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Merge branch 2.4

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This commit is contained in:
Andrey Kamaev
2012-12-21 17:58:48 +04:00
parent 3edf7c5386 ffdbddd6b1
commit 962884cdec
35 changed files with 1091 additions and 191 deletions
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815
modules/imgproc/src/histogram.cpp
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@@ -165,11 +165,13 @@ static void histPrepareImages( const Mat* images, int nimages, const int* channe
deltas[dims*2 + 1] = (int)(mask.step/mask.elemSize1());
}
#ifndef HAVE_TBB
if( isContinuous )
{
imsize.width *= imsize.height;
imsize.height = 1;
}
#endif
if( !ranges )
{
@@ -207,6 +209,538 @@ static void histPrepareImages( const Mat* images, int nimages, const int* channe
////////////////////////////////// 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:
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:
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:
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,
@@ -234,6 +768,11 @@ calcHist_( vector<uchar*>& _ptrs, const vector<int>& _deltas,
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);
return;
#endif
double a = uniranges[0], b = uniranges[1];
int sz = size[0], d0 = deltas[0], step0 = deltas[1];
const T* p0 = (const T*)ptrs[0];
@@ -259,6 +798,11 @@ calcHist_( vector<uchar*>& _ptrs, const vector<int>& _deltas,
}
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);
return;
#endif
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],
@@ -290,6 +834,14 @@ calcHist_( vector<uchar*>& _ptrs, const vector<int>& _deltas,
}
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];
@@ -441,8 +993,20 @@ calcHist_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
if( dims == 1 )
{
#ifdef HAVE_TBB
if( CalcHist1D_8uInvoker::isFit(hist, imsize) )
{
int treadsNumber = tbb::task_scheduler_init::default_num_threads();
int grainSize = imsize.height/treadsNumber;
tbb::mutex histogramWriteLock;
CalcHist1D_8uInvoker body(_ptrs, _deltas, imsize, hist, dims, _tab, &histogramWriteLock);
parallel_for(BlockedRange(0, imsize.height, grainSize), body);
return;
}
#endif
int d0 = deltas[0], step0 = deltas[1];
int matH[256] = {0};
int matH[256] = { 0, };
const uchar* p0 = (const uchar*)ptrs[0];
for( ; imsize.height--; p0 += step0, mask += mstep )
@@ -489,6 +1053,13 @@ calcHist_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
}
else if( dims == 2 )
{
#ifdef HAVE_TBB
if( CalcHist2D_8uInvoker::isFit(hist, imsize) )
{
callCalcHist2D_8u(_ptrs, _deltas, imsize, hist, dims, _tab);
return;
}
#endif
int d0 = deltas[0], step0 = deltas[1],
d1 = deltas[2], step1 = deltas[3];
const uchar* p0 = (const uchar*)ptrs[0];
@@ -514,6 +1085,13 @@ calcHist_8u( vector<uchar*>& _ptrs, const vector<int>& _deltas,
}
else if( dims == 3 )
{
#ifdef HAVE_TBB
if( CalcHist3D_8uInvoker::isFit(hist, imsize) )
{
callCalcHist3D_8u(_ptrs, _deltas, imsize, hist, dims, _tab);
return;
}
#endif
int d0 = deltas[0], step0 = deltas[1],
d1 = deltas[2], step1 = deltas[3],
d2 = deltas[4], step2 = deltas[5];
@@ -2404,61 +2982,206 @@ cvCalcProbDensity( const CvHistogram* hist, const CvHistogram* hist_mask,
}
}
class EqualizeHistCalcHist_Invoker
{
public:
enum {HIST_SZ = 256};
#ifdef HAVE_TBB
typedef tbb::mutex* MutextPtr;
#else
typedef void* MutextPtr;
#endif
EqualizeHistCalcHist_Invoker(cv::Mat& src, int* histogram, MutextPtr histogramLock)
: src_(src), globalHistogram_(histogram), histogramLock_(histogramLock)
{ }
void operator()( const cv::BlockedRange& rowRange ) const
{
int localHistogram[HIST_SZ] = {0, };
const size_t sstep = src_.step;
int width = src_.cols;
int height = rowRange.end() - rowRange.begin();
if (src_.isContinuous())
{
width *= height;
height = 1;
}
for (const uchar* ptr = src_.ptr<uchar>(rowRange.begin()); height--; ptr += sstep)
{
int x = 0;
for (; x <= width - 4; x += 4)
{
int t0 = ptr[x], t1 = ptr[x+1];
localHistogram[t0]++; localHistogram[t1]++;
t0 = ptr[x+2]; t1 = ptr[x+3];
localHistogram[t0]++; localHistogram[t1]++;
}
