ROS_OpenCV2_MatchTemplate模板匹配

给一张图片，在视野中找到。获取物体的二维坐标。语音相关的话题注释掉了。

//给一个物体，在视野中查找
#include <ros/ros.h>  
#include <image_transport/image_transport.h>  
#include <cv_bridge/cv_bridge.h>  
#include <sensor_msgs/image_encodings.h>  
#include <opencv2/imgproc/imgproc.hpp>  
    #include <opencv2/core/core.hpp>        
        
    #include <opencv2/opencv.hpp>      
   
    #include <iostream>      
    #include<string>      
    #include <sstream>    
#include <opencv2/highgui/highgui.hpp>  
#include "opencv2/video/tracking.hpp"  
#include <geometry_msgs/Twist.h>  
#include <std_msgs/Float32.h>  
#include <std_msgs/UInt8.h>  

using namespace cv;  
using namespace std;  

//Store all constants for image encodings in the enc namespace to be used later.  
namespace enc = sensor_msgs::image_encodings;  

stringstream sss;      
static string ImgInfo="/home/hsn/catkin_ws/src/rosopencv/1.jpg";//如果用语音把1.jpg去掉
void MTemplate(Mat src);
/////////////////////////////////////////////////////从语音获取图像的名字。
/*void imgInfoCallback(const std_msgs::String::ConstPtr & msg)  
{  
	ROS_INFO("From SPEECH, I heard: [%s]",msg->data.c_str());  
	sss.clear();      
	sss<<ImgInfo;      
	sss<<msg->data.c_str();      
	sss<<".jpg";      
	sss>>ImgInfo;  
 
} */
//This function is called everytime a new image is published  
void imageCallback(const sensor_msgs::ImageConstPtr& original_image)  
{  
	//Convert from the ROS image message to a CvImage suitable for working with OpenCV for processing  
	cv_bridge::CvImagePtr cv_ptr;  
	try  
	{  
	    //Always copy, returning a mutable CvImage  
	    //OpenCV expects color images to use BGR channel order.  
	    cv_ptr = cv_bridge::toCvCopy(original_image, enc::BGR8);  
	}  
	catch (cv_bridge::Exception& e)  
	{  
	    //if there is an error during conversion, display it  
	    ROS_ERROR("tutorialROSOpenCV::main.cpp::cv_bridge exception: %s", e.what());  
	    return;  
	}  
	MTemplate(cv_ptr->image);  
}  

void MTemplate(Mat src)
{
    Mat templ;    
    Mat result;  
    int match_method=0;  
    templ=imread(ImgInfo,1); 
        int result_cols =  src.cols - templ.cols + 1;  
        int result_rows = src.rows - templ.rows + 1;  
  
        result.create( result_cols, result_rows, CV_32FC1 );  
  
        matchTemplate( src, templ, result, match_method );  
        normalize( result, result, 0, 1, NORM_MINMAX, -1, Mat() );  
  
        /// 通过函数 minMaxLoc 定位最匹配的位置  
        double minVal; double maxVal; Point minLoc; Point maxLoc;  
        Point matchLoc;  
  
        minMaxLoc( result, &minVal, &maxVal, &minLoc, &maxLoc, Mat() );  
  
        /// 对于方法 SQDIFF 和 SQDIFF_NORMED, 越小的数值代表更高的匹配结果. 而对于其他方法, 数值越大匹配越好  
        if( match_method  == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED )  
        { 
            matchLoc = minLoc; 
        }  
        else  
        {
           matchLoc = maxLoc; 
        }  
  
        /// 最终结果  
        rectangle( src, matchLoc, Point( matchLoc.x + templ.cols , matchLoc.y + templ.rows ), Scalar::all(0), 2, 8, 0 );  
        rectangle( result, matchLoc, Point( matchLoc.x + templ.cols , matchLoc.y + templ.rows ), Scalar::all(0), 2, 8, 0 );  
        cout<<"目标的中心坐标 ( "<<matchLoc.x + templ.cols/2<<" , ("<<matchLoc.y + templ.rows<<" )"<<endl;  
        imshow("当前视频",src); 
        imshow("视频",result); 
         waitKey(1);
}

/** 
* This is ROS node to track the destination image 
*/  
int main(int argc, char **argv)  
{  

ros::init(argc, argv, "image_processor");  
ROS_INFO("-----------------");  

ros::NodeHandle nh;  
//Create an ImageTransport instance, initializing it with our NodeHandle.  
image_transport::ImageTransport it(nh);  

//OpenCV HighGUI call to create a display window on start-up.  

namedWindow( "CamShift Demo", 0 );  


image_transport::Subscriber sub = it.subscribe("camera/rgb/image_raw", 1, imageCallback);
///////////////////////////////////////////////////////////////////////////////
//ros::Subscriber imgInfo         = nh.subscribe("final_recognizer_begin", 1, imgInfoCallback);//接收来自语音部分的话题  
 
destroyWindow("CamShift Demo");  


/** 
* In this application all user callbacks will be called from within the ros::spin() call. 
* ros::spin() will not return until the node has been shutdown, either through a call 
* to ros::shutdown() or a Ctrl-C. 
*/  
ros::spin();  

//ROS_INFO is the replacement for printf/cout.  
ROS_INFO("tutorialROSOpenCV::main.cpp::No error.");  
}