generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

a big patch; use special proxy types (Input/OutputArray, Input/OutputArrayOfArrays) for passing in vectors, matrices etc.

Browse Source
This commit is contained in:
Vadim Pisarevsky
2011-04-17 13:14:45 +00:00
parent 335370a7c0
commit abeeb40d46
94 changed files with 10831 additions and 9631 deletions
Download Patch File Download Diff File Expand all files Collapse all files

62
modules/imgproc/src/thresh.cpp
View File

@@ -475,20 +475,24 @@ getThreshVal_Otsu_8u( const Mat& _src )
return max_val;
}
double threshold( const Mat& _src, Mat& _dst, double thresh, double maxval, int type )
}
double cv::threshold( const InputArray& _src, OutputArray _dst, double thresh, double maxval, int type )
{
Mat src = _src.getMat();
bool use_otsu = (type & THRESH_OTSU) != 0;
type &= THRESH_MASK;
if( use_otsu )
{
CV_Assert( _src.type() == CV_8UC1 );
thresh = getThreshVal_Otsu_8u(_src);
CV_Assert( src.type() == CV_8UC1 );
thresh = getThreshVal_Otsu_8u(src);
}
_dst.create( _src.size(), _src.type() );
if( _src.depth() == CV_8U )
_dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
if( src.depth() == CV_8U )
{
int ithresh = cvFloor(thresh);
thresh = ithresh;
@@ -506,16 +510,16 @@ double threshold( const Mat& _src, Mat& _dst, double thresh, double maxval, int
int v = type == THRESH_BINARY ? (ithresh >= 255 ? 0 : imaxval) :
type == THRESH_BINARY_INV ? (ithresh >= 255 ? imaxval : 0) :
type == THRESH_TRUNC ? imaxval : 0;
_dst = Scalar::all(v);
dst = Scalar::all(v);
}
else
_src.copyTo(_dst);
src.copyTo(dst);
}
else
thresh_8u( _src, _dst, (uchar)ithresh, (uchar)imaxval, type );
thresh_8u( src, dst, (uchar)ithresh, (uchar)imaxval, type );
}
else if( _src.depth() == CV_32F )
thresh_32f( _src, _dst, (float)thresh, (float)maxval, type );
else if( src.depth() == CV_32F )
thresh_32f( src, dst, (float)thresh, (float)maxval, type );
else
CV_Error( CV_StsUnsupportedFormat, "" );
@@ -523,31 +527,33 @@ double threshold( const Mat& _src, Mat& _dst, double thresh, double maxval, int
}
void adaptiveThreshold( const Mat& _src, Mat& _dst, double maxValue,
int method, int type, int blockSize, double delta )
void cv::adaptiveThreshold( const InputArray& _src, OutputArray _dst, double maxValue,
int method, int type, int blockSize, double delta )
{
CV_Assert( _src.type() == CV_8UC1 );
Mat src = _src.getMat();
CV_Assert( src.type() == CV_8UC1 );
CV_Assert( blockSize % 2 == 1 && blockSize > 1 );
Size size = _src.size();
Size size = src.size();
_dst.create( size, _src.type() );
_dst.create( size, src.type() );
Mat dst = _dst.getMat();
if( maxValue < 0 )
{
_dst = Scalar(0);
dst = Scalar(0);
return;
}
Mat _mean;
Mat mean;
if( _src.data != _dst.data )
_mean = _dst;
if( src.data != dst.data )
mean = dst;
if( method == ADAPTIVE_THRESH_MEAN_C )
boxFilter( _src, _mean, _src.type(), Size(blockSize, blockSize),
boxFilter( src, mean, src.type(), Size(blockSize, blockSize),
Point(-1,-1), true, BORDER_REPLICATE );
else if( method == ADAPTIVE_THRESH_GAUSSIAN_C )
GaussianBlur( _src, _mean, Size(blockSize, blockSize), 0, 0, BORDER_REPLICATE );
GaussianBlur( src, mean, Size(blockSize, blockSize), 0, 0, BORDER_REPLICATE );
else
CV_Error( CV_StsBadFlag, "Unknown/unsupported adaptive threshold method" );
@@ -565,7 +571,7 @@ void adaptiveThreshold( const Mat& _src, Mat& _dst, double maxValue,
else
CV_Error( CV_StsBadFlag, "Unknown/unsupported threshold type" );
if( _src.isContinuous() && _mean.isContinuous() && _dst.isContinuous() )
if( src.isContinuous() && mean.isContinuous() && dst.isContinuous() )
{
size.width *= size.height;
size.height = 1;
@@ -573,17 +579,15 @@ void adaptiveThreshold( const Mat& _src, Mat& _dst, double maxValue,
for( i = 0; i < size.height; i++ )
{
const uchar* src = _src.data + _src.step*i;
const uchar* mean = _mean.data + _mean.step*i;
uchar* dst = _dst.data + _dst.step*i;
const uchar* sdata = src.data + src.step*i;
const uchar* mdata = mean.data + mean.step*i;
uchar* ddata = dst.data + dst.step*i;
for( j = 0; j < size.width; j++ )
dst[j] = tab[src[j] - mean[j] + 255];
ddata[j] = tab[sdata[j] - mdata[j] + 255];
}
}
}
CV_IMPL double
cvThreshold( const void* srcarr, void* dstarr, double thresh, double maxval, int type )
{