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Open Source Computer Vision Library
https://opencv.org/
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73 lines
2.0 KiB
73 lines
2.0 KiB
#include "opencv2/imgproc/imgproc.hpp" |
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#include "opencv2/highgui/highgui.hpp" |
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#include <iostream> |
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using namespace cv; |
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using namespace std; |
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Mat img; |
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int threshval = 100; |
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static void on_trackbar(int, void*) |
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{ |
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Mat bw = threshval < 128 ? (img < threshval) : (img > threshval); |
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vector<vector<Point> > contours; |
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vector<Vec4i> hierarchy; |
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findContours( bw, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE ); |
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Mat dst = Mat::zeros(img.size(), CV_8UC3); |
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if( !contours.empty() && !hierarchy.empty() ) |
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{ |
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// iterate through all the top-level contours, |
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// draw each connected component with its own random color |
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int idx = 0; |
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for( ; idx >= 0; idx = hierarchy[idx][0] ) |
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{ |
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Scalar color( (rand()&255), (rand()&255), (rand()&255) ); |
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drawContours( dst, contours, idx, color, CV_FILLED, 8, hierarchy ); |
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} |
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} |
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imshow( "Connected Components", dst ); |
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} |
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static void help() |
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{ |
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cout << "\n This program demonstrates connected components and use of the trackbar\n" |
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"Usage: \n" |
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" ./connected_components <image(stuff.jpg as default)>\n" |
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"The image is converted to grayscale and displayed, another image has a trackbar\n" |
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"that controls thresholding and thereby the extracted contours which are drawn in color\n"; |
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} |
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const char* keys = |
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{ |
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"{@image |stuff.jpg|image for converting to a grayscale}" |
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}; |
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int main( int argc, const char** argv ) |
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{ |
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help(); |
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CommandLineParser parser(argc, argv, keys); |
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string inputImage = parser.get<string>(1); |
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img = imread(inputImage.c_str(), 0); |
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if(img.empty()) |
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{ |
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cout << "Could not read input image file: " << inputImage << endl; |
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return -1; |
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} |
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namedWindow( "Image", 1 ); |
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imshow( "Image", img ); |
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namedWindow( "Connected Components", 1 ); |
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createTrackbar( "Threshold", "Connected Components", &threshval, 255, on_trackbar ); |
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on_trackbar(threshval, 0); |
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waitKey(0); |
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return 0; |
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}
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