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Commit d8513d62 authored by Vadim Pisarevsky's avatar Vadim Pisarevsky
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continue adding OpenCL optimization to cascade classifier

parent 302a5adc
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Showing with 63 additions and 40 deletions
modules/objdetect/include/opencv2/objdetect.hpp
View file @ d8513d62
......@@ -111,12 +111,15 @@ public:
};
CV_EXPORTS void groupRectangles(std::vector<Rect>& rectList, int groupThreshold, double eps = 0.2);
CV_EXPORTS_W void groupRectangles(CV_IN_OUT std::vector<Rect>& rectList, CV_OUT std::vector<int>& weights, int groupThreshold, double eps = 0.2);
CV_EXPORTS void groupRectangles(std::vector<Rect>& rectList, int groupThreshold, double eps, std::vector<int>* weights, std::vector<double>* levelWeights );
CV_EXPORTS_W void groupRectangles(CV_IN_OUT std::vector<Rect>& rectList, CV_OUT std::vector<int>& weights,
int groupThreshold, double eps = 0.2);
CV_EXPORTS void groupRectangles(std::vector<Rect>& rectList, int groupThreshold,
double eps, std::vector<int>* weights, std::vector<double>* levelWeights );
CV_EXPORTS void groupRectangles(std::vector<Rect>& rectList, std::vector<int>& rejectLevels,
std::vector<double>& levelWeights, int groupThreshold, double eps = 0.2);
CV_EXPORTS void groupRectangles_meanshift(std::vector<Rect>& rectList, std::vector<double>& foundWeights, std::vector<double>& foundScales,
double detectThreshold = 0.0, Size winDetSize = Size(64, 128));
CV_EXPORTS void groupRectangles_meanshift(std::vector<Rect>& rectList, std::vector<double>& foundWeights,
std::vector<double>& foundScales,
double detectThreshold = 0.0, Size winDetSize = Size(64, 128));
class CV_EXPORTS FeatureEvaluator
{
......@@ -132,7 +135,7 @@ public:
virtual Ptr<FeatureEvaluator> clone() const;
virtual int getFeatureType() const;
virtual bool setImage(const Mat& img, Size origWinSize);
virtual bool setImage(InputArray img, Size origWinSize);
virtual bool setWindow(Point p);
virtual double calcOrd(int featureIdx) const;
......
modules/objdetect/src/cascadedetect.cpp
View file @ d8513d62
This diff is collapsed.
modules/objdetect/src/cascadedetect.hpp
View file @ d8513d62
......@@ -49,11 +49,17 @@ public:
Ptr<MaskGenerator> getMaskGenerator();
protected:
bool detectSingleScale( const Mat& image, int stripCount, Size processingRectSize,
int stripSize, int yStep, double factor, std::vector<Rect>& candidates,
std::vector<int>& rejectLevels, std::vector<double>& levelWeights, bool outputRejectLevels = false );
void detectMultiScaleNoGrouping( const Mat& image, std::vector<Rect>& candidates,
bool detectSingleScale( InputArray image, Size processingRectSize,
int yStep, double factor, std::vector<Rect>& candidates,
std::vector<int>& rejectLevels, std::vector<double>& levelWeights,
bool outputRejectLevels = false );
bool ocl_detectSingleScale( InputArray image, Size processingRectSize,
int yStep, double factor, std::vector<Rect>& candidates,
std::vector<int>& rejectLevels, std::vector<double>& levelWeights,
bool outputRejectLevels = false );
void detectMultiScaleNoGrouping( InputArray image, std::vector<Rect>& candidates,
std::vector<int>& rejectLevels, std::vector<double>& levelWeights,
double scaleFactor, Size minObjectSize, Size maxObjectSize,
bool outputRejectLevels = false );
......@@ -127,6 +133,12 @@ protected:
Ptr<CvHaarClassifierCascade> oldCascade;
Ptr<MaskGenerator> maskGenerator;
UMat ugrayImage, uimageBuffer;
UMat ufacepos, ustages, uclassifiers, unodes, uleaves, usubsets;
ocl::Kernel cascadeKernel;
bool tryOpenCL;
Mutex mtx;
};
#define CC_CASCADE_PARAMS "cascadeParams"
......@@ -212,6 +224,10 @@ protected:
#define CALC_SUM(rect,offset) CALC_SUM_((rect)[0], (rect)[1], (rect)[2], (rect)[3], offset)
#define CALC_SUM_OFS_(p0, p1, p2, p3, ptr) \
((ptr)[p0] - (ptr)[p1] - (ptr)[p2] + (ptr)[p3])
#define CALC_SUM_OFS(rect, ptr) CALC_SUM_OFS_((rect)[0], (rect)[1], (rect)[2], (rect)[3], ptr)
//---------------------------------------------- HaarEvaluator ---------------------------------------
class HaarEvaluator : public FeatureEvaluator
......@@ -241,10 +257,10 @@ public:
enum { RECT_NUM = Feature::RECT_NUM };
