ROS学习笔记（二）：利用opencv将本地图片转换成ROS格式

本文主要讲解如何将本地的图片通过ROS来显示出来。主要利用了opencv库，一样是来源于ROS官网.

创建一个ROS工作区

工作区还是存放和编译我们的文件

$ mkdir -p ~/image_transport_ws/src
$ cd ~/image_transport_ws
$ catkin_make
$ source devel/setup.bash

接下来创建工程包

ROS官方有提供转换图片Demo，直接下载使用。

$ cd ~/image_transport_ws/
$ git clone https://github.com/ros-perception/image_common.git
$ mkdir src

将image_common包中的tutorial复制到src目录下,命名为image_transport_tutorial。

$ cp -r `pwd`/image_common/image_transport/tutorial/ ./src/image_transport_tutorial

其中主要就是 my_publisher.cpp和my_subscriber.cpp这两个文件。my_publisher.cpp文件内容如下：

#include <ros/ros.h>
#include <image_transport/image_transport.h>
#include <opencv2/highgui/highgui.hpp>
#include <cv_bridge/cv_bridge.h>

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(argv[1], CV_LOAD_IMAGE_COLOR);
  cv:WaitKey(30);
  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();
  }
}

my_subscriber.cpp文件内容如下：

#include <ros/ros.h>
#include <image_transport/image_transport.h>
#include <opencv2/highgui/highgui.hpp>
#include <cv_bridge/cv_bridge.h>

void imageCallback(const sensor_msgs::ImageConstPtr& msg)
{
  try
  {
    cv::imshow("view", cv_bridge::toCvShare(msg, "bgr8")->image);
  }
  catch (cv_bridge::Exception& e)
  {
    ROS_ERROR("Could not convert from '%s' to 'bgr8'.", msg->encoding.c_str());
  }
}

int main(int argc, char **argv)
{
  ros::init(argc, argv, "image_listener");
  ros::NodeHandle nh;
  cv::namedWindow("view");
  cv::startWindowThread();
  image_transport::ImageTransport it(nh);
  image_transport::Subscriber sub = it.subscribe("camera/image", 1, imageCallback);
  ros::spin();
  cv::destroyWindow("view");
}

接下来开始编译工程包

$ cd ~/image_transport_ws
$ catkin_make

编译完成之后我们来测试一下功能是否正确

首先启动ROS

$ roscore

现在我们启动叫my_publisher的发布节点，最后一个参数是本地图片的路径。

$ rosrun image_transport_tutorial my_publisher path/to/some/image.jpg

想知道我们启动的节点是否正确，我们可以查看发布的主题(topics):

$ rostopic list -v

看话题中是否有 /camera/image

Published topics:
 * /rosout [roslib/Log] 1 publisher
 * /camera/image [sensor_msgs/Image] 1 publisher
 * /rosout_agg [roslib/Log] 1 publisher

Subscribed topics:
 * /rosout [roslib/Log] 1 subscriber

现在可以运行一个叫 my_subscriber的订阅节点：

rosrun image_transport_tutorial my_subscriber

这时候会看到弹出一个窗口，里面就是我们要发布的图片