aimagestatistics.cpp

微软的基于HMM的人脸识别原代码, 非常经典的说

                }

                for( c = 1; c <= channels; c++ )
                {
                    double  mean_err0, stddev_err0, err1;
                    double  result[2];

                    roi.coi = c;

                    /* //// ROI version /////// */
                    cvMean_StdDev( img, result+0, result+1 );

                    mean_err0 = rel_err( etalon_result[2*c-2], result[0] );
                    stddev_err0 = rel_err( etalon_result[2*c-1], result[1] );

                    cvMean_StdDevMask( img, mask, result+0, result+1 );
                    err1 = rel_err( etalon_mask_result[2*c-2], result[0] );
                    mean_err0 = MAX( mean_err0, err1 );
                    err1 = rel_err( etalon_mask_result[2*c-1], result[1] );
                    stddev_err0 = MAX( stddev_err0, err1 );

                    if( mean_err0 > max_err )
                    {
                        merr_w    = w;
                        merr_h    = h;
                        merr_iter = i;
                        merr_c    = c;
                        max_err   = mean_err0;
                        if( max_err > success_error_level ) goto test_exit;
                    }
                }
            }
            ATS_INCREASE( w, img_size_delta_type, img_size_delta );
        } /* end of the loop by w */

        ATS_INCREASE( h, img_size_delta_type, img_size_delta );
    }  /* end of the loop by h */

test_exit:

    img->roi = img2->roi = mask->roi = 0;

    iplDeallocate( img, IPL_IMAGE_ALL );
    iplDeallocate( img2, IPL_IMAGE_ALL );
    iplDeallocate( mask, IPL_IMAGE_ALL );
    iplDeallocate( mask2, IPL_IMAGE_ALL );

    //if( code == TRS_OK )
    {
        trsWrite( ATS_LST, "Max err is %g at w = %d, h = %d, "
                           "iter = %d, c = %d, seed = %08x",
                           max_err, merr_w, merr_h, merr_iter, merr_c, seed );

        return max_err <= success_error_level ?
            trsResult( TRS_OK, "No errors" ) :
            trsResult( TRS_FAIL, "Bad accuracy" );
    }
    /*else
    {
        trsWrite( ATS_LST, "Fatal error at w = %d, h = %d, "
                           "iter = %d, c = %d, seed = %08x",
                           w, h, i, c, seed );
        return trsResult( TRS_FAIL, "Function returns error code" );
    }*/
}


/* ///////////////////// min_max_loc_test ///////////////////////// */

static double check_extr_point( IplImage* img, IplImage* mask, CvPoint pt,
                                double etalon_value )
{
    double val = 0;
    int ch, nch;

    if( mask && mask->imageData[pt.y*mask->widthStep + pt.x] == 0 ) return 1e30;

    ch = img->roi->coi;
    ch = ch == 0 ? 0 : ch - 1;
    nch = img->nChannels;

    switch( img->depth )
    {
    case IPL_DEPTH_8U:
        val = ((uchar*)img->imageData)[pt.y*img->widthStep + pt.x*nch + ch];
        break;
    case IPL_DEPTH_8S:
        val = ((char*)img->imageData)[pt.y*img->widthStep + pt.x*nch + ch];
        break;
    case IPL_DEPTH_32F:
        val = ((float*)img->imageData)[pt.y*(img->widthStep/4) + pt.x*nch + ch];
        break;
    default:
        assert(0);
        return 1e30;
    }

    return fabs( etalon_value - val );
}


static int min_max_loc_test( void* arg )
{
    const float success_error_level = 0;

    int   param     = (int)arg;
    int   depth     = param/2;
    int   channels  = (param & 1);

    int   seed     = atsGetSeed();

    /* position where the maximum error occured */
    int   merr_w = 0, merr_h = 0, merr_iter = 0, merr_c = 0;

    /* test parameters */
    int     w = 0, h = 0, i = 0, c = 0;
    double  max_err = 0.;
    int     code = TRS_OK;

    IplROI       roi, mask_roi;
    IplImage    *img, *img2, *mask, *mask2;
    AtsRandState rng_state;

    atsRandInit( &rng_state, 0, 1, seed );

    read_img_stat_params();

    if( !(ATS_RANGE( IMGSTAT_MIN_MAX_LOC, fn_l, fn_h+1 ) &&
          ATS_RANGE( depth, dt_l, dt_h+1 ) &&
          ATS_RANGE( channels, ch_l, ch_h+1 ))) return TRS_UNDEF;

    depth = depth == 2 ? IPL_DEPTH_32F : depth == 1 ? IPL_DEPTH_8S : IPL_DEPTH_8U;
    channels = channels*2 + 1;

    img  = atsCreateImage( max_img_size, max_img_size, depth, channels, 0 );
    img2 = atsCreateImage( max_img_size, max_img_size, IPL_DEPTH_32F, channels, 0 );
    mask = atsCreateImage( max_img_size, max_img_size, mask_depth, 1, 0 );
    mask2 = atsCreateImage( max_img_size, max_img_size, mask_depth, 1, 0 );

