Merge pull request #202 from Daniil-Osokin:calcHist
This commit is contained in:
Andrey Kamaev
OpenCV Buildbot
commit
b35fa6c4ff
@ -9,14 +9,14 @@ using std::tr1::get;
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typedef tr1::tuple<Size, MatType> Size_Source_t;
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typedef TestBaseWithParam<Size_Source_t> Size_Source;
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typedef TestBaseWithParam<Size> MatSize;
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static const float rangeHight = 256.0f;
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static const float rangeLow = 0.0f;
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PERF_TEST_P(Size_Source, calcHist,
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testing::Combine(testing::Values(TYPICAL_MAT_SIZES),
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testing::Values(CV_8U, CV_32F)
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)
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PERF_TEST_P(Size_Source, calcHist1d,
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testing::Combine(testing::Values(sz3MP, sz5MP),
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testing::Values(CV_8U, CV_16U, CV_32F) )
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)
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{
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Size size = get<0>(GetParam());
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@ -28,10 +28,69 @@ PERF_TEST_P(Size_Source, calcHist,
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int dims = 1;
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int numberOfImages = 1;
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const float r[] = {0.0f, 256.0f};
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const float r[] = {rangeLow, rangeHight};
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const float* ranges[] = {r};
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declare.in(source, WARMUP_RNG).time(20).iterations(1000);
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randu(source, rangeLow, rangeHight);
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declare.in(source);
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TEST_CYCLE()
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{
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calcHist(&source, numberOfImages, channels, Mat(), hist, dims, histSize, ranges);
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}
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SANITY_CHECK(hist);
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}
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PERF_TEST_P(Size_Source, calcHist2d,
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testing::Combine(testing::Values(sz3MP, sz5MP),
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testing::Values(CV_8UC2, CV_16UC2, CV_32FC2) )
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)
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{
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Size size = get<0>(GetParam());
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MatType type = get<1>(GetParam());
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Mat source(size.height, size.width, type);
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Mat hist;
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int channels [] = {0, 1};
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int histSize [] = {256, 256};
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int dims = 2;
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int numberOfImages = 1;
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const float r[] = {rangeLow, rangeHight};
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const float* ranges[] = {r, r};
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randu(source, rangeLow, rangeHight);
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declare.in(source);
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TEST_CYCLE()
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{
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calcHist(&source, numberOfImages, channels, Mat(), hist, dims, histSize, ranges);
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}
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SANITY_CHECK(hist);
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}
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PERF_TEST_P(Size_Source, calcHist3d,
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testing::Combine(testing::Values(sz3MP, sz5MP),
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testing::Values(CV_8UC3, CV_16UC3, CV_32FC3) )
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)
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{
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Size size = get<0>(GetParam());
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MatType type = get<1>(GetParam());
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Mat hist;
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int channels [] = {0, 1, 2};
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int histSize [] = {32, 32, 32};
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int dims = 3;
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int numberOfImages = 1;
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Mat source(size.height, size.width, type);
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const float r[] = {rangeLow, rangeHight};
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const float* ranges[] = {r, r, r};
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randu(source, rangeLow, rangeHight);
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declare.in(source);
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TEST_CYCLE()
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{
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calcHist(&source, numberOfImages, channels, Mat(), hist, dims, histSize, ranges);
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@ -165,11 +165,13 @@ static void histPrepareImages( const Mat* images, int nimages, const int* channe
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deltas[dims*2 + 1] = (int)(mask.step/mask.elemSize1());
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}
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#ifndef HAVE_TBB
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if( isContinuous )
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{
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imsize.width *= imsize.height;
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imsize.height = 1;
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}
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#endif
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if( !ranges )
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{
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@ -207,6 +209,538 @@ static void histPrepareImages( const Mat* images, int nimages, const int* channe
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////////////////////////////////// C A L C U L A T E H I S T O G R A M ////////////////////////////////////
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#ifdef HAVE_TBB
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enum {one = 1, two, three}; // array elements number
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template<typename T>
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class calcHist1D_Invoker
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{
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public:
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calcHist1D_Invoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
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Mat& hist, const double* _uniranges, int sz, int dims,
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Size& imageSize )
