环境：opencv 3.4.15、 ROS melodic

ros中使用usb相机

首先创建一个工作空间：

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

再建立一个功能包：

$ cd ~/ros_ws/src
$ catkin_create_pkg learning_image_transport roscpp std_msgs cv_bridge image_transport sensor_msgs

然后在功能包learning_image_transport下的src目录中建立两个cpp文件：

$ cd ~/ros_ws/src/learning_image_transport/src/
$ gedit my_publisher.cpp

将下列代码复制进去：

#include <ros/ros.h>
#include <image_transport/image_transport.h>
#include <opencv2/highgui/highgui.hpp>
#include <cv_bridge/cv_bridge.h>
#include <sstream> // for converting the command line parameter to integer  int main(int argc, char** argv)
{  // Check if video source has been passed as a parameter  if(argv[1] == NULL)   {  ROS_INFO("argv[1]=NULL\n");  return 1;  }  ros::init(argc, argv, "image_publisher");  ros::NodeHandle nh;  image_transport::ImageTransport it(nh);  image_transport::Publisher pub = it.advertise("camera/image", 1);  // Convert the passed as command line parameter index for the video device to an integer  std::istringstream video_sourceCmd(argv[1]);  int video_source;  // Check if it is indeed a number  if(!(video_sourceCmd >> video_source))   {  ROS_INFO("video_sourceCmd is %d\n",video_source);  return 1;  }  cv::VideoCapture cap(video_source);  // Check if video device can be opened with the given index  if(!cap.isOpened())   {  ROS_INFO("can not opencv video device\n");  return 1;  }  cv::Mat frame;  sensor_msgs::ImagePtr msg;  ros::Rate loop_rate(5);  while (nh.ok()) {  cap >> frame;  // Check if grabbed frame is actually full with some content  if(!frame.empty()) {  msg = cv_bridge::CvImage(std_msgs::Header(), "bgr8", frame).toImageMsg();  pub.publish(msg);  //cv::Wait(1);  }  }ros::spinOnce();  loop_rate.sleep();
}

保存以后，继续创建my_subscriber.cpp：

$ gedit my_subscriber.cpp

复制下列代码：

#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); // cv::waitKey(30);  }  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");
}

接下来要把涉及到的各种包和opencv在CMakeList中声明一下，回到程序包目录下。

$ cd ~/ros_ws/src/learning_image_transport/
$ gedit CMakeLists.txt

添加以下语句：

find_package(OpenCV REQUIRED)
# add the publisher example
add_executable(my_publisher src/my_publisher.cpp)  target_link_libraries(my_publisher ${catkin_LIBRARIES} ${OpenCV_LIBRARIES})  # add the subscriber example
add_executable(my_subscriber src/my_subscriber.cpp)
target_link_libraries(my_subscriber ${catkin_LIBRARIES} ${OpenCV_LIBRARIES})

将这个包进行编译：

$ cd ~/ros_ws/
$ catkin_make

接下来开始运行程序,首先启动ROS。

$ roscore

运行my_publisher节点.(如果运行不起来,需要先source devel/setup.bash)。

$ rosrun learning_image_transport my_publisher 0

这时候会看到我们的摄像头灯已经亮起来了,0代表默认摄像头,如果有多个摄像头,则第二个是1,依次类推。

接下来运行my_subscriber节点来接收图像。

$ rosrun learning_image_transport my_subscriber

ros订阅图像

ros编写发布/接收图片的结点(Python)

新建py文件 /AGV/src/image_processing/scripts/image_process.py

#!/usr/bin/env python2.7
#coding:utf-8import rospy
import cv2
from sensor_msgs.msg import Image
from cv_bridge import CvBridge,CvBridgeErrordef callback(data):             cv_image=CvBridge().imgmsg_to_cv2(data,"bgr8")cv2.imshow("view",cv_image)cv2.waitKey(1)if __name__ == '__main__':rospy.init_node('image_acquistion')rospy.Subscriber('camera/image', Image, callback)rospy.spin()cv2.destoryAllWindows()

rosrun image_processing image_process.py

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