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3328 lines (2903 loc) · 103 KB
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
namespace cv
{
template<> void Ptr<CvHistogram>::delete_obj()
{ cvReleaseHist(&obj); }
////////////////// Helper functions //////////////////////
static const size_t OUT_OF_RANGE = (size_t)1 << (sizeof(size_t)*8 - 2);
static void
calcHistLookupTables_8u( const Mat& hist, const SparseMat& shist,
int dims, const float** ranges, const double* uniranges,
bool uniform, bool issparse, vector<size_t>& _tab )
{
const int low = 0, high = 256;
int i, j;
_tab.resize((high-low)*dims);
size_t* tab = &_tab[0];
if( uniform )
{
for( i = 0; i < dims; i++ )
{
double a = uniranges[i*2];
double b = uniranges[i*2+1];
int sz = !issparse ? hist.size[i] : shist.size(i);
size_t step = !issparse ? hist.step[i] : 1;
for( j = low; j < high; j++ )
{
int idx = cvFloor(j*a + b);
size_t written_idx;
if( (unsigned)idx < (unsigned)sz )
written_idx = idx*step;
else
written_idx = OUT_OF_RANGE;
tab[i*(high - low) + j - low] = written_idx;
}
}
}
else
{
for( i = 0; i < dims; i++ )
{
int limit = std::min(cvCeil(ranges[i][0]), high);
int idx = -1, sz = !issparse ? hist.size[i] : shist.size(i);
size_t written_idx = OUT_OF_RANGE;
size_t step = !issparse ? hist.step[i] : 1;
for(j = low;;)
{
for( ; j < limit; j++ )
tab[i*(high - low) + j - low] = written_idx;
if( (unsigned)(++idx) < (unsigned)sz )
{
limit = std::min(cvCeil(ranges[i][idx+1]), high);
written_idx = idx*step;
}
else
{
for( ; j < high; j++ )
tab[i*(high - low) + j - low] = OUT_OF_RANGE;
break;
}
}
}
}
}
static void histPrepareImages( const Mat* images, int nimages, const int* channels,
const Mat& mask, int dims, const int* histSize,
const float** ranges, bool uniform,
vector<uchar*>& ptrs, vector<int>& deltas,
Size& imsize, vector<double>& uniranges )
{
int i, j, c;
CV_Assert( channels != 0 || nimages == dims );
imsize = images[0].size();
int depth = images[0].depth(), esz1 = (int)images[0].elemSize1();
bool isContinuous = true;
ptrs.resize(dims + 1);
deltas.resize((dims + 1)*2);
for( i = 0; i < dims; i++ )
{
if(!channels)
{
j = i;
c = 0;
CV_Assert( images[j].channels() == 1 );
}
else
{
c = channels[i];
CV_Assert( c >= 0 );
for( j = 0; j < nimages; c -= images[j].channels(), j++ )
if( c < images[j].channels() )
break;
CV_Assert( j < nimages );
}
CV_Assert( images[j].size() == imsize && images[j].depth() == depth );
if( !images[j].isContinuous() )
isContinuous = false;
ptrs[i] = images[j].data + c*esz1;
deltas[i*2] = images[j].channels();
deltas[i*2+1] = (int)(images[j].step/esz1 - imsize.width*deltas[i*2]);
}
if( mask.data )
{
CV_Assert( mask.size() == imsize && mask.channels() == 1 );
isContinuous = isContinuous && mask.isContinuous();
ptrs[dims] = mask.data;
deltas[dims*2] = 1;
deltas[dims*2 + 1] = (int)(mask.step/mask.elemSize1());
}
#ifndef HAVE_TBB
if( isContinuous )
{
imsize.width *= imsize.height;
imsize.height = 1;
}
#endif
if( !ranges )
{
CV_Assert( depth == CV_8U );
uniranges.resize( dims*2 );
for( i = 0; i < dims; i++ )
{
uniranges[i*2] = histSize[i]/256.;
uniranges[i*2+1] = 0;
}
}
else if( uniform )
{
uniranges.resize( dims*2 );
