Open Source Computer Vision Library https://opencv.org/
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#include <opencv2/core/utility.hpp>
#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
using namespace cv;
using namespace std;
Mat img;
int threshval = 100;
static void on_trackbar(int, void*)
{
Mat bw = threshval < 128 ? (img < threshval) : (img > threshval);
Mat labelImage(img.size(), CV_32S);
int nLabels = connectedComponents(bw, labelImage, 8);
std::vector<Vec3b> colors(nLabels);
colors[0] = Vec3b(0, 0, 0);//background
for(int label = 1; label < nLabels; ++label){
colors[label] = Vec3b( (rand()&255), (rand()&255), (rand()&255) );
}
Mat dst(img.size(), CV_8UC3);
for(int r = 0; r < dst.rows; ++r){
for(int c = 0; c < dst.cols; ++c){
int label = labelImage.at<int>(r, c);
Vec3b &pixel = dst.at<Vec3b>(r, c);
pixel = colors[label];
}
}
imshow( "Connected Components", dst );
}
static void help()
{
cout << "\n This program demonstrates connected components and use of the trackbar\n"
"Usage: \n"
" ./connected_components <image(stuff.jpg as default)>\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";
}
const char* keys =
{
"{@image|stuff.jpg|image for converting to a grayscale}"
};
int main( int argc, const char** argv )
{
help();
CommandLineParser parser(argc, argv, keys);
string inputImage = parser.get<string>(0);
img = imread(inputImage.c_str(), 0);
if(img.empty())
{
cout << "Could not read input image file: " << inputImage << endl;
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;
}