1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
/**
* @file MatchTemplate_Demo.cpp
* @brief Sample code to use the function MatchTemplate
* @author OpenCV team
*/
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
using namespace std;
using namespace cv;
//! [declare]
/// Global Variables
bool use_mask;
Mat img; Mat templ; Mat mask; Mat result;
const char* image_window = "Source Image";
const char* result_window = "Result window";
int match_method;
int max_Trackbar = 5;
//! [declare]
/// Function Headers
void MatchingMethod( int, void* );
/**
* @function main
*/
int main( int argc, char** argv )
{
if (argc < 3)
{
cout << "Not enough parameters" << endl;
cout << "Usage:\n./MatchTemplate_Demo <image_name> <template_name> [<mask_name>]" << endl;
return -1;
}
//! [load_image]
/// Load image and template
img = imread( argv[1], IMREAD_COLOR );
templ = imread( argv[2], IMREAD_COLOR );
if(argc > 3) {
use_mask = true;
mask = imread( argv[3], IMREAD_COLOR );
}
if(img.empty() || templ.empty() || (use_mask && mask.empty()))
{
cout << "Can't read one of the images" << endl;
return -1;
}
//! [load_image]
//! [create_windows]
/// Create windows
namedWindow( image_window, WINDOW_AUTOSIZE );
namedWindow( result_window, WINDOW_AUTOSIZE );
//! [create_windows]
//! [create_trackbar]
/// 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 );
//! [create_trackbar]
MatchingMethod( 0, 0 );
//! [wait_key]
waitKey(0);
return 0;
//! [wait_key]
}
/**
* @function MatchingMethod
* @brief Trackbar callback
*/
void MatchingMethod( int, void* )
{
//! [copy_source]
/// Source image to display
Mat img_display;
img.copyTo( img_display );
//! [copy_source]
//! [create_result_matrix]
/// Create the result matrix
int result_cols = img.cols - templ.cols + 1;
int result_rows = img.rows - templ.rows + 1;
result.create( result_rows, result_cols, CV_32FC1 );
//! [create_result_matrix]
//! [match_template]
/// Do the Matching and Normalize
bool method_accepts_mask = (CV_TM_SQDIFF == match_method || match_method == CV_TM_CCORR_NORMED);
if (use_mask && method_accepts_mask)
{ matchTemplate( img, templ, result, match_method, mask); }
else
{ matchTemplate( img, templ, result, match_method); }
//! [match_template]
//! [normalize]
normalize( result, result, 0, 1, NORM_MINMAX, -1, Mat() );
//! [normalize]
//! [best_match]
/// Localizing the best match with minMaxLoc
double minVal; double maxVal; Point minLoc; Point maxLoc;
Point matchLoc;
minMaxLoc( result, &minVal, &maxVal, &minLoc, &maxLoc, Mat() );
//! [best_match]
//! [match_loc]
/// 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; }
//! [match_loc]
//! [imshow]
/// 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 );
//! [imshow]
return;
}