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: mask_(_ptrs[dims]),
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mstep_(_deltas[dims*2 + 1]),
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imageWidth_(imageSize.width),
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histogramSize_(hist.size()), histogramType_(hist.type()),
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globalHistogram_((tbb::atomic<int>*)hist.data)
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{
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p_[0] = ((T**)&_ptrs[0])[0];
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step_[0] = (&_deltas[0])[1];
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d_[0] = (&_deltas[0])[0];
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a_[0] = (&_uniranges[0])[0];
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b_[0] = (&_uniranges[0])[1];
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size_[0] = sz;
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}
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void operator()( const BlockedRange& range ) const
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{
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T* p0 = p_[0] + range.begin() * (step_[0] + imageWidth_*d_[0]);
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uchar* mask = mask_ + range.begin()*mstep_;
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for( int row = range.begin(); row < range.end(); row++, p0 += step_[0] )
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{
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if( !mask_ )
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{
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for( int x = 0; x < imageWidth_; x++, p0 += d_[0] )
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{
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int idx = cvFloor(*p0*a_[0] + b_[0]);
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if( (unsigned)idx < (unsigned)size_[0] )
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{
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globalHistogram_[idx].fetch_and_add(1);
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}
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}
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}
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else
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{
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for( int x = 0; x < imageWidth_; x++, p0 += d_[0] )
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{
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if( mask[x] )
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{
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int idx = cvFloor(*p0*a_[0] + b_[0]);
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if( (unsigned)idx < (unsigned)size_[0] )
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{
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globalHistogram_[idx].fetch_and_add(1);
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}
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}
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}
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mask += mstep_;
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}
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}
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}
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private:
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T* p_[one];
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uchar* mask_;
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int step_[one];
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int d_[one];
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int mstep_;
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double a_[one];
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double b_[one];
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int size_[one];
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int imageWidth_;
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Size histogramSize_;
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int histogramType_;
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tbb::atomic<int>* globalHistogram_;
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};
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template<typename T>
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class calcHist2D_Invoker
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{
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public:
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calcHist2D_Invoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
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Mat& hist, const double* _uniranges, const int* size,
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int dims, Size& imageSize, size_t* hstep )
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: mask_(_ptrs[dims]),
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mstep_(_deltas[dims*2 + 1]),
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imageWidth_(imageSize.width),
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histogramSize_(hist.size()), histogramType_(hist.type()),
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globalHistogram_(hist.data)
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{
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p_[0] = ((T**)&_ptrs[0])[0]; p_[1] = ((T**)&_ptrs[0])[1];
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step_[0] = (&_deltas[0])[1]; step_[1] = (&_deltas[0])[3];
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d_[0] = (&_deltas[0])[0]; d_[1] = (&_deltas[0])[2];
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a_[0] = (&_uniranges[0])[0]; a_[1] = (&_uniranges[0])[2];
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b_[0] = (&_uniranges[0])[1]; b_[1] = (&_uniranges[0])[3];
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size_[0] = size[0]; size_[1] = size[1];
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hstep_[0] = hstep[0];
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}
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void operator()(const BlockedRange& range) const
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{
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T* p0 = p_[0] + range.begin()*(step_[0] + imageWidth_*d_[0]);
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T* p1 = p_[1] + range.begin()*(step_[1] + imageWidth_*d_[1]);
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uchar* mask = mask_ + range.begin()*mstep_;
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for( int row = range.begin(); row < range.end(); row++, p0 += step_[0], p1 += step_[1] )
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{
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if( !mask_ )
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{
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for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1] )
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{
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int idx0 = cvFloor(*p0*a_[0] + b_[0]);
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int idx1 = cvFloor(*p1*a_[1] + b_[1]);
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if( (unsigned)idx0 < (unsigned)size_[0] && (unsigned)idx1 < (unsigned)size_[1] )
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( (tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0) )[idx1].fetch_and_add(1);
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}
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}
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else
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{
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for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1] )