for( i = 0; i < dims; i++ )
{
CV_Assert( ranges[i] && ranges[i][0] < ranges[i][1] );
double low = ranges[i][0], high = ranges[i][1];
double t = histSize[i]/(high - low);
uniranges[i*2] = t;
uniranges[i*2+1] = -t*low;
}
}
else
{
for( i = 0; i < dims; i++ )
{
size_t n = histSize[i];
for(size_t k = 0; k < n; k++ )
CV_Assert( ranges[i][k] < ranges[i][k+1] );
}
}
}
////////////////////////////////// C A L C U L A T E H I S T O G R A M ////////////////////////////////////
#ifdef HAVE_TBB
enum {one = 1, two, three}; // array elements number
template<typename T>
class calcHist1D_Invoker
{
public:
calcHist1D_Invoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
Mat& hist, const double* _uniranges, int sz, int dims,
Size& imageSize )
: mask_(_ptrs[dims]),
mstep_(_deltas[dims*2 + 1]),
imageWidth_(imageSize.width),
histogramSize_(hist.size()), histogramType_(hist.type()),
globalHistogram_((tbb::atomic<int>*)hist.data)
{
p_[0] = ((T**)&_ptrs[0])[0];
step_[0] = (&_deltas[0])[1];
d_[0] = (&_deltas[0])[0];
a_[0] = (&_uniranges[0])[0];
b_[0] = (&_uniranges[0])[1];
size_[0] = sz;
}
void operator()( const BlockedRange& range ) const
{
T* p0 = p_[0] + range.begin() * (step_[0] + imageWidth_*d_[0]);
uchar* mask = mask_ + range.begin()*mstep_;
for( int row = range.begin(); row < range.end(); row++, p0 += step_[0] )
{
if( !mask_ )
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0] )
{
int idx = cvFloor(*p0*a_[0] + b_[0]);
if( (unsigned)idx < (unsigned)size_[0] )
{
globalHistogram_[idx].fetch_and_add(1);
}
}
}
else
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0] )
{
if( mask[x] )
{
int idx = cvFloor(*p0*a_[0] + b_[0]);
if( (unsigned)idx < (unsigned)size_[0] )
{
globalHistogram_[idx].fetch_and_add(1);
}
}
}
mask += mstep_;
}
}
}
private:
calcHist1D_Invoker operator=(const calcHist1D_Invoker&);
T* p_[one];
uchar* mask_;
int step_[one];
int d_[one];
int mstep_;
double a_[one];
double b_[one];
int size_[one];
int imageWidth_;
Size histogramSize_;
int histogramType_;
tbb::atomic<int>* globalHistogram_;
};
template<typename T>
class calcHist2D_Invoker
{
public:
calcHist2D_Invoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
Mat& hist, const double* _uniranges, const int* size,
int dims, Size& imageSize, size_t* hstep )
: mask_(_ptrs[dims]),
mstep_(_deltas[dims*2 + 1]),
imageWidth_(imageSize.width),
histogramSize_(hist.size()), histogramType_(hist.type()),
globalHistogram_(hist.data)
{
p_[0] = ((T**)&_ptrs[0])[0]; p_[1] = ((T**)&_ptrs[0])[1];
step_[0] = (&_deltas[0])[1]; step_[1] = (&_deltas[0])[3];
d_[0] = (&_deltas[0])[0]; d_[1] = (&_deltas[0])[2];
a_[0] = (&_uniranges[0])[0]; a_[1] = (&_uniranges[0])[2];
b_[0] = (&_uniranges[0])[1]; b_[1] = (&_uniranges[0])[3];
size_[0] = size[0]; size_[1] = size[1];
hstep_[0] = hstep[0];
}
void operator()(const BlockedRange& range) const
{
T* p0 = p_[0] + range.begin()*(step_[0] + imageWidth_*d_[0]);
T* p1 = p_[1] + range.begin()*(step_[1] + imageWidth_*d_[1]);
uchar* mask = mask_ + range.begin()*mstep_;
for( int row = range.begin(); row < range.end(); row++, p0 += step_[0], p1 += step_[1] )
{
if( !mask_ )
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1] )
