思路： 
（1）使用opencv读取本地图像 
（2）调用cv_bridge::CvImage（）.toImageMsg()将本地图像发送给rviz显示

 

1.使用opencv读取本地图像并发布图像消息
（1）利用catkin新建一个工程叫rosopencv,并进行初始化

 

mkdir -p rosopencv/src
cd rosopencv/src
catkin_create_pkg rosopencv sensor_msgs cv_bridge roscpp std_msgs image_transport
cd ..
catkin_make
source ./devel/setup.bash

（2）编辑主函数代码

在rosopencv包文件夹src目录下创建rosopencv.cpp

主函数rosopencv.cpp内容如下

 

    #include <ros/ros.h>
    #include <image_transport/image_transport.h>
    #include <opencv2/highgui/highgui.hpp>
    #include <cv_bridge/cv_bridge.h>
     
    #include <stdio.h>
     
    int main(int argc, char** argv)
    {
      ros::init(argc, argv, "image_publisher");
      ros::NodeHandle nh;
      image_transport::ImageTransport it(nh);
      image_transport::Publisher pub = it.advertise("camera/image", 1);
     
      cv::Mat image = cv::imread("~/rosopencv/test.jpg", CV_LOAD_IMAGE_COLOR);
      if(image.empty()){
       printf("open error\n");
       }
      sensor_msgs::ImagePtr msg = cv_bridge::CvImage(std_msgs::Header(), "bgr8", image).toImageMsg();
     
      ros::Rate loop_rate(5);
      while (nh.ok()) {
        pub.publish(msg);
        ros::spinOnce();
        loop_rate.sleep();
      }
    }

 

（3）编辑CmakeLists.txt 

cmake_minimum_required(VERSION 3.0.2)
project(rosopencv)

find_package(catkin REQUIRED COMPONENTS
  cv_bridge
  image_transport
  roscpp
  sensor_msgs
  std_msgs
)

catkin_package(
  INCLUDE_DIRS include
#  LIBRARIES rosopencv
  CATKIN_DEPENDS cv_bridge image_transport roscpp sensor_msgs std_msgs
#  DEPENDS system_lib
)


include_directories(
  include
  ${catkin_INCLUDE_DIRS}
)

add_executable(${PROJECT_NAME}_node src/rosopencv.cpp)


 target_link_libraries(${PROJECT_NAME}_node
   ${catkin_LIBRARIES}
 )

 

2编译和运行

编译

1. cd ~/rosopencv
2. catkin_make

打开一个终端运行 roscore

 

另外一个终端工作空间运行

　source devel/setup.bash　

rosrun rosopencv rosopencv_node 

 

3.在rviz 中显示

rviz

左边点击add 
选中image 
在image的topic选项中选 
/camera/image

即可显示图片