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Optimized version of Norm and NormDiff functions with f32 type added

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This commit is contained in:
Kirill Kornyakov 2011-11-21 05:59:49 +00:00
parent 7172c8cea9
commit 9fb9d99bb9
1 changed files with 13 additions and 12 deletions
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25
modules/core/src/stat.cpp
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@ -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;
}
}