{
int idx0 = cvFloor(*p0*a_[0] + b_[0]);
int idx1 = cvFloor(*p1*a_[1] + b_[1]);
if( (unsigned)idx0 < (unsigned)size_[0] && (unsigned)idx1 < (unsigned)size_[1] )
( (tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0) )[idx1].fetch_and_add(1);
}
}
else
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1] )
{
if( mask[x] )
{
int idx0 = cvFloor(*p0*a_[0] + b_[0]);
int idx1 = cvFloor(*p1*a_[1] + b_[1]);
if( (unsigned)idx0 < (unsigned)size_[0] && (unsigned)idx1 < (unsigned)size_[1] )
((tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0))[idx1].fetch_and_add(1);
}
}
mask += mstep_;
}
}
}
private:
calcHist2D_Invoker operator=(const calcHist2D_Invoker&);
T* p_[two];
uchar* mask_;
int step_[two];
int d_[two];
int mstep_;
double a_[two];
double b_[two];
int size_[two];
const int imageWidth_;
size_t hstep_[one];
Size histogramSize_;
int histogramType_;
uchar* globalHistogram_;
};
template<typename T>
class calcHist3D_Invoker
{
public:
calcHist3D_Invoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, const double* uniranges, int _dims,
size_t* hstep, int* size )
: mask_(_ptrs[_dims]),
mstep_(_deltas[_dims*2 + 1]),
imageWidth_(imsize.width),
globalHistogram_(hist.data)
{
p_[0] = ((T**)&_ptrs[0])[0]; p_[1] = ((T**)&_ptrs[0])[1]; p_[2] = ((T**)&_ptrs[0])[2];
step_[0] = (&_deltas[0])[1]; step_[1] = (&_deltas[0])[3]; step_[2] = (&_deltas[0])[5];
d_[0] = (&_deltas[0])[0]; d_[1] = (&_deltas[0])[2]; d_[2] = (&_deltas[0])[4];
a_[0] = uniranges[0]; a_[1] = uniranges[2]; a_[2] = uniranges[4];
b_[0] = uniranges[1]; b_[1] = uniranges[3]; b_[2] = uniranges[5];
size_[0] = size[0]; size_[1] = size[1]; size_[2] = size[2];
hstep_[0] = hstep[0]; hstep_[1] = hstep[1];
}
void operator()( const BlockedRange& range ) const
{
T* p0 = p_[0] + range.begin()*(imageWidth_*d_[0] + step_[0]);
T* p1 = p_[1] + range.begin()*(imageWidth_*d_[1] + step_[1]);
T* p2 = p_[2] + range.begin()*(imageWidth_*d_[2] + step_[2]);
uchar* mask = mask_ + range.begin()*mstep_;
for( int i = range.begin(); i < range.end(); i++, p0 += step_[0], p1 += step_[1], p2 += step_[2] )
{
if( !mask_ )
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1], p2 += d_[2] )
{
int idx0 = cvFloor(*p0*a_[0] + b_[0]);
int idx1 = cvFloor(*p1*a_[1] + b_[1]);
int idx2 = cvFloor(*p2*a_[2] + b_[2]);
if( (unsigned)idx0 < (unsigned)size_[0] &&
(unsigned)idx1 < (unsigned)size_[1] &&
(unsigned)idx2 < (unsigned)size_[2] )
{
( (tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0 + hstep_[1]*idx1) )[idx2].fetch_and_add(1);
}
}
}
else
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1], p2 += d_[2] )
{
if( mask[x] )
{
int idx0 = cvFloor(*p0*a_[0] + b_[0]);
int idx1 = cvFloor(*p1*a_[1] + b_[1]);
int idx2 = cvFloor(*p2*a_[2] + b_[2]);
if( (unsigned)idx0 < (unsigned)size_[0] &&
(unsigned)idx1 < (unsigned)size_[1] &&
(unsigned)idx2 < (unsigned)size_[2] )
{
( (tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0 + hstep_[1]*idx1) )[idx2].fetch_and_add(1);
}
}
}
mask += mstep_;
}
}
}
static bool isFit( const Mat& histogram, const Size imageSize )
{
return ( imageSize.width * imageSize.height >= 320*240
&& histogram.total() >= 8*8*8 );
}
private:
