ameanshift.cpp

微软的基于HMM的人脸识别原代码, 非常经典的说

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#include "CvTest.h"

#define Pi 3.14159265358979f

/* Testing parameters */
static char* FuncName = "cvMeanShift8uC1R";

static char TestName[]    = "Calculating MeanShift";
static char TestClass[]   = "Algorithm";

static int height;
static int width;
static int Lenght;
static int Width;
static int iter;
static float epsilon;
static int steps;

#define ATS_8U  0
#define ATS_8S  1
#define ATS_32F 2

#define EPS_8U      (ATS_8U << 4) | CV_TERMCRIT_EPS
#define ITER_8U     (ATS_8U << 4) | CV_TERMCRIT_ITER
#define EPS_ITER_8U (ATS_8U << 4) | CV_TERMCRIT_EPS | CV_TERMCRIT_EPS

#define EPS_8S      (ATS_8S << 4) | CV_TERMCRIT_EPS
#define ITER_8S     (ATS_8S << 4) | CV_TERMCRIT_ITER
#define EPS_ITER_8S (ATS_8S << 4) | CV_TERMCRIT_EPS | CV_TERMCRIT_EPS

#define EPS_32F      (ATS_32F << 4) | CV_TERMCRIT_EPS
#define ITER_32F     (ATS_32F << 4) | CV_TERMCRIT_ITER
#define EPS_ITER_32F (ATS_32F << 4) | CV_TERMCRIT_EPS | CV_TERMCRIT_EPS

static int foaMeanShiftC1R( void* prm )
{
    /* Some variables */
    long       lParam  = (long)prm;
    int        Flvr = (lParam >> 4) & 0xf;
    int        depth = (Flvr == ATS_8U ? IPL_DEPTH_8U : 
                        Flvr == ATS_8S ? IPL_DEPTH_8S : IPL_DEPTH_32F);
    int        Type = lParam & 0xf;
    int        Errors = 0;

    CvTermCriteria criteria;
    CvRect     Window;
    CvSize     roi;

    IplImage*  src;

    float      alpha = 0;
    int        i;
    int        x, y;

    float      destArea = 0;
    int        destIters = 0;

    static int  read_param = 0;

    /* Initialization global parameters */
    if( !read_param )
    {
        read_param = 1;
        trsiRead( &height, "512", "source array lenght" );
        trsiRead( &width, "512", "source array width" );
        trsiRead( &Lenght, "68", "oval lenght" );
        trsiRead( &Width, "15", "oval width" );
        trsiRead( &iter, "10", "iterations" );
        trsiRead( &steps, "10", "steps" );
        trssRead( &epsilon, "1", "epsilon" );
    }

    /* Initilization */
    Window.x = width / 4;
    Window.y = height / 4;
    Window.width = width / 2;
    Window.height = height / 2;

    roi.width = width;
    roi.height = height;

    criteria.type = Type;
    criteria.epsilon = epsilon;
    criteria.maxIter = iter;

    /* Allocating source arrays; */
    src = cvCreateImage(roi, depth, 1);
    assert(src);

    for( alpha = -Pi / 2; alpha < Pi / 2; alpha += Pi / steps )
    {
        x = (int)(width  / 2 + width / 8 * cos(alpha));
        y = (int)(height / 2 + height / 8 * sin(alpha));

        switch( Flvr )
        {
        case ATS_8U:
            atsbInitEllipse( (uchar*)src->imageData,
                             roi.width,
                             roi.height,
                             src->widthStep,
                             x,
                             y,
                             Lenght,
                             Width,
                             alpha,
                             10 );
            break;
        case ATS_8S:
            atsbInitEllipse( (uchar*)src->imageData,
                             roi.width,
                             roi.height,
                             src->widthStep,
                             x,
                             y,
                             Lenght,
                             Width,
                             alpha,
                             10 );
            break;
        case ATS_32F:
            atsfInitEllipse( (float*)src->imageData,
                             roi.width,
                             roi.height,
                             src->widthStep,
                             x,
                             y,
                             Lenght,
                             Width,
                             alpha,
                             10 );
            break;
        } /* switch( Flvr ) */

        for( i = 0; i < steps; i++ )
        {
            CvConnectedComp comp;
            destIters = cvMeanShift( src, Window, criteria, &comp );
            Window = comp.rect;
            destArea = (float) comp.area;
        }
        
        /* Checking results */
        /* Checking x-centers */
        if( fabs( x - (Window.x + Window.width / 2) ) > epsilon )
        {
            Errors++;
            trsWrite( ATS_LST,
                      "x-center: act: %d,  exp: %d\n",
                      Window.x + Window.width / 2,
                      x );
        }
        /* Checking lenght */
        /* Checking x-centers */
        if( fabs( y - (Window.y + Window.height / 2) ) > epsilon )
        {
            Errors++;
            trsWrite( ATS_LST,
                      "y-center: act: %d,  exp: %d\n",
                      Window.y + Window.height / 2,
                      y );
        }
    }

    cvReleaseImage(&src);

    return Errors == 0 ? TRS_OK : trsResult( TRS_FAIL, "Fixed %d errors", Errors );

} /* foaCamShiftC1R */


void InitAMeanShift()
{
    trsRegArg( FuncName, TestName, TestClass, foaMeanShiftC1R, EPS_8U );
    trsRegArg( FuncName, TestName, TestClass, foaMeanShiftC1R, ITER_8U );
    trsRegArg( FuncName, TestName, TestClass, foaMeanShiftC1R, EPS_ITER_8U );

    trsRegArg( FuncName, TestName, TestClass, foaMeanShiftC1R, EPS_8S );
    trsRegArg( FuncName, TestName, TestClass, foaMeanShiftC1R, ITER_8S );
    trsRegArg( FuncName, TestName, TestClass, foaMeanShiftC1R, EPS_ITER_8S );

    trsRegArg( FuncName, TestName, TestClass, foaMeanShiftC1R, EPS_32F );
    trsRegArg( FuncName, TestName, TestClass, foaMeanShiftC1R, ITER_32F );
    trsRegArg( FuncName, TestName, TestClass, foaMeanShiftC1R, EPS_ITER_32F );
} /* InitAMeanShiftC1R */


/* End of file. */