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      1 /*M///////////////////////////////////////////////////////////////////////////////////////
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      9 //
     10 //                        Intel License Agreement
     11 //                For Open Source Computer Vision Library
     12 //
     13 // Copyright (C) 2000, Intel Corporation, all rights reserved.
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     16 // Redistribution and use in source and binary forms, with or without modification,
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     30 // any express or implied warranties, including, but not limited to, the implied
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     39 //
     40 //M*/
     41 #include "_cv.h"
     42 
     43 #if 0
     44 
     45 IPCVAPI(CvStatus, icvCalcContrastHist8uC1R, ( uchar** img, int step, CvSize size,
     46                                               CvHistogram* hist, int dont_clear ))
     47 
     48 IPCVAPI(CvStatus, icvCalcContrastHistMask8uC1R, ( uchar** img, int step,
     49                                                   uchar*  mask, int mask_step, CvSize size,
     50                                                   CvHistogram* hist, int dont_clear ))
     51 
     52 /*F///////////////////////////////////////////////////////////////////////////////////////
     53 //    Name:       icvCalcContrastHist8uC1R
     54 //    Purpose:    Calculating the histogram of contrast from one-channel images
     55 //    Context:
     56 //    Parameters:
     57 //    Returns:
     58 //    Notes:      if dont_clear parameter is NULL then histogram clearing before
     59 //                calculating (all values sets to NULL)
     60 //F*/
     61 static CvStatus CV_STDCALL
     62 icvCalcContrastHist8uC1R( uchar** img, int step, CvSize size,
     63                           CvHistogram* hist, int dont_clear )
     64 {
     65     int i, j, t, x = 0, y = 0;
     66     int dims;
     67 
     68     if( !hist || !img )
     69         return CV_NULLPTR_ERR;
     70 
     71     dims = hist->c_dims;
     72     if( dims != 1 )
     73         return CV_BADSIZE_ERR;
     74 
     75     if( hist->type != CV_HIST_ARRAY )
     76         return CV_BADFLAG_ERR;
     77 
     78     for( i = 0; i < dims; i++ )
     79         if( !img[i] )
     80             return CV_NULLPTR_ERR;
     81 
     82     for( i = 0; i < hist->c_dims; i++ )
     83     {
     84         if( !hist->thresh[i] )
     85             return CV_NULLPTR_ERR;
     86         assert( hist->chdims[i] );
     87     }
     88 
     89     j = hist->dims[0] * hist->mdims[0];
     90 
     91     int *n = (int *)cvAlloc( (size_t)hist->dims[0] * sizeof( int ));
     92 
     93     if( hist->type == CV_HIST_ARRAY )
     94     {
     95         if( !dont_clear )
     96             for( i = 0; i < j; i++ )
     97             {
     98                 hist->array[i] = 0;
     99                 n[i] = 0;
    100             }
    101 
    102         switch (hist->c_dims)
    103         {
    104         case 1:
    105             {
    106                 uchar *data0 = img[0];
    107                 int *array = (int *) hist->array;
    108                 int *chdims = hist->chdims[0];
    109 
    110                 for( i = 0; i < j; i++ )
    111                     array[i] = cvRound( hist->array[i] );
    112 
    113                 for( y = 0; y < size.height; y++, data0 += step )
    114                 {
    115                     for( x = 0; x <= size.width - 1; x += 2 )
    116                     {
    117                         int v1_r = MIN( data0[x], data0[x + 1] );
    118                         int v2_r = MAX( data0[x], data0[x + 1] );
    119 
    120 //    calculate contrast for the right-left pair
    121                         for( t = v1_r; t < v2_r; t++ )
    122                         {
    123                             int val0 = chdims[t + 128];
    124 
    125                             array[val0] += MIN( t - v1_r, v2_r - t );
    126                             n[val0]++;
    127                         }
    128 
    129                         if( y < size.height - 1 )
    130                         {
    131                             int v1_d = MIN( data0[x], data0[x + step] );
    132                             int v2_d = MAX( data0[x], data0[x + step] );
    133 
    134 //    calculate contrast for the top-down pair
