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OpenCV
4.2.0
Open Source Computer Vision
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An example on K-means clustering
#include <iostream>
using namespace std;
int main( int , char** )
{
const int MAX_CLUSTERS = 5;
{
};
for(;;)
{
int k, clusterCount = rng.
uniform(2, MAX_CLUSTERS+1);
int i, sampleCount = rng.
uniform(1, 1001);
clusterCount =
MIN(clusterCount, sampleCount);
std::vector<Point2f> centers;
for( k = 0; k < clusterCount; k++ )
{
Mat pointChunk = points.
rowRange(k*sampleCount/clusterCount,
k == clusterCount - 1 ? sampleCount :
(k+1)*sampleCount/clusterCount);
}
double compactness =
kmeans(points, clusterCount, labels,
for( i = 0; i < sampleCount; i++ )
{
int clusterIdx = labels.
at<
int>(i);
}
for (i = 0; i < (int)centers.size(); ++i)
{
}
cout << "Compactness: " << compactness << endl;
if( key == 27 || key == 'q' || key == 'Q' )
break;
}
return 0;
}
int uniform(int a, int b)
returns uniformly distributed integer random number from [a,b) range
int rows
the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions
Definition: mat.hpp:2086
static Scalar_< double > all(double v0)
returns a scalar with all elements set to v0
The class defining termination criteria for iterative algorithms.
Definition: types.hpp:852
_Tp & at(int i0=0)
Returns a reference to the specified array element.
Definition: core.hpp:2772
int waitKey(int delay=0)
Waits for a pressed key.
the maximum number of iterations or elements to compute
Definition: types.hpp:860
the desired accuracy or change in parameters at which the iterative algorithm stops
Definition: types.hpp:862
_Tp y
y coordinate of the point
Definition: types.hpp:187
_Tp x
x coordinate of the point
Definition: types.hpp:186
void randShuffle(InputOutputArray dst, double iterFactor=1., RNG *rng=0)
Shuffles the array elements randomly.
int cols
Definition: mat.hpp:2086
#define CV_8UC3
Definition: interface.h:90
Definition: imgproc.hpp:804
#define MIN(a, b)
Definition: cvdef.h:453
#define CV_32FC2
Definition: interface.h:119
double kmeans(InputArray data, int K, InputOutputArray bestLabels, TermCriteria criteria, int attempts, int flags, OutputArray centers=noArray())
Finds centers of clusters and groups input samples around the clusters.
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
Mat rowRange(int startrow, int endrow) const
Creates a matrix header for the specified row span.
Scalar_< double > Scalar
Definition: types.hpp:669
Random Number Generator.
Definition: core.hpp:2768
n-dimensional dense array class
Definition: mat.hpp:791
"black box" representation of the file storage associated with a file on disk.
Definition: affine.hpp:51
void fill(InputOutputArray mat, int distType, InputArray a, InputArray b, bool saturateRange=false)
Fills arrays with random numbers.
antialiased line
Definition: imgproc.hpp:807
void circle(InputOutputArray img, Point center, int radius, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
Draws a circle.