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写在前面:近期打算做一下视觉算法部署,需用到ROS知识传输视频,以此作为记录
首先需要电脑有ROS和opencv
1、建立新的工作空间
mkdir -p ~/catkin_ws/src
cd ~/catkin_ws/src
# 初始化文件
catkin_init_workspace
# 编译工作空间
cd ~/catkin_ws/
catkin_make
# 设置环境变量,避免每次开终端都要source
echo "source ~/catkin_ws/devel/setup.bash" >> ~/.bashrc
source ~/.bashrc
2、创建新的功能包
# 创建my_image_transport功能包
cd catkin_ws/
cd src/
catkin_create_pkg my_image_transport image_transport cv_bridge
# 重新编译
cd ..
catkin_make
3、发布图片
首先进入my_image_transport
功能包,创建src
文件夹新建my_publisher.cpp
文件,并将下述内容复制进去即可
#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); 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(); } }
即可在camera/image话题上发布图像
同样在src
文件夹新建my_subscriber.cpp
文件,将下述内容复制进去即可
#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"); }
即可
1、在CMakeList.txt添加如下代码
find_package(OpenCV)
include_directories(include ${OpenCV_INCLUDE_DIRS})
message(${OpenCV_INCLUDE_DIRS})
#build my_publisher and my_subscriber
# 注意一定要将${OpenCV_LIBS},即opencv加入链接
add_executable(my_publisher src/my_publisher.cpp)
target_link_libraries(my_publisher ${catkin_LIBRARIES} ${OpenCV_LIBS})
add_executable(my_subscriber src/my_subscriber.cpp)
target_link_libraries(my_subscriber ${catkin_LIBRARIES} ${OpenCV_LIBS})
2、在package.xml添加如下代码
<buildtool_depend>catkin</buildtool_depend> <build_depend>cv_bridge</build_depend> <build_depend>image_transport</build_depend> <build_depend>roscpp</build_depend> <build_depend>rospy</build_depend> <build_depend>std_msgs</build_depend> <build_export_depend>cv_bridge</build_export_depend> <build_export_depend>image_transport</build_export_depend> <build_export_depend>roscpp</build_export_depend> <build_export_depend>rospy</build_export_depend> <build_export_depend>std_msgs</build_export_depend> <exec_depend>cv_bridge</exec_depend> <exec_depend>image_transport</exec_depend> <exec_depend>roscpp</exec_depend> <exec_depend>rospy</exec_depend> <exec_depend>std_msgs</exec_depend>
3、重新编译
cd ~/catkin_ws
catkin_make -DCATKIN_WHITHELIST_PACKAGES="my_image_transport"
出现下图即编译完成
打开roscore
,运行rosrun my_image_transport my_publisher path/Pictures
,path/Pictures
为图片路径,在另一个终端运行rosrun my_image_transport my_subscriber
即可。
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