4.png
[1507862-20181024104414155-1561992070.png]: /images/20211227/dea3a920e04b43ab9346f4ee58a4b252.png