140 lines
6.8 KiB
C++
140 lines
6.8 KiB
C++
#include "stdafx.h"
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#include "opencv2/imgcodecs.hpp"
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#include "opencv2/highgui.hpp"
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#include "opencv2/imgproc.hpp"
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#include <iostream>
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using namespace std;
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using namespace cv;
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//! [declare]
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/// Global Variables
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bool use_mask;
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Mat img; Mat templ; Mat mask; Mat result;
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const char* image_window = "Source Image";
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const char* result_window = "Result window";
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int match_method;
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int max_Trackbar = 5;
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//! [declare]
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/// Function Headers
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void MatchingMethod(int, void*);
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/**
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* @function main
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*/
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int main(int argc, char** argv)
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{
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/*if (argc < 2)
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{
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cout << "Not enough parameters" << endl;
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cout << "Usage:\n./MatchTemplate_Demo <image_name> " << endl;
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return -1;
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}*/
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//! [load_image]
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/// Load image and template
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img = imread("2.jpg", IMREAD_COLOR);
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templ = imread("temp.jpg", IMREAD_COLOR);
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/*if (argc > 3) {
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use_mask = true;
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mask = imread(argv[3], IMREAD_COLOR);
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}*/
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if (img.empty() || templ.empty() || (use_mask && mask.empty()))
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{
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cout << "Can't read one of the images" << endl;
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return -1;
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}
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//! [load_image]
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//! [create_windows]
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/// Create windows
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namedWindow(image_window, WINDOW_AUTOSIZE);
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namedWindow(result_window, WINDOW_AUTOSIZE);
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//! [create_windows]
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//! [create_trackbar]
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/// Create Trackbar
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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";
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createTrackbar(trackbar_label, image_window, &match_method, max_Trackbar, MatchingMethod);
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//! [create_trackbar]
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MatchingMethod(0, 0);
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//! [wait_key]
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waitKey(0);
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return 0;
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//! [wait_key]
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}
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/**
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* @function MatchingMethod
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* @brief Trackbar callback
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*/
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void MatchingMethod(int, void*)
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{
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//! [copy_source]
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/// Source image to display
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Mat img_display;
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img.copyTo(img_display);
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//! [copy_source]
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//! [create_result_matrix]
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/// Create the result matrix
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int result_cols = img.cols - templ.cols + 1;
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int result_rows = img.rows - templ.rows + 1;
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result.create(result_rows, result_cols, CV_32FC1);
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//! [create_result_matrix]
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//! [match_template]
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/// Do the Matching and Normalize
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bool method_accepts_mask = (TM_SQDIFF == match_method || match_method == TM_CCORR_NORMED);
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if (use_mask && method_accepts_mask)
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{
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matchTemplate(img, templ, result, match_method, mask);
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}
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else
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{
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matchTemplate(img, templ, result, match_method);
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}
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//! [match_template]
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//! [normalize]
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normalize(result, result, 0, 1, NORM_MINMAX, -1, Mat());
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//! [normalize]
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//! [best_match]
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/// Localizing the best match with minMaxLoc
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double minVal; double maxVal; Point minLoc; Point maxLoc;
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Point matchLoc;
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minMaxLoc(result, &minVal, &maxVal, &minLoc, &maxLoc, Mat());
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//! [best_match]
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//! [match_loc]
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/// For SQDIFF and SQDIFF_NORMED, the best matches are lower values. For all the other methods, the higher the better
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if (match_method == TM_SQDIFF || match_method == TM_SQDIFF_NORMED)
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{
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matchLoc = minLoc;
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}
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else
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{
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matchLoc = maxLoc;
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}
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//! [match_loc]
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//! [imshow]
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/// Show me what you got
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rectangle(img_display, matchLoc, Point(matchLoc.x + templ.cols, matchLoc.y + templ.rows), Scalar::all(0), 2, 8, 0);
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rectangle(result, matchLoc, Point(matchLoc.x + templ.cols, matchLoc.y + templ.rows), Scalar::all(0), 2, 8, 0);
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imshow(image_window, img_display);
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imshow(result_window, result);
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//! [imshow]
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return;
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} |