ROS之service传输图片

之前一直用Topic来进行图片的传输，近期由于项目需要，需要用service进行图片的传输，查了不少博客很少有详细的解释，故写博客记录一下方便后续查询，也为了帮助大家。

topic和service对于图片的传输格式是一样的，只不过两者的通信方式不一样。

在此只介绍源码的编写，对于如何创建service工作空间，如何编译在我的上一篇博客中有详细的介绍。

srv文件

img.srv

sensor_msgs/Image image    // 图像转换到sensor_msgs/Image格式进行传输
---
string a
string b

C++版本

ros和opencv之间图片如何传输详见：Converting between ROS images and OpenCV images (C++)

客户端程序

client_img.cpp

#include 
#include 
#include 
#include "learn_service/img.h"

int main(int argc, char** argv)
{
	ros::init(argc, argv, "client_img");
	ros::NodeHandle node;

    // 发现/cam服务后，创建一个服务客户端，连接名为/service_img的service
	ros::service::waitForService("/cam");
	ros::ServiceClient img_client = node.serviceClient<learn_service::img>("/cam");

	//读取图片
	cv::Mat image = cv::imread("../data/6.png");
	sensor_msgs::ImagePtr image_srv = cv_bridge::CvImage(std_msgs::Header(), "bgr8", image).toImageMsg();  //图片转换成消息格式进行传输

    // 初始化learn_service::img的请求数据
	learn_service::img srv;

	srv.request.image = *image_srv;

    // 请求服务调用
	img_client .call(srv);

	// TO-DO: 处理服务调用结果

	return 0;
};

服务端程序

server_img.cpp

#include 
#include "learn_service/img.h"
#include 
#include 
#include 

// service回调函数，输入参数req，输出参数res
bool cam_result_callback(learn_service::img::Request  &req,
         		 learn_service::img::Response &res)
{

    cv_bridge::CvImagePtr cv_ptr;
    //图像有消息格式转换成Mat格式
	cv_ptr = cv_bridge::toCvCopy(req.image, sensor_msgs::image_encodings::BGR8);
	cv::imshow("view", cv_ptr->image);
	cv::waitKey(0);

    return true;
}

int main(int argc, char **argv)
{
    ros::init(argc, argv, "server_img");
    ros::NodeHandle node;

    // 创建一个名为/cam的server，注册回调函数cam_result_callback
    ros::ServiceServer img_service = node.advertiseService("/cam", cam_result_callback);

    // 循环等待回调函数
    ros::spin();

    return 0;
}

python版本

ros和opencv之间图片如何传输详见：Converting between ROS images and OpenCV images (Python)

客户端程序

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import sys
import rospy
import cv2
from cv_bridge import CvBridge
from sensor_msgs.msg import Image
from learn_service.srv import img, imgRequest

def Img_client():
    # ROS节点初始化
    rospy.init_node('client_img')    
    # 发现/img服务后，创建一个服务客户端，连接名为/img的service
    rospy.wait_for_service('/img')
    bridge = CvBridge()
    #读取图片
    image = cv2.imread('/home/ubuntu/ros_practice/src/learn_service/data/6.png')
    #转换图片为消息格式
    image_message = bridge.cv2_to_imgmsg(image, "bgr8")

    # try:
    img_client = rospy.ServiceProxy('/img', img)
    # 请求服务调用，输入请求数据
    response = img_client(image_message)
    return response.a
	
    # except rospy.ServiceException, e:
    #     print "Service call failed: %s"%e

if __name__ == "__main__":
	#服务调用并显示调用结果
    Img_client()

服务端程序

#!/usr/bin/env python3
# -*- coding: utf-8 -*-


import rospy
import cv2
from learn_service.srv import img, imgResponse
from cv_bridge import CvBridge
from sensor_msgs.msg import Image

def ImgCallback(req):
    bridge = CvBridge()
    cv_image = bridge.imgmsg_to_cv2(req.image, "bgr8")
    cv2.imshow("view", cv_image)
    cv2.waitKey(0)
	# 反馈数据
    #return imgResponse("OK1", "OK2")

def img_server():
	# ROS节点初始化
    rospy.init_node('server_img')

	# 创建一个名为/show_person的server，注册回调函数personCallback
    s = rospy.Service('/img', img, ImgCallback)

	# 循环等待回调函数
    print("Ready to show img informtion")
    rospy.spin()

if __name__ == "__main__":
    img_server()