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Merge pull request #9551 from ChristofKaufmann:MultiChannelMask

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This commit is contained in:
Vadim Pisarevsky 2017-09-18 09:28:34 +00:00
commit f4136679ea
4 changed files with 61 additions and 28 deletions
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7
modules/core/include/opencv2/core/mat.hpp
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@ -1192,8 +1192,8 @@ public:
/** @overload
@param m Destination matrix. If it does not have a proper size or type before the operation, it is
reallocated.
@param mask Operation mask. Its non-zero elements indicate which matrix elements need to be copied.
The mask has to be of type CV_8U and can have 1 or multiple channels.
@param mask Operation mask of the same size as \*this. Its non-zero elements indicate which matrix
elements need to be copied. The mask has to be of type CV_8U and can have 1 or multiple channels.
*/
void copyTo( OutputArray m, InputArray mask ) const;
@ -1229,7 +1229,8 @@ public:
This is an advanced variant of the Mat::operator=(const Scalar& s) operator.
@param value Assigned scalar converted to the actual array type.
@param mask Operation mask of the same size as \*this.
@param mask Operation mask of the same size as \*this. Its non-zero elements indicate which matrix
elements need to be copied. The mask has to be of type CV_8U and can have 1 or multiple channels
*/
Mat& setTo(InputArray value, InputArray mask=noArray());

13
modules/core/src/copy.cpp
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@ -336,7 +336,7 @@ static bool ipp_copyTo(const Mat &src, Mat &dst, const Mat &mask)
#ifdef HAVE_IPP_IW
CV_INSTRUMENT_REGION_IPP()
if(mask.channels() > 1 && mask.depth() != CV_8U)
if(mask.channels() > 1 || mask.depth() != CV_8U)
return false;
if (src.dims <= 2)
@ -512,20 +512,23 @@ Mat& Mat::setTo(InputArray _value, InputArray _mask)
Mat value = _value.getMat(), mask = _mask.getMat();
CV_Assert( checkScalar(value, type(), _value.kind(), _InputArray::MAT ));
CV_Assert( mask.empty() || (mask.type() == CV_8U && size == mask.size) );
int cn = channels(), mcn = mask.channels();
CV_Assert( mask.empty() || (mask.depth() == CV_8U && (mcn == 1 || mcn == cn) && size == mask.size) );
CV_IPP_RUN_FAST(ipp_Mat_setTo_Mat(*this, value, mask), *this)
size_t esz = elemSize();
size_t esz = mcn > 1 ? elemSize1() : elemSize();
BinaryFunc copymask = getCopyMaskFunc(esz);
const Mat* arrays[] = { this, !mask.empty() ? &mask : 0, 0 };
uchar* ptrs[2]={0,0};
NAryMatIterator it(arrays, ptrs);
int totalsz = (int)it.size, blockSize0 = std::min(totalsz, (int)((BLOCK_SIZE + esz-1)/esz));
int totalsz = (int)it.size*mcn;
int blockSize0 = std::min(totalsz, (int)((BLOCK_SIZE + esz-1)/esz));
blockSize0 -= blockSize0 % mcn; // must be divisible without remainder for unrolling and advancing
AutoBuffer<uchar> _scbuf(blockSize0*esz + 32);
uchar* scbuf = alignPtr((uchar*)_scbuf, (int)sizeof(double));
convertAndUnrollScalar( value, type(), scbuf, blockSize0 );
convertAndUnrollScalar( value, type(), scbuf, blockSize0/mcn );
for( size_t i = 0; i < it.nplanes; i++, ++it )
{

