我正在尝试在货架图像中执行模板匹配, 这是我的照片 - 1 -
2 - 我的模板图片 -
#include "stdio.h"
#include "opencv2/highgui/highgui.hpp"
#include "iostream"
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv/cv.h"
using namespace cv;
using namespace std;
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
/**
* Function to perform fast template matching with image pyramid
*/
void fastMatchTemplate(cv::Mat& srca, // The reference image
cv::Mat& srcb, // The template image
cv::Mat& dst, // Template matching result
int maxlevel) // Number of levels
{
std::vector<cv::Mat> refs, tpls, results;
// Build Gaussian pyramid
cv::buildPyramid(srca, refs, maxlevel);
cv::buildPyramid(srcb, tpls, maxlevel);
cv::Mat ref, tpl, res;
// Process each level
for (int level = maxlevel; level >= 0; level--)
{
ref = refs[level];
tpl = tpls[level];
res = cv::Mat::zeros(ref.size() + cv::Size(1,1) - tpl.size(), CV_32FC1);
if (level == maxlevel)
{
// On the smallest level, just perform regular template matching
cv::matchTemplate(ref, tpl, res, CV_TM_CCORR_NORMED);
}
else
{
// On the next layers, template matching is performed on pre-defined
// ROI areas. We define the ROI using the template matching result
// from the previous layer.
cv::Mat mask;
cv::pyrUp(results.back(), mask);
cv::Mat mask8u;
mask.convertTo(mask8u, CV_8U);
// Find matches from previous layer
std::vector<std::vector<cv::Point> > contours;
cv::findContours(mask8u, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
// Use the contours to define region of interest and
// perform template matching on the areas
for (int i = 0; i < contours.size(); i++)
{
cv::Rect r = cv::boundingRect(contours[i]);
cv::matchTemplate(
ref(r + (tpl.size() - cv::Size(1,1))),
tpl,
res(r),
CV_TM_CCORR_NORMED
);
}
}
// Only keep good matches
cv::threshold(res, res, 0.80, 1., CV_THRESH_TOZERO);
results.push_back(res);
}
res.copyTo(dst);
}
int main()
{
/* string path;
string path1;
cout << "Please enter image template: ";
cin >> path;
cout << "Please enter image reference: ";
cin >> path1;*/
cv::Mat ref = cv::imread("E:\\CodeImage\\plan1.png");
cv::Mat tpl = cv::imread("E:\\CodeImage\\t.png");
if (ref.empty() || tpl.empty())
return -1;
cv::Mat ref_gray, tpl_gray;
cv::cvtColor(ref, ref_gray, CV_BGR2GRAY);
cv::cvtColor(tpl, tpl_gray, CV_BGR2GRAY);
cv::Mat dst;
fastMatchTemplate(ref_gray, tpl_gray, dst, 2);
while (true)
{
double minval, maxval;
cv::Point minloc, maxloc;
cv::minMaxLoc(dst, &minval, &maxval, &minloc, &maxloc);
if (maxval >= 0.9)
{
cv::rectangle(
ref, maxloc,
cv::Point(maxloc.x + tpl.cols, maxloc.y + tpl.rows),
CV_RGB(0,255,0), 2
);
cv::floodFill(
dst, maxloc,
cv::Scalar(0), 0,
cv::Scalar(.1),
cv::Scalar(1.)
);
}
else
{
cout << "No match found ";
break;
}
}
cv::imshow("result", ref);
cv::waitKey();
return 0;
getchar();
}
我的结果图片是 -
你可以在结果图像中看到绿色矩形但是应该有2个匹配,它只给出一个。
我如何找到两个图像,因为两者都是相同的。