for (; x < width; ++x, ++ptr)
localHistogram[ptr[x]]++;
}
#ifdef HAVE_TBB
tbb::mutex::scoped_lock lock(*histogramLock_);
#endif
for( int i = 0; i < HIST_SZ; i++ )
globalHistogram_[i] += localHistogram[i];
}
static bool isWorthParallel( const cv::Mat& src )
{
#ifdef HAVE_TBB
return ( src.total() >= 640*480 );
#else
(void)src;
return false;
#endif
}
private:
EqualizeHistCalcHist_Invoker& operator=(const EqualizeHistCalcHist_Invoker&);
cv::Mat& src_;
int* globalHistogram_;
MutextPtr histogramLock_;
};
class EqualizeHistLut_Invoker
{
public:
EqualizeHistLut_Invoker( cv::Mat& src, cv::Mat& dst, int* lut )
: src_(src),
dst_(dst),
lut_(lut)
{ }
void operator()( const cv::BlockedRange& rowRange ) const
{
const size_t sstep = src_.step;
const size_t dstep = dst_.step;
int width = src_.cols;
int height = rowRange.end() - rowRange.begin();
int* lut = lut_;
if (src_.isContinuous() && dst_.isContinuous())
{
width *= height;
height = 1;
}
const uchar* sptr = src_.ptr<uchar>(rowRange.begin());
uchar* dptr = dst_.ptr<uchar>(rowRange.begin());
for (; height--; sptr += sstep, dptr += dstep)
{
int x = 0;
for (; x <= width - 4; x += 4)
{
int v0 = sptr[x];
int v1 = sptr[x+1];
int x0 = lut[v0];
int x1 = lut[v1];
dptr[x] = (uchar)x0;
dptr[x+1] = (uchar)x1;
v0 = sptr[x+2];
v1 = sptr[x+3];
x0 = lut[v0];
x1 = lut[v1];
dptr[x+2] = (uchar)x0;
dptr[x+3] = (uchar)x1;
}
for (; x < width; ++x)
dptr[x] = (uchar)lut[sptr[x]];
}
}
static bool isWorthParallel( const cv::Mat& src )
{
#ifdef HAVE_TBB
return ( src.total() >= 640*480 );
#else
(void)src;
return false;
#endif
}
private:
EqualizeHistLut_Invoker& operator=(const EqualizeHistLut_Invoker&);
cv::Mat& src_;
cv::Mat& dst_;
int* lut_;
};
CV_IMPL void cvEqualizeHist( const CvArr* srcarr, CvArr* dstarr )
{
CvMat sstub, *src = cvGetMat(srcarr, &sstub);
CvMat dstub, *dst = cvGetMat(dstarr, &dstub);
CV_Assert( CV_ARE_SIZES_EQ(src, dst) && CV_ARE_TYPES_EQ(src, dst) &&
CV_MAT_TYPE(src->type) == CV_8UC1 );
CvSize size = cvGetMatSize(src);
if( CV_IS_MAT_CONT(src->type & dst->type) )
{
size.width *= size.height;
size.height = 1;
}
int x, y;
const int hist_sz = 256;
int hist[hist_sz];
memset(hist, 0, sizeof(hist));
for( y = 0; y < size.height; y++ )
{
const uchar* sptr = src->data.ptr + src->step*y;
for( x = 0; x < size.width; x++ )
hist[sptr[x]]++;
}
float scale = 255.f/(size.width*size.height);
int sum = 0;
uchar lut[hist_sz+1];
for( int i = 0; i < hist_sz; i++ )
{
sum += hist[i];
int val = cvRound(sum*scale);
lut[i] = CV_CAST_8U(val);
}
lut[0] = 0;
for( y = 0; y < size.height; y++ )
{
const uchar* sptr = src->data.ptr + src->step*y;
uchar* dptr = dst->data.ptr + dst->step*y;
for( x = 0; x < size.width; x++ )
dptr[x] = lut[sptr[x]];
}
cv::equalizeHist(cv::cvarrToMat(srcarr), cv::cvarrToMat(dstarr));
}
void cv::equalizeHist( InputArray _src, OutputArray _dst )
{
Mat src = _src.getMat();
CV_Assert( src.type() == CV_8UC1 );
_dst.create( src.size(), src.type() );
Mat dst = _dst.getMat();
CvMat _csrc = src, _cdst = dst;
cvEqualizeHist( &_csrc, &_cdst );
if(src.empty())
return;
#ifdef HAVE_TBB
tbb::mutex histogramLockInstance;
EqualizeHistCalcHist_Invoker::MutextPtr histogramLock = &histogramLockInstance;
#else
EqualizeHistCalcHist_Invoker::MutextPtr histogramLock = 0;
#endif
const int hist_sz = EqualizeHistCalcHist_Invoker::HIST_SZ;
int hist[hist_sz] = {0,};
int lut[hist_sz];
EqualizeHistCalcHist_Invoker calcBody(src, hist, histogramLock);
EqualizeHistLut_Invoker lutBody(src, dst, lut);
cv::BlockedRange heightRange(0, src.rows);
if(EqualizeHistCalcHist_Invoker::isWorthParallel(src))
parallel_for(heightRange, calcBody);
else
calcBody(heightRange);
int i = 0;
while (!hist[i]) ++i;
int total = (int)src.total();
if (hist[i] == total)
{
dst.setTo(i);
return;
}
float scale = (hist_sz - 1.f)/(total - hist[i]);
int sum = 0;
for (lut[i++] = 0; i < hist_sz; ++i)
{
sum += hist[i];
lut[i] = saturate_cast<uchar>(sum * scale);
}
if(EqualizeHistLut_Invoker::isWorthParallel(src))
parallel_for(heightRange, lutBody);
else
lutBody(heightRange);
}
/* Implementation of RTTI and Generic Functions for CvHistogram */