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Open Source Computer Vision
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lsd_lines.cpp

An example using the LineSegmentDetector

building_lsd.png
Sample output image
#include <iostream>
using namespace std;
using namespace cv;
int main(int argc, char** argv)
{
cv::CommandLineParser parser(argc, argv,
"{input i|../data/building.jpg|input image}"
"{refine r|false|if true use LSD_REFINE_STD method, if false use LSD_REFINE_NONE method}"
"{canny c|false|use Canny edge detector}"
"{overlay o|false|show result on input image}"
"{help h|false|show help message}");
if (parser.get<bool>("help"))
{
parser.printMessage();
return 0;
}
parser.printMessage();
String filename = parser.get<String>("input");
bool useRefine = parser.get<bool>("refine");
bool useCanny = parser.get<bool>("canny");
bool overlay = parser.get<bool>("overlay");
Mat image = imread(filename, IMREAD_GRAYSCALE);
if( image.empty() )
{
cout << "Unable to load " << filename;
return 1;
}
imshow("Source Image", image);
if (useCanny)
{
Canny(image, image, 50, 200, 3); // Apply Canny edge detector
}
// Create and LSD detector with standard or no refinement.
double start = double(getTickCount());
vector<Vec4f> lines_std;
// Detect the lines
ls->detect(image, lines_std);
double duration_ms = (double(getTickCount()) - start) * 1000 / getTickFrequency();
std::cout << "It took " << duration_ms << " ms." << std::endl;
// Show found lines
if (!overlay || useCanny)
{
image = Scalar(0, 0, 0);
}
ls->drawSegments(image, lines_std);
String window_name = useRefine ? "Result - standard refinement" : "Result - no refinement";
window_name += useCanny ? " - Canny edge detector used" : "";
imshow(window_name, image);
return 0;
}