calcHist3D_Invoker operator=(const calcHist3D_Invoker&);
T* p_[three];
uchar* mask_;
int step_[three];
int d_[three];
const int mstep_;
double a_[three];
double b_[three];
int size_[three];
int imageWidth_;
size_t hstep_[two];
uchar* globalHistogram_;
};
class CalcHist1D_8uInvoker
{
public:
CalcHist1D_8uInvoker( const vector<uchar*>& ptrs, const vector<int>& deltas,
Size imsize, Mat& hist, int dims, const vector<size_t>& tab,
tbb::mutex* lock )
: mask_(ptrs[dims]),
mstep_(deltas[dims*2 + 1]),
imageWidth_(imsize.width),
imageSize_(imsize),
histSize_(hist.size()), histType_(hist.type()),
tab_((size_t*)&tab[0]),
histogramWriteLock_(lock),
globalHistogram_(hist.data)
{
p_[0] = (&ptrs[0])[0];
step_[0] = (&deltas[0])[1];
d_[0] = (&deltas[0])[0];
}
void operator()( const BlockedRange& range ) const
{
int localHistogram[256] = { 0, };
uchar* mask = mask_;
uchar* p0 = p_[0];
int x;
tbb::mutex::scoped_lock lock;
if( !mask_ )
{
int n = (imageWidth_ - 4) / 4 + 1;
int tail = imageWidth_ - n*4;
int xN = 4*n;
p0 += (xN*d_[0] + tail*d_[0] + step_[0]) * range.begin();
}
else
{
p0 += (imageWidth_*d_[0] + step_[0]) * range.begin();
mask += mstep_*range.begin();
}
for( int i = range.begin(); i < range.end(); i++, p0 += step_[0] )
{
if( !mask_ )
{
if( d_[0] == 1 )
{
for( x = 0; x <= imageWidth_ - 4; x += 4 )
{
int t0 = p0[x], t1 = p0[x+1];
localHistogram[t0]++; localHistogram[t1]++;
t0 = p0[x+2]; t1 = p0[x+3];
localHistogram[t0]++; localHistogram[t1]++;
}
p0 += x;
}
else
{
for( x = 0; x <= imageWidth_ - 4; x += 4 )
{
int t0 = p0[0], t1 = p0[d_[0]];
localHistogram[t0]++; localHistogram[t1]++;
p0 += d_[0]*2;
t0 = p0[0]; t1 = p0[d_[0]];
localHistogram[t0]++; localHistogram[t1]++;
p0 += d_[0]*2;
}
}
for( ; x < imageWidth_; x++, p0 += d_[0] )
{
localHistogram[*p0]++;
}
}
else
{
for( x = 0; x < imageWidth_; x++, p0 += d_[0] )
{
if( mask[x] )
{
localHistogram[*p0]++;
}
}
mask += mstep_;
}
}
lock.acquire(*histogramWriteLock_);
for(int i = 0; i < 256; i++ )
{
size_t hidx = tab_[i];
if( hidx < OUT_OF_RANGE )
{
*(int*)((globalHistogram_ + hidx)) += localHistogram[i];
}
}
lock.release();
}
static bool isFit( const Mat& histogram, const Size imageSize )
{
return ( histogram.total() >= 8
&& imageSize.width * imageSize.height >= 160*120 );
}
private:
uchar* p_[one];
uchar* mask_;
int mstep_;
int step_[one];
int d_[one];
int imageWidth_;
Size imageSize_;
Size histSize_;
int histType_;
size_t* tab_;
tbb::mutex* histogramWriteLock_;
uchar* globalHistogram_;
};
class CalcHist2D_8uInvoker
{
public:
CalcHist2D_8uInvoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, int dims, const vector<size_t>& _tab,
tbb::mutex* lock )
: mask_(_ptrs[dims]),
mstep_(_deltas[dims*2 + 1]),
imageWidth_(imsize.width),
histSize_(hist.size()), histType_(hist.type()),
tab_((size_t*)&_tab[0]),
histogramWriteLock_(lock),
globalHistogram_(hist.data)
{
p_[0] = (uchar*)(&_ptrs[0])[0]; p_[1] = (uchar*)(&_ptrs[0])[1];
step_[0] = (&_deltas[0])[1]; step_[1] = (&_deltas[0])[3];
d_[0] = (&_deltas[0])[0]; d_[1] = (&_deltas[0])[2];
}
void operator()( const BlockedRange& range ) const
{
uchar* p0 = p_[0] + range.begin()*(step_[0] + imageWidth_*d_[0]);