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{
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if( mask[x] )
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{
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int idx0 = cvFloor(*p0*a_[0] + b_[0]);
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int idx1 = cvFloor(*p1*a_[1] + b_[1]);
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if( (unsigned)idx0 < (unsigned)size_[0] && (unsigned)idx1 < (unsigned)size_[1] )
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((tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0))[idx1].fetch_and_add(1);
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}
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}
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mask += mstep_;
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}
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}
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}
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private:
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T* p_[two];
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uchar* mask_;
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int step_[two];
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int d_[two];
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int mstep_;
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double a_[two];
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double b_[two];
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int size_[two];
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const int imageWidth_;
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size_t hstep_[one];
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Size histogramSize_;
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int histogramType_;
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uchar* globalHistogram_;
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};
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template<typename T>
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class calcHist3D_Invoker
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{
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public:
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calcHist3D_Invoker( const vector<uchar*>& _ptrs, const vector<int>& _deltas,
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Size imsize, Mat& hist, const double* uniranges, int _dims,
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size_t* hstep, int* size )
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: mask_(_ptrs[_dims]),
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mstep_(_deltas[_dims*2 + 1]),
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imageWidth_(imsize.width),
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globalHistogram_(hist.data)
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{
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p_[0] = ((T**)&_ptrs[0])[0]; p_[1] = ((T**)&_ptrs[0])[1]; p_[2] = ((T**)&_ptrs[0])[2];
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step_[0] = (&_deltas[0])[1]; step_[1] = (&_deltas[0])[3]; step_[2] = (&_deltas[0])[5];
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d_[0] = (&_deltas[0])[0]; d_[1] = (&_deltas[0])[2]; d_[2] = (&_deltas[0])[4];
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a_[0] = uniranges[0]; a_[1] = uniranges[2]; a_[2] = uniranges[4];
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b_[0] = uniranges[1]; b_[1] = uniranges[3]; b_[2] = uniranges[5];
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size_[0] = size[0]; size_[1] = size[1]; size_[2] = size[2];
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hstep_[0] = hstep[0]; hstep_[1] = hstep[1];
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}
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void operator()( const BlockedRange& range ) const
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{
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T* p0 = p_[0] + range.begin()*(imageWidth_*d_[0] + step_[0]);
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T* p1 = p_[1] + range.begin()*(imageWidth_*d_[1] + step_[1]);
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T* p2 = p_[2] + range.begin()*(imageWidth_*d_[2] + step_[2]);
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uchar* mask = mask_ + range.begin()*mstep_;
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for( int i = range.begin(); i < range.end(); i++, p0 += step_[0], p1 += step_[1], p2 += step_[2] )
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{
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if( !mask_ )
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{
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for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1], p2 += d_[2] )
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{
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int idx0 = cvFloor(*p0*a_[0] + b_[0]);
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int idx1 = cvFloor(*p1*a_[1] + b_[1]);
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int idx2 = cvFloor(*p2*a_[2] + b_[2]);
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if( (unsigned)idx0 < (unsigned)size_[0] &&
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(unsigned)idx1 < (unsigned)size_[1] &&
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(unsigned)idx2 < (unsigned)size_[2] )
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{
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( (tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0 + hstep_[1]*idx1) )[idx2].fetch_and_add(1);
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}
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}
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}
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else
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{
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for( int x = 0; x < imageWidth_; x++, p0 += d_[0], p1 += d_[1], p2 += d_[2] )
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{
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if( mask[x] )
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{
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int idx0 = cvFloor(*p0*a_[0] + b_[0]);
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int idx1 = cvFloor(*p1*a_[1] + b_[1]);
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int idx2 = cvFloor(*p2*a_[2] + b_[2]);
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if( (unsigned)idx0 < (unsigned)size_[0] &&
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(unsigned)idx1 < (unsigned)size_[1] &&
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(unsigned)idx2 < (unsigned)size_[2] )
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{
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( (tbb::atomic<int>*)(globalHistogram_ + hstep_[0]*idx0 + hstep_[1]*idx1) )[idx2].fetch_and_add(1);
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}
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}
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}
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mask += mstep_;
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}
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}
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}
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static bool isFit( const Mat& histogram, const Size imageSize )
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{
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return ( imageSize.width * imageSize.height >= 320*240
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&& histogram.total() >= 8*8*8 );
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}
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private:
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T* p_[three];
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uchar* mask_;
