Open Source Computer Vision Library https://opencv.org/
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#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
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#include <iostream>
using namespace cv;
using namespace std;
Mat img;
int threshval = 100;
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void help()
{
cout <<
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"\n This program demonstrates connected components and use of the trackbar\n"
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<< "\n"
<< "Usage: ./connected_components <image>\n"
<< "\n"
<< "The image is converted to grayscale and displayed, another image has a trackbar\n"
<< "that controls thresholding and thereby the extracted contours which are drawn in color\n"
<< endl;
}
void on_trackbar(int, void*)
{
Mat bw = threshval < 128 ? (img < threshval) : (img > threshval);
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
findContours( bw, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );
Mat dst = Mat::zeros(img.size(), CV_8UC3);
if( contours.size() > 0 )
{
// iterate through all the top-level contours,
// draw each connected component with its own random color
int idx = 0;
for( ; idx >= 0; idx = hierarchy[idx][0] )
{
Scalar color( (rand()&255), (rand()&255), (rand()&255) );
drawContours( dst, contours, idx, color, CV_FILLED, 8, hierarchy );
}
}
imshow( "Connected Components", dst );
}
int main( int argc, char** argv )
{
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// the first command line parameter
if(argc != 2)
{
help();
return -1;
}
if( !(img=imread(argc == 2 ? argv[1] : "stuff.jpg", 0)).data) //The ending 0 in imread converts the image to grayscale.
return -1;
namedWindow( "Image", 1 );
imshow( "Image", img );
namedWindow( "Connected Components", 1 );
createTrackbar( "Threshold", "Connected Components", &threshval, 255, on_trackbar );
on_trackbar(threshval, 0);
waitKey(0);
return 0;
}