    roi.coi = mask_roi.coi = 0;
    roi.xOffset = roi.yOffset = 0;
    mask_roi.xOffset = mask_roi.yOffset = 0;

    img->roi = img2->roi = &roi;
    mask->roi = &mask_roi;

    for( h = min_img_size; h <= max_img_size; )
    {
        for( w = min_img_size; w <= max_img_size; )
        {
            int  denom = (w - min_img_size + 1)*(h - min_img_size + 1)*channels;
            int  iters = (base_iters*2 + denom)/(2*denom);

            roi.width = mask_roi.width = w;
            roi.height = mask_roi.height = h;

            if( iters < 1 ) iters = 1;

            for( i = 0; i < iters; i++ )
            {
                double  etalon_result[6];
                double  etalon_mask_result[6];
                CvPoint etalon_loc[6];
                CvPoint etalon_mask_loc[6];
                int      mask_pix = 0;

                switch( depth )
                {
                case IPL_DEPTH_8U:
                    atsRandSetBounds( &rng_state, 0, img8u_range );
                    break;
                case IPL_DEPTH_8S:
                    atsRandSetBounds( &rng_state, -img8s_range, img8s_range );
                    break;
                case IPL_DEPTH_32F:
                    atsRandSetBounds( &rng_state, -img32f_range, img32f_range );
                    atsRandSetFloatBits( &rng_state, img32f_bits );
                    break;
                }

                roi.coi = 0;
                atsFillRandomImageEx( img, &rng_state );

                atsRandSetBounds( &rng_state, 0, 255 );
                atsFillRandomImageEx( mask, &rng_state );
                iplAndS( mask, mask, mask_mask );

                if( depth != IPL_DEPTH_32F ) atsConvert( img, img2 );

                for( c = 1; c <= channels; c++ )
                {
                    roi.coi = c;
                    atsCalcImageStatistics(
                        depth == IPL_DEPTH_32F ? img : img2, 0,
                        &etalon_result[2*c-2], &etalon_result[2*c-1],  /* min & max vals */
                        &etalon_loc[2*c-2], &etalon_loc[2*c-1],  /* min & max locs */
                        0, /* non_zero */
                        0, /* sum */
                        0, 0, /* mean & stddev */
                        0, 0, 0, 0 ); /* c_norm, l1_norm, l2_norm */

                    atsCalcImageStatistics(
                        depth == IPL_DEPTH_32F ? img : img2, mask,
                        &etalon_mask_result[2*c-2], &etalon_mask_result[2*c-1],  /* min & max vals */
                        &etalon_mask_loc[2*c-2], &etalon_mask_loc[2*c-1],  /* min & max locs */
                        0, /* non_zero */
                        0, /* sum */
                        0, 0, /* mean & stddev */
                        0, 0, 0, &mask_pix ); /* c_norm, l1_norm, l2_norm */
                }

                for( c = 1; c <= channels; c++ )
                {
                    double  minmax_err0, dist_err0, err1;
                    double  result[2];
                    CvPoint loc[2];

                    roi.coi = c;

                    //printf("\r%5d%5d%6d%3d", h, w, i, c );

                    /* //// ROI version /////// */
                    cvMinMaxLoc( img, result+0, result+1, loc+0, loc+1 );
                    
                    minmax_err0 = rel_err( etalon_result[2*c-2], result[0] );
                    err1 = rel_err( etalon_result[2*c-1], result[1] );
                    minmax_err0 = MAX( minmax_err0, err1 );
                    dist_err0 = check_extr_point( img, 0, loc[0], etalon_result[2*c-2] );
                    err1 = check_extr_point( img, 0, loc[1], etalon_result[2*c-1] );
                    dist_err0 = MAX( dist_err0, err1 );

                    /* //// ROI Mask version /////// */
                    cvMinMaxLocMask( img, mask, result+0, result+1, loc+0, loc+1 );

                    if( mask_pix == 0 )
                    {
                        if( loc[0].x != 0 || loc[0].y != 0 ||
                            loc[1].x != 0 || loc[1].y != 0 ||
                            result[0] != 0 || result[1] != 0 )
                        {
                            code = TRS_FAIL;
                            goto test_exit;
                        }
                    }
                    else
                    {
                        err1 = rel_err( etalon_mask_result[2*c-2], result[0] );
                        minmax_err0 = MAX( minmax_err0, err1 );
                        err1 = rel_err( etalon_mask_result[2*c-1], result[1] );
                        minmax_err0 = MAX( minmax_err0, err1 );
                        err1 = check_extr_point( img, mask, loc[0], etalon_mask_result[2*c-2] );
                        dist_err0 = MAX( dist_err0, err1 );
                        err1 = check_extr_point( img, mask, loc[1], etalon_mask_result[2*c-1] );
                        dist_err0 = MAX( dist_err0, err1 );
                    }

                    if( minmax_err0 > max_err || dist_err0 != 0 )
                    {
                        merr_w    = w;
                        merr_h    = h;
                        merr_iter = i;
                        merr_c    = c;
                        max_err   = minmax_err0;
                        if( dist_err0 != 0 )
                        {
                            max_err = 1e30;
                            goto test_exit;
                        }