    135                             for( t = v1_d; t < v2_d; t++ )
    136                             {
    137                                 int val0 = chdims[t + 128];
    138 
    139                                 array[val0] += MIN( t - v1_d, v2_d - t );
    140                                 n[val0]++;
    141                             }
    142                         }
    143                     }
    144                 }
    145 
    146 //  convert int to float
    147                 for( i = 0; i < j; i++ )
    148                 {
    149                     if( n[i] != 0 )
    150                         hist->array[i] = (float) array[i] / n[i];
    151                     else
    152                         hist->array[i] = 0;
    153                 }
    154             }
    155             break;
    156         default:
    157             return CV_BADSIZE_ERR;
    158         }
    159     }
    160 
    161     cvFree( &n );
    162     return CV_NO_ERR;
    163 }
    164 
    165 /*F///////////////////////////////////////////////////////////////////////////////////////
    166 //    Name:       icvCalcContrastHistMask8uC1R
    167 //    Purpose:    Calculating the mask histogram of contrast from one-channel images
    168 //    Context:
    169 //    Parameters:
    170 //    Returns:
    171 //    Notes:      if dont_clear parameter is NULL then histogram clearing before
    172 //                calculating (all values sets to NULL)
    173 //F*/
    174 static CvStatus CV_STDCALL
    175 icvCalcContrastHistMask8uC1R( uchar** img, int step, uchar* mask, int mask_step,
    176                               CvSize size, CvHistogram * hist, int dont_clear )
    177 {
    178     int i, j, t, x = 0, y = 0;
    179     int dims;
    180 
    181 
    182     if( !hist || !img || !mask )
    183         return CV_NULLPTR_ERR;
    184 
    185     dims = hist->c_dims;
    186     if( dims != 1 )
    187         return CV_BADSIZE_ERR;
    188 
    189     if( hist->type != CV_HIST_ARRAY )
    190         return CV_BADFLAG_ERR;
    191 
    192     for( i = 0; i < dims; i++ )
    193         if( !img[i] )
    194             return CV_NULLPTR_ERR;
    195 
    196     for( i = 0; i < hist->c_dims; i++ )
    197     {
    198         if( !hist->thresh[i] )
    199             return CV_NULLPTR_ERR;
    200         assert( hist->chdims[i] );
    201     }
    202 
    203     j = hist->dims[0] * hist->mdims[0];
    204 
    205     int *n = (int *)cvAlloc( (size_t) hist->dims[0] * sizeof( int ));
    206 
    207     if( hist->type == CV_HIST_ARRAY )
    208     {
    209         if( !dont_clear )
    210             for( i = 0; i < j; i++ )
    211             {
    212                 hist->array[i] = 0;
    213                 n[i] = 0;
    214             }
    215 
    216         switch (hist->c_dims)
    217         {
    218         case 1:
    219             {
    220                 uchar *data0 = img[0];
    221                 uchar *maskp = mask;
    222                 int *array = (int *) hist->array;
    223                 int *chdims = hist->chdims[0];
    224 
    225                 for( i = 0; i < j; i++ )
    226                     array[i] = cvRound( hist->array[i] );
    227 
    228                 for( y = 0; y < size.height; y++, data0 += step, maskp += mask_step )
    229                 {
    230                     for( x = 0; x <= size.width - 2; x++ )
    231                     {
    232                         if( maskp[x] )
    233                         {
    234                             if( maskp[x + 1] )
    235                             {
    236                                 int v1_r = MIN( data0[x], data0[x + 1] );
    237                                 int v2_r = MAX( data0[x], data0[x + 1] );
    238 
    239 
    240                                 //    calculate contrast for the right-left pair
    241                                 for( t = v1_r; t < v2_r; t++ )
    242                                 {
    243                                     int val0 = chdims[t + 128];
    244 
    245                                     array[val0] += MIN( t - v1_r, v2_r - t );
    246                                     n[val0]++;
    247 
    248                                 }
    249                             }
    250 
    251                             if( y < size.height - 1 )
    252                             {
    253                                 if( maskp[x + mask_step] )
