Chiebot-Mirror
/
opencv
mirror of https://github.com/opencv/opencv.git
8
0
Fork 0
Code Issues Projects Releases Wiki Activity

Optimized version of Norm and NormDiff functions with f32 type added

Browse Source
pull/13383/head
Kirill Kornyakov 13 years ago
parent 7172c8cea9
commit 9fb9d99bb9
1 changed files with 13 additions and 12 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 25
      modules/core/src/stat.cpp

25
modules/core/src/stat.cpp
Unescape View File

@ -1175,7 +1175,7 @@ static NormFunc normTab[3][8] =
},
{
(NormFunc)GET_OPTIMIZED(normL2_8u), (NormFunc)normL2_8s, (NormFunc)normL2_16u, (NormFunc)normL2_16s,
(NormFunc)normL2_32s, (NormFunc)normL2_32f, (NormFunc)normL2_64f, 0
(NormFunc)normL2_32s, (NormFunc)GET_OPTIMIZED(normL2_32f), (NormFunc)normL2_64f, 0
}
};
@ -1184,19 +1184,19 @@ static NormDiffFunc normDiffTab[3][8] =
{
(NormDiffFunc)GET_OPTIMIZED(normDiffInf_8u), (NormDiffFunc)normDiffInf_8s,
(NormDiffFunc)normDiffInf_16u, (NormDiffFunc)normDiffInf_16s,
(NormDiffFunc)normDiffInf_32s, (NormDiffFunc)normDiffInf_32f,
(NormDiffFunc)normDiffInf_32s, (NormDiffFunc)GET_OPTIMIZED(normDiffInf_32f),
(NormDiffFunc)normDiffInf_64f, 0
},
{
(NormDiffFunc)GET_OPTIMIZED(normDiffL1_8u), (NormDiffFunc)normDiffL1_8s,
(NormDiffFunc)normDiffL1_16u, (NormDiffFunc)normDiffL1_16s,
(NormDiffFunc)normDiffL1_32s, (NormDiffFunc)normDiffL1_32f,
(NormDiffFunc)normDiffL1_32s, (NormDiffFunc)GET_OPTIMIZED(normDiffL1_32f),
(NormDiffFunc)normDiffL1_64f, 0
},
{
(NormDiffFunc)GET_OPTIMIZED(normDiffL2_8u), (NormDiffFunc)normDiffL2_8s,
(NormDiffFunc)normDiffL2_16u, (NormDiffFunc)normDiffL2_16s,
(NormDiffFunc)normDiffL2_32s, (NormDiffFunc)normDiffL2_32f,
(NormDiffFunc)normDiffL2_32s, (NormDiffFunc)GET_OPTIMIZED(normDiffL2_32f),
(NormDiffFunc)normDiffL2_64f, 0
}
};
@ -1221,19 +1221,20 @@ double cv::norm( InputArray _src, int normType, InputArray _mask )
if( normType == NORM_L2 )
{
double result = 0;
normL2_32f(data, 0, &result, (int)len, 1);
GET_OPTIMIZED(normL2_32f)(data, 0, &result, (int)len, 1);
return std::sqrt(result);
}
if( normType == NORM_L1 )
{
double result = 0;
normL1_32f(data, 0, &result, (int)len, 1);
GET_OPTIMIZED(normL1_32f)(data, 0, &result, (int)len, 1);
return result;
}
{
float result = 0;
normInf_32f(data, 0, &result, (int)len, 1);
GET_OPTIMIZED(normInf_32f)(data, 0, &result, (int)len, 1);
return result;
}
}
}
@ -1274,8 +1275,8 @@ double cv::norm( InputArray _src, int normType, InputArray _mask )
for( j = 0; j < total; j += blockSize )
{
int bsz = std::min(total - j, blockSize);
func( ptrs[0], ptrs[1], (uchar*)ibuf, bsz, cn );
count += bsz;
func( ptrs[0], ptrs[1], (uchar*)ibuf, bsz, cn );
count += bsz;
if( blockSum && (count + blockSize >= intSumBlockSize || (i+1 >= it.nplanes && j+bsz >= total)) )
{
result.d += isum;
@ -1328,18 +1329,18 @@ double cv::norm( InputArray _src1, InputArray _src2, int normType, InputArray _m
if( normType == NORM_L2 )
{
double result = 0;
normDiffL2_32f(data1, data2, 0, &result, (int)len, 1);
GET_OPTIMIZED(normDiffL2_32f)(data1, data2, 0, &result, (int)len, 1);
return std::sqrt(result);
}
if( normType == NORM_L1 )
{
double result = 0;
normDiffL1_32f(data1, data2, 0, &result, (int)len, 1);
GET_OPTIMIZED(normDiffL1_32f)(data1, data2, 0, &result, (int)len, 1);
return result;
}
{
float result = 0;
normDiffInf_32f(data1, data2, 0, &result, (int)len, 1);
GET_OPTIMIZED(normDiffInf_32f)(data1, data2, 0, &result, (int)len, 1);
return result;
}
}

Write Preview
Loading…
Cancel
Save