uchar* p1 = p_[1] + range.begin()*(step_[1] + imageWidth_*d_[1]);
uchar* mask = mask_ + range.begin()*mstep_;
Mat localHist = Mat::zeros(histSize_, histType_);
uchar* localHistData = localHist.data;
tbb::mutex::scoped_lock lock;
for(int i = range.begin(); i < range.end(); i++, p0 += step_[0], p1 += step_[1])
{
if( !mask_ )
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1] )
{
size_t idx = tab_[*p0] + tab_[*p1 + 256];
if( idx < OUT_OF_RANGE )
{
++*(int*)(localHistData + idx);
}
}
}
else
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1] )
{
size_t idx;
if( mask[x] && (idx = tab_[*p0] + tab_[*p1 + 256]) < OUT_OF_RANGE )
{
++*(int*)(localHistData + idx);
}
}
mask += mstep_;
}
}
lock.acquire(*histogramWriteLock_);
for(int i = 0; i < histSize_.width*histSize_.height; i++)
{
((int*)globalHistogram_)[i] += ((int*)localHistData)[i];
}
lock.release();
}
static bool isFit( const Mat& histogram, const Size imageSize )
{
return ( (histogram.total() > 4*4 && histogram.total() <= 116*116
&& imageSize.width * imageSize.height >= 320*240)
|| (histogram.total() > 116*116 && imageSize.width * imageSize.height >= 1280*720) );
}
private:
uchar* p_[two];
uchar* mask_;
int step_[two];
int d_[two];
int mstep_;
int imageWidth_;
Size histSize_;
int histType_;
size_t* tab_;
tbb::mutex* histogramWriteLock_;
uchar* globalHistogram_;
};
class CalcHist3D_8uInvoker
{
public:
CalcHist3D_8uInvoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, int dims, const vector<size_t>& tab )
: mask_(_ptrs[dims]),
mstep_(_deltas[dims*2 + 1]),
histogramSize_(hist.size.p), histogramType_(hist.type()),
imageWidth_(imsize.width),
tab_((size_t*)&tab[0]),
globalHistogram_(hist.data)
{
p_[0] = (uchar*)(&_ptrs[0])[0]; p_[1] = (uchar*)(&_ptrs[0])[1]; p_[2] = (uchar*)(&_ptrs[0])[2];
step_[0] = (&_deltas[0])[1]; step_[1] = (&_deltas[0])[3]; step_[2] = (&_deltas[0])[5];
d_[0] = (&_deltas[0])[0]; d_[1] = (&_deltas[0])[2]; d_[2] = (&_deltas[0])[4];
}
void operator()( const BlockedRange& range ) const
{
uchar* p0 = p_[0] + range.begin()*(step_[0] + imageWidth_*d_[0]);
uchar* p1 = p_[1] + range.begin()*(step_[1] + imageWidth_*d_[1]);
uchar* p2 = p_[2] + range.begin()*(step_[2] + imageWidth_*d_[2]);
uchar* mask = mask_ + range.begin()*mstep_;
for(int i = range.begin(); i < range.end(); i++, p0 += step_[0], p1 += step_[1], p2 += step_[2] )
{
if( !mask_ )
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1], p2 += d_[2] )
{
size_t idx = tab_[*p0] + tab_[*p1 + 256] + tab_[*p2 + 512];
if( idx < OUT_OF_RANGE )
{
( *(tbb::atomic<int>*)(globalHistogram_ + idx) ).fetch_and_add(1);
}
}
}
else
{
for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1], p2 += d_[2] )
{
size_t idx;
if( mask[x] && (idx = tab_[*p0] + tab_[*p1 + 256] + tab_[*p2 + 512]) < OUT_OF_RANGE )
{
(*(tbb::atomic<int>*)(globalHistogram_ + idx)).fetch_and_add(1);
}
}
mask += mstep_;
}
}
}
static bool isFit( const Mat& histogram, const Size imageSize )
{
return ( histogram.total() >= 128*128*128
&& imageSize.width * imageSize.width >= 320*240 );
}
private:
uchar* p_[three];
uchar* mask_;
int mstep_;
int step_[three];
int d_[three];
int* histogramSize_;
int histogramType_;
int imageWidth_;