    254                                 {
    255                                     int v1_d = MIN( data0[x], data0[x + step] );
    256                                     int v2_d = MAX( data0[x], data0[x + step] );
    257 
    258                                     //    calculate contrast for the top-down pair
    259                                     for( t = v1_d; t < v2_d; t++ )
    260                                     {
    261                                         int val0 = chdims[t + 128];
    262 
    263                                         array[val0] += MIN( t - v1_d, v2_d - t );
    264                                         n[val0]++;
    265 
    266                                     }
    267                                 }
    268                             }
    269                         }
    270                     }
    271                 }
    272 
    273 //  convert int to float
    274                 for( i = 0; i < j; i++ )
    275                 {
    276                     if( n[i] != 0 )
    277                         hist->array[i] = (float) array[i] / n[i];
    278                     else
    279                         hist->array[i] = 0;
    280                 }
    281             }
    282             break;
    283         default:
    284             return CV_BADSIZE_ERR;
    285         }
    286     }
    287 
    288     cvFree( &n );
    289     return CV_NO_ERR;
    290 }
    291 
    292 /*
    293 CV_IMPL void cvCalcContrastHist( IplImage** img, CvHistogram* hist, int dont_clear )
    294 {
    295     CV_FUNCNAME( "cvCalcContrastHist" );
    296     uchar*   data[CV_HIST_MAX_DIM];
    297     int      step = 0;
    298     CvSize roi = {0,0};
    299 
    300     __BEGIN__;
    301 
    302     {for( int i = 0; i < hist->c_dims; i++ )
    303         CV_CALL( CV_CHECK_IMAGE( img[i] ) );}
    304 
    305     {for( int i = 0; i < hist->c_dims; i++ )
    306         cvGetImageRawData( img[i], &data[i], &step, &roi );}
    307 
    308     if(img[0]->nChannels != 1)
    309         CV_ERROR( IPL_BadNumChannels, "bad channels numbers" );
    310 
    311     if(img[0]->depth != IPL_DEPTH_8U)
    312         CV_ERROR( IPL_BadDepth, "bad image depth" );
    313 
    314     switch(img[0]->depth)
    315     {
    316     case IPL_DEPTH_8U:
    317         IPPI_CALL( icvCalcContrastHist8uC1R( data, step, roi, hist, dont_clear ) );
    318         break;
    319     default:  CV_ERROR( IPL_BadDepth, "bad image depth" );
    320     }
    321 
    322     __CLEANUP__;
    323     __END__;
    324 }
    325 */
    326 
    327 CV_IMPL void
    328 cvCalcContrastHist( IplImage ** img, CvHistogram * hist, int dont_clear, IplImage * mask )
    329 {
    330     CV_FUNCNAME( "cvCalcContrastHist" );
    331     uchar *data[CV_HIST_MAX_DIM];
    332     uchar *mask_data = 0;
    333     int step = 0;
    334     int mask_step = 0;
    335     CvSize roi = { 0, 0 };
    336 
    337     __BEGIN__;
    338 
    339     {
    340         for( int i = 0; i < hist->c_dims; i++ )
    341             CV_CALL( CV_CHECK_IMAGE( img[i] ));
    342     }
    343     if( mask )
    344     {
    345         CV_CALL( CV_CHECK_IMAGE( mask ));
    346         if( mask->depth != IPL_DEPTH_8U )
    347             CV_ERROR( CV_BadDepth, "bad mask depth" );
    348         cvGetImageRawData( mask, &mask_data, &mask_step, 0 );
    349     }
    350 
    351 
    352     {
    353         for( int i = 0; i < hist->c_dims; i++ )
    354             cvGetImageRawData( img[i], &data[i], &step, &roi );
    355     }
    356 
    357     if( img[0]->nChannels != 1 )
    358         CV_ERROR( CV_BadNumChannels, "bad channels numbers" );
    359 
    360     if( img[0]->depth != IPL_DEPTH_8U )
    361         CV_ERROR( CV_BadDepth, "bad image depth" );
    362 
    363 
    364     switch (img[0]->depth)
    365     {
    366     case IPL_DEPTH_8U:
    367         if( !mask )
    368         {
    369             IPPI_CALL( icvCalcContrastHist8uC1R( data, step, roi, hist, dont_clear ));
    370         }
    371         else
    372         {
    373             IPPI_CALL( icvCalcContrastHistMask8uC1R( data, step, mask_data,
    374                                                      mask_step, roi, hist, dont_clear ));
    375         }
    376         break;
    377     default:
    378         CV_ERROR( CV_BadDepth, "bad image depth" );
    379     }
    380 
    381     __CLEANUP__;
    382     __END__;
    383 }
    384 
    385 #endif
    386