i have to build up face detection system for human identification. if correct human present the door will open.like that. um using opencv and c++ for that.um using template matching alogo for that. no i want know what is the images matching percentage. how do it? any way is there have enchanted system for human face identification? thank you
below is my current code:
What I have tried:
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
using namespace std;
using namespace cv;
Mat img; Mat templ; Mat result;
char* image_window = "Source Image";
char* result_window = "Result window";
int match_method;
int max_Trackbar = 5;
void MatchingMethod(int, void*);
int main(int argc, char** argv)
{
img = imread("IMG_20160214_092738.jpg", 1);
cv::resize(img, img, cv::Size(), 0.35, 0.3);
templ = imread("IMG_20160131_120252.jpg", 1);
cv::resize(templ, templ, cv::Size(), 0.25, 0.25);
namedWindow(image_window, CV_WINDOW_AUTOSIZE);
namedWindow(result_window, CV_WINDOW_AUTOSIZE);
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;
}
void MatchingMethod(int, void*)
{
Mat img_display;
img.copyTo(img_display);
int result_cols = img.cols - templ.cols + 1;
int result_rows = img.rows - templ.rows + 1;
result.create(result_rows, result_cols, CV_32FC1);
matchTemplate(img, templ, result, match_method);
normalize(result, result, 0, 1, NORM_MINMAX, -1, Mat());
double minVal; double maxVal; Point minLoc; Point maxLoc;
Point matchLoc;
minMaxLoc(result, &minVal, &maxVal, &minLoc, &maxLoc, Mat());
cout << minVal << "***" << maxVal << endl;
if (match_method == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED)
{
matchLoc = minLoc;
}
else
{
matchLoc = maxLoc;
}
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;
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