size_t* tab_;
uchar* globalHistogram_;
};
static void
callCalcHist2D_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, int dims, vector<size_t>& _tab )
{
int grainSize = imsize.height / tbb::task_scheduler_init::default_num_threads();
tbb::mutex histogramWriteLock;
CalcHist2D_8uInvoker body(_ptrs, _deltas, imsize, hist, dims, _tab, &histogramWriteLock);
parallel_for(BlockedRange(0, imsize.height, grainSize), body);
}
static void
callCalcHist3D_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, int dims, vector<size_t>& _tab )
{
CalcHist3D_8uInvoker body(_ptrs, _deltas, imsize, hist, dims, _tab);
parallel_for(BlockedRange(0, imsize.height), body);
}
#endif
template<typename T> static void
calcHist_( vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, int dims, const float** _ranges,
const double* _uniranges, bool uniform )
{
T** ptrs = (T**)&_ptrs[0];
const int* deltas = &_deltas[0];
uchar* H = hist.data;
int i, x;
const uchar* mask = _ptrs[dims];
int mstep = _deltas[dims*2 + 1];
int size[CV_MAX_DIM];
size_t hstep[CV_MAX_DIM];
for( i = 0; i < dims; i++ )
{
size[i] = hist.size[i];
hstep[i] = hist.step[i];
}
if( uniform )
{
const double* uniranges = &_uniranges[0];
if( dims == 1 )
{
#ifdef HAVE_TBB
calcHist1D_Invoker<T> body(_ptrs, _deltas, hist, _uniranges, size[0], dims, imsize);
parallel_for(BlockedRange(0, imsize.height), body);
#else
double a = uniranges[0], b = uniranges[1];
int sz = size[0], d0 = deltas[0], step0 = deltas[1];
const T* p0 = (const T*)ptrs[0];
for( ; imsize.height--; p0 += step0, mask += mstep )
{
if( !mask )
for( x = 0; x < imsize.width; x++, p0 += d0 )
{
int idx = cvFloor(*p0*a + b);
if( (unsigned)idx < (unsigned)sz )
((int*)H)[idx]++;
}
else
for( x = 0; x < imsize.width; x++, p0 += d0 )
if( mask[x] )
{
int idx = cvFloor(*p0*a + b);
if( (unsigned)idx < (unsigned)sz )
((int*)H)[idx]++;
}
}
#endif //HAVE_TBB
return;
}
else if( dims == 2 )
{
#ifdef HAVE_TBB
calcHist2D_Invoker<T> body(_ptrs, _deltas, hist, _uniranges, size, dims, imsize, hstep);
parallel_for(BlockedRange(0, imsize.height), body);
#else
double a0 = uniranges[0], b0 = uniranges[1], a1 = uniranges[2], b1 = uniranges[3];
int sz0 = size[0], sz1 = size[1];
int d0 = deltas[0], step0 = deltas[1],
d1 = deltas[2], step1 = deltas[3];
size_t hstep0 = hstep[0];
const T* p0 = (const T*)ptrs[0];
const T* p1 = (const T*)ptrs[1];
for( ; imsize.height--; p0 += step0, p1 += step1, mask += mstep )
{
if( !mask )
for( x = 0; x < imsize.width; x++, p0 += d0, p1 += d1 )
{
int idx0 = cvFloor(*p0*a0 + b0);
int idx1 = cvFloor(*p1*a1 + b1);
if( (unsigned)idx0 < (unsigned)sz0 && (unsigned)idx1 < (unsigned)sz1 )
((int*)(H + hstep0*idx0))[idx1]++;
}
else
for( x = 0; x < imsize.width; x++, p0 += d0, p1 += d1 )
if( mask[x] )
{
int idx0 = cvFloor(*p0*a0 + b0);
int idx1 = cvFloor(*p1*a1 + b1);
if( (unsigned)idx0 < (unsigned)sz0 && (unsigned)idx1 < (unsigned)sz1 )
((int*)(H + hstep0*idx0))[idx1]++;
}
}
#endif //HAVE_TBB
return;
}
else if( dims == 3 )
{
#ifdef HAVE_TBB
if( calcHist3D_Invoker<T>::isFit(hist, imsize) )
{
calcHist3D_Invoker<T> body(_ptrs, _deltas, imsize, hist, uniranges, dims, hstep, size);
parallel_for(BlockedRange(0, imsize.height), body);