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int step_[three];
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int d_[three];
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const int mstep_;
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double a_[three];
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double b_[three];
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int size_[three];
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int imageWidth_;
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size_t hstep_[two];
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uchar* globalHistogram_;
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};
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class CalcHist1D_8uInvoker
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{
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public:
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CalcHist1D_8uInvoker( const vector<uchar*>& ptrs, const vector<int>& deltas,
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Size imsize, Mat& hist, int dims, const vector<size_t>& tab,
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tbb::mutex* lock )
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: mask_(ptrs[dims]),
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mstep_(deltas[dims*2 + 1]),
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imageWidth_(imsize.width),
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imageSize_(imsize),
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histSize_(hist.size()), histType_(hist.type()),
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tab_((size_t*)&tab[0]),
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histogramWriteLock_(lock),
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globalHistogram_(hist.data)
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{
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p_[0] = (&ptrs[0])[0];
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step_[0] = (&deltas[0])[1];
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d_[0] = (&deltas[0])[0];
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}
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void operator()( const BlockedRange& range ) const
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{
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int localHistogram[256] = { 0, };
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uchar* mask = mask_;
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uchar* p0 = p_[0];
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int x;
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tbb::mutex::scoped_lock lock;
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if( !mask_ )
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{
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int n = (imageWidth_ - 4) / 4 + 1;
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int tail = imageWidth_ - n*4;
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int xN = 4*n;
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p0 += (xN*d_[0] + tail*d_[0] + step_[0]) * range.begin();
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}
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else
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{
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p0 += (imageWidth_*d_[0] + step_[0]) * range.begin();
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mask += mstep_*range.begin();
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}
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for( int i = range.begin(); i < range.end(); i++, p0 += step_[0] )
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{
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if( !mask_ )
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{
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if( d_[0] == 1 )
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{
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for( x = 0; x <= imageWidth_ - 4; x += 4 )
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{
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int t0 = p0[x], t1 = p0[x+1];
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localHistogram[t0]++; localHistogram[t1]++;
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t0 = p0[x+2]; t1 = p0[x+3];
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localHistogram[t0]++; localHistogram[t1]++;
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}
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p0 += x;
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}
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else
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{
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for( x = 0; x <= imageWidth_ - 4; x += 4 )
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{
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int t0 = p0[0], t1 = p0[d_[0]];
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localHistogram[t0]++; localHistogram[t1]++;
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p0 += d_[0]*2;
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t0 = p0[0]; t1 = p0[d_[0]];
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localHistogram[t0]++; localHistogram[t1]++;
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p0 += d_[0]*2;
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}
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}
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for( ; x < imageWidth_; x++, p0 += d_[0] )
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{
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localHistogram[*p0]++;
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}
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}
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else
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{
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for( x = 0; x < imageWidth_; x++, p0 += d_[0] )
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{
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if( mask[x] )
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{
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localHistogram[*p0]++;
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}
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}
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mask += mstep_;
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}
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}
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lock.acquire(*histogramWriteLock_);
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for(int i = 0; i < 256; i++ )
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{
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size_t hidx = tab_[i];
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if( hidx < OUT_OF_RANGE )
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{
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*(int*)((globalHistogram_ + hidx)) += localHistogram[i];
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}
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}
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lock.release();
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}
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static bool isFit( const Mat& histogram, const Size imageSize )
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{
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return ( histogram.total() >= 8
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&& imageSize.width * imageSize.height >= 160*120 );
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}
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private:
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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];
|
||||
|
||||
Loading…
Reference in New Issue
Block a user