윤곽선 그리기 - DrawContours

drawContours

Draws contours outlines or filled contours.

C++: void drawContours(InputOutputArray image, InputArrayOfArrays contours, int contourIdx, const Scalar& color, int thickness=1, int lineType=8, InputArray hierarchy=noArray(), int maxLevel=INT_MAX, Point offset=Point() )

Python: cv2.drawContours(image, contours, contourIdx, color[, thickness[, lineType[, hierarchy[, maxLevel[, offset]]]]]) → None

C: void cvDrawContours(CvArr* img, CvSeq* contour, CvScalar externalColor, CvScalar holeColor, int maxLevel, int thickness=1, int lineType=8 )

Python: cv.DrawContours(img, contour, external_color, hole_color, max_level, thickness=1, lineType=8, offset=(0, 0)) → None

Parameters:

image – Destination image. contours – All the input contours. Each contour is stored as a point vector. contourIdx – Parameter indicating a contour to draw. If it is negative, all the contours are drawn. color – Color of the contours. thickness – Thickness of lines the contours are drawn with. If it is negative (for example, thickness=CV_FILLED ), the contour interiors are drawn. lineType – Line connectivity. See line() for details. hierarchy – Optional information about hierarchy. It is only needed if you want to draw only some of the contours (see maxLevel ). maxLevel – Maximal level for drawn contours. If it is 0, only the specified contour is drawn. If it is 1, the function draws the contour(s) and all the nested contours. If it is 2, the function draws the contours, all the nested contours, all the nested-to-nested contours, and so on. This parameter is only taken into account when there is hierarchy available. offset – Optional contour shift parameter. Shift all the drawn contours by the specified . contour – Pointer to the first contour. externalColor – Color of external contours. holeColor – Color of internal contours (holes).

The function draws contour outlines in the image if  or fills the area bounded by the contours if . The example below shows how to retrieve connected components from the binary image and label them:

#include "cv.h"
#include "highgui.h"

using namespace cv;

int main( int argc, char** argv )
{
    Mat src;
    // the first command-line parameter must be a filename of the binary
    // (black-n-white) image
    if( argc != 2 || !(src=imread(argv[1], 0)).data)
        return -1;

    Mat dst = Mat::zeros(src.rows, src.cols, CV_8UC3);

    src = src > 1;
    namedWindow( "Source", 1 );
    imshow( "Source", src );

    vector<vector<Point> > contours;
    vector<Vec4i> hierarchy;

    findContours( src, contours, hierarchy,
        CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE );

    // 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 );
    }

    namedWindow( "Components", 1 );
    imshow( "Components", dst );
    waitKey(0);
}

Note

• An example using the drawContour functionality can be found at opencv_source_code/samples/cpp/contours2.cpp
• An example using drawContours to clean up a background segmentation result at opencv_source_code/samples/cpp/segment_objects.cpp
• (Python) An example using the drawContour functionality can be found at opencv_source/samples/python2/contours.py