aemd.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 <stdlib.h>
#include <assert.h>
#include <limits.h>
#include <float.h>

#include "CvTest.h"

static char* funcs[] =
{
    "cvCalcEMD",
};

static char *test_desc = "Test for EMD on concrete example";


/*////////////////////// emd_test /////////////////////////*/

typedef struct matr_info
{
    float*  x_origin;
    float*  y_origin;
    float*  matr;
    int     rows;
    int     cols;
}
matr_info;

static float matr_dist( float* x, float* y, void* param )
{
    matr_info* mi = (matr_info*)param;
    int i = x - mi->x_origin - 1;
    int j = y - mi->y_origin - 1;
    assert( 0 <= i && i < mi->rows &&
            0 <= j && j < mi->cols );
    return  mi->matr[i*mi->cols + j];
}

static int emd_test( void* arg )
{
    const double success_error_level = 1e-6;
    #define M 10000
    double emd0 = 2460./210;
    static float cost[] = 
    {
        16, 16, 13, 22, 17,
        14, 14, 13, 19, 15,
        19, 19, 20, 23,  M,
        M ,  0,  M,  0,  0
    };
    static float  w1[] = { 50, 60, 50, 50 },
                  w2[] = { 30, 20, 70, 30, 60 };
    matr_info mi;
    float emd;
    arg;

    mi.x_origin = w1;
    mi.y_origin = w2;

    mi.rows = sizeof(w1)/sizeof(w1[0]);
    mi.cols = sizeof(w2)/sizeof(w2[0]);
    mi.matr = cost;

    emd = cvCalcEMD( w1, mi.rows, w2, mi.cols, 0, (CvDisType)-1,
                     matr_dist, 0, &mi );

    return fabs( emd - emd0 )/(emd0 + 1e-5) < success_error_level ?
        trsResult( TRS_OK, "No errors" ) :
        trsResult( TRS_FAIL, "Bad accuracy" );
}

#define EMD_SAMPLE  0

void InitAEMD( void )
{
    /* Registering test functions */
    trsRegArg( funcs[0], test_desc, atsAlgoClass, emd_test, EMD_SAMPLE );

} /* InitAEMD */

/* End of file. */