                        if( max_err > success_error_level )
                            goto test_exit;
                    }
                }
            }
            ATS_INCREASE( w, img_size_delta_type, img_size_delta );
        } /* end of the loop by w */

        ATS_INCREASE( h, img_size_delta_type, img_size_delta );
    }  /* end of the loop by h */

test_exit:

    img->roi = img2->roi = mask->roi = 0;

    iplDeallocate( img, IPL_IMAGE_ALL );
    iplDeallocate( img2, IPL_IMAGE_ALL );
    iplDeallocate( mask, IPL_IMAGE_ALL );
    iplDeallocate( mask2, IPL_IMAGE_ALL );

    if( code == TRS_OK )
    {
        trsWrite( ATS_LST, "Max err is %g at w = %d, h = %d, "
                           "iter = %d, c = %d, seed = %08x",
                           max_err, merr_w, merr_h, merr_iter, merr_c, seed );

        return max_err <= success_error_level ?
            trsResult( TRS_OK, "No errors" ) :
            trsResult( TRS_FAIL, "Bad accuracy" );
    }
    else
    {
        trsWrite( ATS_LST, "Fatal error at w = %d, h = %d, "
                           "iter = %d, c = %d, seed = %08x",
                           w, h, i, c, seed );
        return trsResult( TRS_FAIL, "Function returns error code" );
    }
}


#define _8U_C1     0
#define _8U_C3     1
#define _8S_C1     2
#define _8S_C3     3
#define _32F_C1    4
#define _32F_C3    5

void InitAImageStatistics( void )
{
    /* Register test functions */
    trsRegArg( funcs[0], test_desc, atsAlgoClass, count_non_zero_test, _8U_C1 );
    trsRegArg( funcs[0], test_desc, atsAlgoClass, count_non_zero_test, _8U_C3 );
    trsRegArg( funcs[0], test_desc, atsAlgoClass, count_non_zero_test, _8S_C1 );
    trsRegArg( funcs[0], test_desc, atsAlgoClass, count_non_zero_test, _8S_C3 );
    trsRegArg( funcs[0], test_desc, atsAlgoClass, count_non_zero_test, _32F_C1 );
    trsRegArg( funcs[0], test_desc, atsAlgoClass, count_non_zero_test, _32F_C3 );

    trsRegArg( funcs[1], test_desc, atsAlgoClass, sum_pixels_test, _8U_C1 );
    trsRegArg( funcs[1], test_desc, atsAlgoClass, sum_pixels_test, _8U_C3 );
    trsRegArg( funcs[1], test_desc, atsAlgoClass, sum_pixels_test, _8S_C1 );
    trsRegArg( funcs[1], test_desc, atsAlgoClass, sum_pixels_test, _8S_C3 );
    trsRegArg( funcs[1], test_desc, atsAlgoClass, sum_pixels_test, _32F_C1 );
    trsRegArg( funcs[1], test_desc, atsAlgoClass, sum_pixels_test, _32F_C3 );

    trsRegArg( funcs[2], test_desc, atsAlgoClass, min_max_loc_test, _8U_C1 );
    trsRegArg( funcs[2], test_desc, atsAlgoClass, min_max_loc_test, _8U_C3 );
    trsRegArg( funcs[2], test_desc, atsAlgoClass, min_max_loc_test, _8S_C1 );
    trsRegArg( funcs[2], test_desc, atsAlgoClass, min_max_loc_test, _8S_C3 );
    trsRegArg( funcs[2], test_desc, atsAlgoClass, min_max_loc_test, _32F_C1 );
    trsRegArg( funcs[2], test_desc, atsAlgoClass, min_max_loc_test, _32F_C3 );

    trsRegArg( funcs[3], test_desc, atsAlgoClass, mean_test, _8U_C1 );
    trsRegArg( funcs[3], test_desc, atsAlgoClass, mean_test, _8U_C3 );
    trsRegArg( funcs[3], test_desc, atsAlgoClass, mean_test, _8S_C1 );
    trsRegArg( funcs[3], test_desc, atsAlgoClass, mean_test, _8S_C3 );
    trsRegArg( funcs[3], test_desc, atsAlgoClass, mean_test, _32F_C1 );
    trsRegArg( funcs[3], test_desc, atsAlgoClass, mean_test, _32F_C3 );

    trsRegArg( funcs[4], test_desc, atsAlgoClass, mean_stddev_test, _8U_C1 );
    trsRegArg( funcs[4], test_desc, atsAlgoClass, mean_stddev_test, _8U_C3 );
    trsRegArg( funcs[4], test_desc, atsAlgoClass, mean_stddev_test, _8S_C1 );
    trsRegArg( funcs[4], test_desc, atsAlgoClass, mean_stddev_test, _8S_C3 );
    trsRegArg( funcs[4], test_desc, atsAlgoClass, mean_stddev_test, _32F_C1 );
    trsRegArg( funcs[4], test_desc, atsAlgoClass, mean_stddev_test, _32F_C3 );
} /* InitAImageStatistics */

/* End of file. */