19
modules/core/test/test_arithm.cpp
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@ -1,4 +1,4 @@
#include "test_precomp.hpp"
#include "test_precomp.hpp"
#include <cmath>
using namespace cv;
@ -15,7 +15,7 @@ const int ARITHM_MAX_SIZE_LOG = 10;
struct BaseElemWiseOp
{
enum { FIX_ALPHA=1, FIX_BETA=2, FIX_GAMMA=4, REAL_GAMMA=8, SUPPORT_MASK=16, SCALAR_OUTPUT=32 };
enum { FIX_ALPHA=1, FIX_BETA=2, FIX_GAMMA=4, REAL_GAMMA=8, SUPPORT_MASK=16, SCALAR_OUTPUT=32, SUPPORT_MULTICHANNELMASK=64 };
BaseElemWiseOp(int _ninputs, int _flags, double _alpha, double _beta,
Scalar _gamma=Scalar::all(0), int _context=1)
: ninputs(_ninputs), flags(_flags), alpha(_alpha), beta(_beta), gamma(_gamma), context(_context) {}
@ -467,7 +467,7 @@ struct CmpSOp : public BaseElemWiseOp
struct CopyOp : public BaseElemWiseOp
{
CopyOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK, 1, 1, Scalar::all(0)) { }
CopyOp() : BaseElemWiseOp(1, FIX_ALPHA+FIX_BETA+FIX_GAMMA+SUPPORT_MASK+SUPPORT_MULTICHANNELMASK, 1, 1, Scalar::all(0)) { }
void op(const vector<Mat>& src, Mat& dst, const Mat& mask)
{
src[0].copyTo(dst, mask);
@ -489,7 +489,7 @@ struct CopyOp : public BaseElemWiseOp
struct SetOp : public BaseElemWiseOp
{
SetOp() : BaseElemWiseOp(0, FIX_ALPHA+FIX_BETA+SUPPORT_MASK, 1, 1, Scalar::all(0)) {}
SetOp() : BaseElemWiseOp(0, FIX_ALPHA+FIX_BETA+SUPPORT_MASK+SUPPORT_MULTICHANNELMASK, 1, 1, Scalar::all(0)) {}
void op(const vector<Mat>&, Mat& dst, const Mat& mask)
{
dst.setTo(gamma, mask);
@ -1394,7 +1394,8 @@ TEST_P(ElemWiseTest, accuracy)
op->getRandomSize(rng, size);
int type = op->getRandomType(rng);
int depth = CV_MAT_DEPTH(type);
bool haveMask = (op->flags & cvtest::BaseElemWiseOp::SUPPORT_MASK) != 0 && rng.uniform(0, 4) == 0;
bool haveMask = ((op->flags & cvtest::BaseElemWiseOp::SUPPORT_MASK) != 0
|| (op->flags & cvtest::BaseElemWiseOp::SUPPORT_MULTICHANNELMASK) != 0) && rng.uniform(0, 4) == 0;
double minval=0, maxval=0;
op->getValueRange(depth, minval, maxval);
@ -1403,8 +1404,12 @@ TEST_P(ElemWiseTest, accuracy)
for( i = 0; i < ninputs; i++ )
src[i] = cvtest::randomMat(rng, size, type, minval, maxval, true);
Mat dst0, dst, mask;
if( haveMask )
mask = cvtest::randomMat(rng, size, CV_8U, 0, 2, true);
if( haveMask ) {
bool multiChannelMask = (op->flags & cvtest::BaseElemWiseOp::SUPPORT_MULTICHANNELMASK) != 0
&& rng.uniform(0, 2) == 0;
int masktype = CV_8UC(multiChannelMask ? CV_MAT_CN(type) : 1);
mask = cvtest::randomMat(rng, size, masktype, 0, 2, true);
}
if( (haveMask || ninputs == 0) && !(op->flags & cvtest::BaseElemWiseOp::SCALAR_OUTPUT))
{

50
modules/ts/src/ts_func.cpp
View File

@ -353,26 +353,38 @@ void copy(const Mat& src, Mat& dst, const Mat& mask, bool invertMask)
return;
}
CV_Assert( src.size == mask.size && mask.type() == CV_8U );
int mcn = mask.channels();
CV_Assert( src.size == mask.size && mask.depth() == CV_8U
&& (mcn == 1 || mcn == src.channels()) );
const Mat *arrays[]={&src, &dst, &mask, 0};
Mat planes[3];
NAryMatIterator it(arrays, planes);
size_t j, k, elemSize = src.elemSize(), total = planes[0].total();
size_t j, k, elemSize = src.elemSize(), maskElemSize = mask.elemSize(), total = planes[0].total();
size_t i, nplanes = it.nplanes;
size_t elemSize1 = src.elemSize1();
for( i = 0; i < nplanes; i++, ++it)
{
const uchar* sptr = planes[0].ptr();
uchar* dptr = planes[1].ptr();
const uchar* mptr = planes[2].ptr();
for( j = 0; j < total; j++, sptr += elemSize, dptr += elemSize )
for( j = 0; j < total; j++, sptr += elemSize, dptr += elemSize, mptr += maskElemSize )
{
if( (mptr[j] != 0) ^ invertMask )
for( k = 0; k < elemSize; k++ )
dptr[k] = sptr[k];
if( mcn == 1)
{
if( (mptr[0] != 0) ^ invertMask )
for( k = 0; k < elemSize; k++ )
dptr[k] = sptr[k];
}
else
{
for( int c = 0; c < mcn; c++ )
if( (mptr[c] != 0) ^ invertMask )
for( k = 0; k < elemSize1; k++ )
dptr[k + c * elemSize1] = sptr[k + c * elemSize1];
}
}
}
}
@ -414,25 +426,37 @@ void set(Mat& dst, const Scalar& gamma, const Mat& mask)
return;
}
CV_Assert( dst.size == mask.size && mask.type() == CV_8U );
int cn = dst.channels(), mcn = mask.channels();
CV_Assert( dst.size == mask.size && (mcn == 1 || mcn == cn) );
const Mat *arrays[]={&dst, &mask, 0};
Mat planes[2];
NAryMatIterator it(arrays, planes);
size_t j, k, elemSize = dst.elemSize(), total = planes[0].total();
size_t j, k, elemSize = dst.elemSize(), maskElemSize = mask.elemSize(), total = planes[0].total();
size_t i, nplanes = it.nplanes;
size_t elemSize1 = dst.elemSize1();
for( i = 0; i < nplanes; i++, ++it)
{
uchar* dptr = planes[0].ptr();
const uchar* mptr = planes[1].ptr();
for( j = 0; j < total; j++, dptr += elemSize )
for( j = 0; j < total; j++, dptr += elemSize, mptr += maskElemSize )
{
if( mptr[j] )
for( k = 0; k < elemSize; k++ )
dptr[k] = gptr[k];
if( mcn == 1)
{
if( mptr[0] )
for( k = 0; k < elemSize; k++ )
dptr[k] = gptr[k];
}
else
{
for( int c = 0; c < mcn; c++ )
if( mptr[c] )
for( k = 0; k < elemSize1; k++ )
dptr[k + c * elemSize1] = gptr[k + c * elemSize1];
}
}
}
}