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visual-c++ - 使用单个模板匹配多个对象

转载 作者:太空宇宙 更新时间:2023-11-03 21:22:40 25 4
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如何使用单个模板匹配多个对象?我正在尝试使用树的中心作为模板来匹配多棵香蕉树。我的程序只匹配一次,我希望匹配航拍图像中香蕉树的所有出现。`

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>

using namespace std;
using namespace cv;

/// Global Variables
Mat img; Mat templ; Mat result;
const char* image_window = "Source Image";
const char* result_window = "Result window";

int match_method;
int max_Trackbar = 5;

/// Function Headers
void MatchingMethod( int, void* );

/**
* @function main
*/
int main( int, char** argv )
{
/// Load image and template
img = imread( argv[1], 1 );
templ = imread( argv[2], 1 );

/// Create windows
namedWindow( image_window, WINDOW_AUTOSIZE );
namedWindow( result_window, WINDOW_AUTOSIZE );

/// Create Trackbar
const char* trackbar_label = "Method: \n 0: SQDIFF \n 1: SQDIFF NORMED \n 2: TM CCORR \n 3: TM CCORR NORMED \n 4: TM COEFF \n 5: TM COEFF NORMED";
createTrackbar( trackbar_label, image_window, &match_method, max_Trackbar, MatchingMethod );

MatchingMethod( 0, 0 );

waitKey(0);
return 0;
}

/**
* @function MatchingMethod
* @brief Trackbar callback
*/
void MatchingMethod( int, void* )
{
/// Source image to display
Mat img_display;
img.copyTo( img_display );

/// Create the result matrix
int result_cols = img.cols - templ.cols + 1;
int result_rows = img.rows - templ.rows + 1;

result.create( result_cols, result_rows, CV_32FC1 );

/// Do the Matching and Normalize
matchTemplate( img, templ, result, match_method );
normalize( result, result, 0, 1, NORM_MINMAX, -1, Mat() );

/// Localizing the best match with minMaxLoc
double minVal; double maxVal; Point minLoc; Point maxLoc;
Point matchLoc;

minMaxLoc( result, &minVal, &maxVal, &minLoc, &maxLoc, Mat() );


/// For SQDIFF and SQDIFF_NORMED, the best matches are lower values. For all the other methods, the higher the better
if( match_method == TM_SQDIFF || match_method == TM_SQDIFF_NORMED )
{ matchLoc = minLoc; }
else
{ matchLoc = maxLoc; }

/// Show me what you got
rectangle( img_display, 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 );

imshow( image_window, img_display );
imshow( result_window, result );

return;
}

`

最佳答案

在 Saikat(和 Bartlett)的代码中使用如下行

result.at<float>(minLoc.x,minLoc.y)=1.0;

和类似的行有下一个缺点:代码屏蔽了唯一的极值像素,然后进行下一个循环可能会找到相同的对象,将一个像素移到一边。我建议用模板大小的矩形来掩盖结果。此代码启用控制相邻物体的重叠程度。

void matchingMethod(Mat& img,  const Mat& templ,  int     match_method)
{
/// Source image to display
Mat img_display; Mat result;
if(img.channels()==3)
cvtColor(img, img, cv::COLOR_BGR2GRAY);
img.copyTo( img_display );//for later show off

/// Create the result matrix - shows template responces
int result_cols = img.cols - templ.cols + 1;
int result_rows = img.rows - templ.rows + 1;
result.create( result_cols, result_rows, CV_32FC1 );

/// Do the Matching and Normalize
matchTemplate( img, templ, result, match_method );
normalize( result, result, 0, 1, NORM_MINMAX, -1, Mat() );

/// Localizing the best match with minMaxLoc
double minVal; double maxVal;
Point minLoc; Point maxLoc;
Point matchLoc;


//in my variant we create general initially positive mask
Mat general_mask=Mat::ones(result.rows,result.cols,CV_8UC1);

for(int k=0;k<5;++k)// look for N=5 objects
{
minMaxLoc( result, &minVal, &maxVal, &minLoc, &maxLoc, general_mask);
//just to visually observe centering I stay this part of code:
result.at<float>(minLoc ) =1.0;//
result.at<float>(maxLoc ) =0.0;//

// For SQDIFF and SQDIFF_NORMED, the best matches are lower values.
//For all the other methods, the higher the better
if( match_method == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED )
matchLoc = minLoc;
else
matchLoc = maxLoc;
//koeffitient to control neiboring:
//k_overlapping=1.- two neiboring selections can overlap half-body of template
//k_overlapping=2.- no overlapping,only border touching possible
//k_overlapping>2.- distancing
//0.< k_overlapping <1.- selections can overlap more then half
float k_overlapping=1.7f;//little overlapping is good for my task

//create template size for masking objects, which have been found,
//to be excluded in the next loop run
int template_w= ceil(k_overlapping*templ.cols);
int template_h= ceil(k_overlapping*templ.rows);
int x=matchLoc.x-template_w/2;
int y=matchLoc.y-template_h/2;

//shrink template-mask size to avoid boundary violation
if(y<0) y=0;
if(x<0) x=0;
//will template come beyond the mask?:if yes-cut off margin;
if(template_w + x > general_mask.cols)
template_w= general_mask.cols-x;
if(template_h + y > general_mask.rows)
template_h= general_mask.rows-y;

//set the negative mask to prevent repeating
Mat template_mask=Mat::zeros(template_h,template_w, CV_8UC1);
template_mask.copyTo(general_mask(cv::Rect(x, y, template_w, template_h)));

/// Show me what you got on main image and on result (
rectangle( img_display,matchLoc , Point( matchLoc.x + templ.cols , matchLoc.y + templ.rows ), Scalar::all(0), 2, 8, 0 );
//small correction here-size of "result" is smaller
rectangle( result,Point(matchLoc.x- templ.cols/2,matchLoc.y- templ.rows/2) , Point( matchLoc.x + templ.cols/2 , matchLoc.y + templ.rows/2 ), Scalar::all(0), 2, 8, 0 );
}//for k= 0--5
}

关于visual-c++ - 使用单个模板匹配多个对象,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/15918495/

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