return;
}
#endif
double a0 = uniranges[0], b0 = uniranges[1],
a1 = uniranges[2], b1 = uniranges[3],
a2 = uniranges[4], b2 = uniranges[5];
int sz0 = size[0], sz1 = size[1], sz2 = size[2];
int d0 = deltas[0], step0 = deltas[1],
d1 = deltas[2], step1 = deltas[3],
d2 = deltas[4], step2 = deltas[5];
size_t hstep0 = hstep[0], hstep1 = hstep[1];
const T* p0 = (const T*)ptrs[0];
const T* p1 = (const T*)ptrs[1];
const T* p2 = (const T*)ptrs[2];
for( ; imsize.height--; p0 += step0, p1 += step1, p2 += step2, mask += mstep )
{
if( !mask )
for( x = 0; x < imsize.width; x++, p0 += d0, p1 += d1, p2 += d2 )
{
int idx0 = cvFloor(*p0*a0 + b0);
int idx1 = cvFloor(*p1*a1 + b1);
int idx2 = cvFloor(*p2*a2 + b2);
if( (unsigned)idx0 < (unsigned)sz0 &&
(unsigned)idx1 < (unsigned)sz1 &&
(unsigned)idx2 < (unsigned)sz2 )
((int*)(H + hstep0*idx0 + hstep1*idx1))[idx2]++;
}
else
for( x = 0; x < imsize.width; x++, p0 += d0, p1 += d1, p2 += d2 )
if( mask[x] )
{
int idx0 = cvFloor(*p0*a0 + b0);
int idx1 = cvFloor(*p1*a1 + b1);
int idx2 = cvFloor(*p2*a2 + b2);
if( (unsigned)idx0 < (unsigned)sz0 &&
(unsigned)idx1 < (unsigned)sz1 &&
(unsigned)idx2 < (unsigned)sz2 )
((int*)(H + hstep0*idx0 + hstep1*idx1))[idx2]++;
}
}
}
else
{
for( ; imsize.height--; mask += mstep )
{
if( !mask )
for( x = 0; x < imsize.width; x++ )
{
uchar* Hptr = H;
for( i = 0; i < dims; i++ )
{
int idx = cvFloor(*ptrs[i]*uniranges[i*2] + uniranges[i*2+1]);
if( (unsigned)idx >= (unsigned)size[i] )
break;
ptrs[i] += deltas[i*2];
Hptr += idx*hstep[i];
}
if( i == dims )
++*((int*)Hptr);
else
for( ; i < dims; i++ )
ptrs[i] += deltas[i*2];
}
else
for( x = 0; x < imsize.width; x++ )
{
uchar* Hptr = H;
i = 0;
if( mask[x] )
for( ; i < dims; i++ )
{
int idx = cvFloor(*ptrs[i]*uniranges[i*2] + uniranges[i*2+1]);
if( (unsigned)idx >= (unsigned)size[i] )
break;
ptrs[i] += deltas[i*2];
Hptr += idx*hstep[i];
}
if( i == dims )
++*((int*)Hptr);
else
for( ; i < dims; i++ )
ptrs[i] += deltas[i*2];
}
for( i = 0; i < dims; i++ )
ptrs[i] += deltas[i*2 + 1];
}
}
}
else
{
// non-uniform histogram
const float* ranges[CV_MAX_DIM];
for( i = 0; i < dims; i++ )
ranges[i] = &_ranges[i][0];
for( ; imsize.height--; mask += mstep )
{
for( x = 0; x < imsize.width; x++ )
{
uchar* Hptr = H;
i = 0;
if( !mask || mask[x] )
for( ; i < dims; i++ )
{
float v = (float)*ptrs[i];
const float* R = ranges[i];
int idx = -1, sz = size[i];
while( v >= R[idx+1] && ++idx < sz )
; // nop
if( (unsigned)idx >= (unsigned)sz )
break;
ptrs[i] += deltas[i*2];
Hptr += idx*hstep[i];
}
if( i == dims )
++*((int*)Hptr);
else
for( ; i < dims; i++ )
ptrs[i] += deltas[i*2];
}
for( i = 0; i < dims; i++ )
ptrs[i] += deltas[i*2 + 1];
}
}
}
static void
calcHist_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
Size imsize, Mat& hist, int dims, const float** _ranges,
const double* _uniranges, bool uniform )
{
uchar** ptrs = &_ptrs[0];
const int* deltas = &_deltas[0];
uchar* H = hist.data;
int x;
const uchar* mask = _ptrs[dims];
int mstep = _deltas[dims*2 + 1];
vector<size_t> _tab;
calcHistLookupTables_8u( hist, SparseMat(), dims, _ranges, _uniranges, uniform, false, _tab );
const size_t* tab = &_tab[0];