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submodule
opencv
Commits
fda1e767
Commit
fda1e767
authored
Sep 08, 2017
by
saskatchewancatch
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Feedback.
Still need to remove the descriptions of these flags from cv::norm
parent
570083fb
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52 additions
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6 deletions
+52
-6
core.hpp
modules/core/include/opencv2/core.hpp
+5
-1
base.hpp
modules/core/include/opencv2/core/base.hpp
+47
-5
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modules/core/include/opencv2/core.hpp
View file @
fda1e767
...
...
@@ -640,10 +640,14 @@ Scalar_ 's.
CV_EXPORTS_W
void
meanStdDev
(
InputArray
src
,
OutputArray
mean
,
OutputArray
stddev
,
InputArray
mask
=
noArray
());
/** @brief Calculates
an absolute array norm
.
/** @brief Calculates
the absolute norm of an array
.
This version of cv::norm calculates the absolute norm of src1. The type of norm to calculate is specified using cv::NormTypes.
If normType is not specified, NORM_L2 is used.
--done edit--
\f[norm = \forkfour{\|\texttt{src1}\|_{L_{\infty}} = \max _I | \texttt{src1} (I)|}{if \(\texttt{normType} = \texttt{NORM_INF}\) }
{ \| \texttt{src1} \| _{L_1} = \sum _I | \texttt{src1} (I)|}{if \(\texttt{normType} = \texttt{NORM_L1}\) }
{ \| \texttt{src1} \| _{L_2} = \sqrt{\sum_I \texttt{src1}(I)^2} }{if \(\texttt{normType} = \texttt{NORM_L2}\) }
...
...
modules/core/include/opencv2/core/base.hpp
View file @
fda1e767
...
...
@@ -151,16 +151,58 @@ enum DecompTypes {
DECOMP_NORMAL
=
16
};
//! norm types
enum
NormTypes
{
NORM_INF
=
1
,
/** norm types
src1 and src2 denote input arrays.
*/
enum
NormTypes
{
/**
\f[
norm = \forkthree
{\|\texttt{src1}\|_{L_{\infty}} = \max _I | \texttt{src1} (I)|}{if \(\texttt{normType} = \texttt{NORM_INF}\) }
{\|\texttt{src1}-\texttt{src2}\|_{L_{\infty}} = \max _I | \texttt{src1} (I) - \texttt{src2} (I)|}{if \(\texttt{normType} = \texttt{NORM_INF}\) }
{\frac{\|\texttt{src1}-\texttt{src2}\|_{L_{\infty}} }{\|\texttt{src2}\|_{L_{\infty}} }}{if \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_INF}\) }
\f]
*/
NORM_INF
=
1
,
/**
\f[
norm = \forkthree
{\| \texttt{src1} \| _{L_1} = \sum _I | \texttt{src1} (I)|}{if \(\texttt{normType} = \texttt{NORM_L1}\)}
{ \| \texttt{src1} - \texttt{src2} \| _{L_1} = \sum _I | \texttt{src1} (I) - \texttt{src2} (I)|}{if \(\texttt{normType} = \texttt{NORM_L1}\) }
{ \frac{\|\texttt{src1}-\texttt{src2}\|_{L_1} }{\|\texttt{src2}\|_{L_1}} }{if \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_L1}\) }
\f]*/
NORM_L1
=
2
,
/**
\f[
norm = \forkthree
{ \| \texttt{src1} \| _{L_2} = \sqrt{\sum_I \texttt{src1}(I)^2} }{if \(\texttt{normType} = \texttt{NORM_L2}\) }
{ \| \texttt{src1} - \texttt{src2} \| _{L_2} = \sqrt{\sum_I (\texttt{src1}(I) - \texttt{src2}(I))^2} }{if \(\texttt{normType} = \texttt{NORM_L2}\) }
{ \frac{\|\texttt{src1}-\texttt{src2}\|_{L_2} }{\|\texttt{src2}\|_{L_2}} }{if \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_L2}\) }
\f]
*/
NORM_L2
=
4
,
/**
\f[
norm = \forkthree
{ \| \texttt{src1} \| _{L_2} ^{2} = \sum_I \texttt{src1}(I)^2} {if \(\texttt{normType} = \texttt{NORM_L2SQR}\)}
{ \| \texttt{src1} - \texttt{src2} \| _{L_2} ^{2} = \sum_I (\texttt{src1}(I) - \texttt{src2}(I))^2 }{if \(\texttt{normType} = \texttt{NORM_L2SQR}\) }
{ \left(\frac{\|\texttt{src1}-\texttt{src2}\|_{L_2} }{\|\texttt{src2}\|_{L_2}}\right)^2 }{if \(\texttt{normType} = \texttt{NORM_RELATIVE | NORM_L2}\) }
\f]
*/
NORM_L2SQR
=
5
,
/**
In the case of one input array, calculates the Hamming distance of the array from zero,
In the case of two input arrays, calculates the Hamming distance between the arrays.
*/
NORM_HAMMING
=
6
,
/**
Similar to NORM_HAMMING, but in the calculation, each two bits of the input sequence will
be added and treated as a single bit to be used in the same calculation as NORM_HAMMING.
*/
NORM_HAMMING2
=
7
,
#ifndef CV_DOXYGEN
NORM_TYPE_MASK
=
7
,
#endif
NORM_TYPE_MASK
=
7
,
//!< bit-mask which can be used to separate norm type from norm flags
NORM_RELATIVE
=
8
,
//!< flag
NORM_MINMAX
=
32
//!< flag
};
...
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