float calc( const int* pwin ) const;
void setPtrs( const Mat& sum, const Feature& f );
void setOffsets( const Feature& _f, int step, int tofs );
int ofs[RECT_NUM][4];
float weight[RECT_NUM];
float weight[4];
};
HaarEvaluator();
......@@ -254,8 +270,11 @@ public:
virtual Ptr<FeatureEvaluator> clone() const;
virtual int getFeatureType() const { return FeatureEvaluator::HAAR; }
virtual bool setImage(const Mat&, Size origWinSize);
virtual bool setImage(InputArray, Size origWinSize);
virtual bool setWindow(Point pt);
virtual bool setUMat(InputArray, Size origWinSize, Size origImgSize);
virtual void getUMats(std::vector<UMat>& bufs);
double operator()(int featureIdx) const
{ return optfeaturesPtr[featureIdx].calc(pwin) * varianceNormFactor; }
......@@ -263,22 +282,22 @@ public:
{ return (*this)(featureIdx); }
protected:
Size origWinSize;
std::vector<Feature> features;
std::vector<OptFeature> optfeatures;
Size origWinSize, origImgSize;
Ptr<std::vector<Feature> > features;
Ptr<std::vector<OptFeature> > optfeatures;
OptFeature* optfeaturesPtr; // optimization
bool hasTiltedFeatures;
Mat sum0, sqsum0, tilted0;
Mat sum0, sqsum0;
Mat sum, sqsum, tilted;
UMat usum, usqsum, fbuf;
Rect normrect;
int p[4];
int pq[4];
int nofs[4];
int nqofs[4];
const int* pwin;
const double* pqwin;
int offset;
double varianceNormFactor;
};
......@@ -298,34 +317,35 @@ inline HaarEvaluator::OptFeature :: OptFeature()
ofs[2][0] = ofs[2][1] = ofs[2][2] = ofs[2][3] = 0;
}
/*inline float HaarEvaluator::Feature :: calc( int _offset ) const
inline float HaarEvaluator::OptFeature :: calc( const int* ptr ) const
{
float ret = rect[0].weight * CALC_SUM(p[0], _offset) + rect[1].weight * CALC_SUM(p[1], _offset);
float ret = weight[0] * CALC_SUM_OFS(ofs[0], ptr) +
weight[1] * CALC_SUM_OFS(ofs[1], ptr);
if( rect[2].weight != 0.0f )
ret += rect[2].weight * CALC_SUM(p[2], _offset);
if( weight[2] != 0.0f )
ret += weight[2] * CALC_SUM_OFS(ofs[2], ptr);
return ret;
}*/
}
inline void HaarEvaluator::OptFeature :: setPtrs( const Mat& _sum, const Feature& _f )
inline void HaarEvaluator::OptFeature :: setOffsets( const Feature& _f, int step, int tofs )
{
const int* ptr = (const int*)_sum.data;
size_t step = _sum.step/sizeof(ptr[0]);
size_t tiltedofs =
if (tilted)
weight[0] = _f.rect[0].weight;
weight[1] = _f.rect[1].weight;
weight[2] = _f.rect[2].weight;
if (_f.tilted)
{
CV_TILTED_PTRS( p[0][0], p[0][1], p[0][2], p[0][3], ptr, rect[0].r, step );
CV_TILTED_PTRS( p[1][0], p[1][1], p[1][2], p[1][3], ptr, rect[1].r, step );
if (rect[2].weight)
CV_TILTED_PTRS( p[2][0], p[2][1], p[2][2], p[2][3], ptr, rect[2].r, step );
CV_TILTED_OFS( ofs[0][0], ofs[0][1], ofs[0][2], ofs[0][3], tofs, _f.rect[0].r, step );
CV_TILTED_OFS( ofs[1][0], ofs[1][1], ofs[1][2], ofs[1][3], tofs, _f.rect[1].r, step );
if (weight[2])
CV_TILTED_PTRS( ofs[2][0], ofs[2][1], ofs[2][2], ofs[2][3], tofs, _f.rect[2].r, step );
}
else
{
CV_SUM_PTRS( p[0][0], p[0][1], p[0][2], p[0][3], ptr, rect[0].r, step );
CV_SUM_PTRS( p[1][0], p[1][1], p[1][2], p[1][3], ptr, rect[1].r, step );
if (rect[2].weight)
CV_SUM_PTRS( p[2][0], p[2][1], p[2][2], p[2][3], ptr, rect[2].r, step );
CV_SUM_OFS( ofs[0][0], ofs[0][1], ofs[0][2], ofs[0][3], 0, _f.rect[0].r, step );
CV_SUM_OFS( ofs[1][0], ofs[1][1], ofs[1][2], ofs[1][3], 0, _f.rect[1].r, step );
if (weight[2])
CV_SUM_OFS( ofs[2][0], ofs[2][1], ofs[2][2], ofs[2][3], 0, _f.rect[2].r, step );
}
}
......@@ -356,7 +376,7 @@ public:
virtual Ptr<FeatureEvaluator> clone() const;
virtual int getFeatureType() const { return FeatureEvaluator::LBP; }
virtual bool setImage(const Mat& image, Size _origWinSize);
virtual bool setImage(InputArray image, Size _origWinSize);
virtual bool setWindow(Point pt);
int operator()(int featureIdx) const
......@@ -433,7 +453,7 @@ public:
virtual bool read( const FileNode& node );
virtual Ptr<FeatureEvaluator> clone() const;
virtual int getFeatureType() const { return FeatureEvaluator::HOG; }
virtual bool setImage( const Mat& image, Size winSize );
virtual bool setImage( InputArray image, Size winSize );
virtual bool setWindow( Point pt );
double operator()(int featureIdx) const
{
......
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