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https://github.com/opencv/opencv.git
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added upright mode to SURF (#825)
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@ -81,6 +81,7 @@ CV_INLINE CvSURFPoint cvSURFPoint( CvPoint2D32f pt, int laplacian,
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typedef struct CvSURFParams
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{
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int extended;
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int upright;
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double hessianThreshold;
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int nOctaves;
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@ -395,7 +396,7 @@ public:
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CV_WRAP SURF();
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//! the full constructor taking all the necessary parameters
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CV_WRAP SURF(double _hessianThreshold, int _nOctaves=4,
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int _nOctaveLayers=2, bool _extended=false);
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int _nOctaveLayers=2, bool _extended=false, bool _upright=false);
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//! returns the descriptor size in float's (64 or 128)
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CV_WRAP int descriptorSize() const;
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@ -1519,7 +1520,7 @@ protected:
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class CV_EXPORTS SurfFeatureDetector : public FeatureDetector
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{
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public:
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SurfFeatureDetector( double hessianThreshold=400., int octaves=3, int octaveLayers=4 );
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SurfFeatureDetector( double hessianThreshold=400., int octaves=3, int octaveLayers=4, bool upright=false );
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virtual void read( const FileNode& fn );
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virtual void write( FileStorage& fs ) const;
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@ -1897,7 +1898,7 @@ protected:
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class CV_EXPORTS SurfDescriptorExtractor : public DescriptorExtractor
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{
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public:
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SurfDescriptorExtractor( int nOctaves=4, int nOctaveLayers=2, bool extended=false );
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SurfDescriptorExtractor( int nOctaves=4, int nOctaveLayers=2, bool extended=false, bool upright=false );
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virtual void read( const FileNode &fn );
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virtual void write( FileStorage &fs ) const;
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@ -1906,7 +1907,7 @@ public:
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virtual int descriptorType() const;
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protected:
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virtual void computeImpl( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const;
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virtual void computeImpl( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors ) const;
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SURF surf;
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};
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@ -191,8 +191,8 @@ int SiftDescriptorExtractor::descriptorType() const
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* SurfDescriptorExtractor *
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\****************************************************************************************/
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SurfDescriptorExtractor::SurfDescriptorExtractor( int nOctaves,
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int nOctaveLayers, bool extended )
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: surf( 0.0, nOctaves, nOctaveLayers, extended )
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int nOctaveLayers, bool extended, bool upright )
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: surf( 0.0, nOctaves, nOctaveLayers, extended, upright )
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{}
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void SurfDescriptorExtractor::computeImpl( const Mat& image,
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@ -218,8 +218,9 @@ void SurfDescriptorExtractor::read( const FileNode &fn )
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int nOctaves = fn["nOctaves"];
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int nOctaveLayers = fn["nOctaveLayers"];
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bool extended = (int)fn["extended"] != 0;
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bool upright = (int)fn["upright"] != 0;
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surf = SURF( 0.0, nOctaves, nOctaveLayers, extended );
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surf = SURF( 0.0, nOctaves, nOctaveLayers, extended, upright );
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}
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void SurfDescriptorExtractor::write( FileStorage &fs ) const
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@ -229,6 +230,7 @@ void SurfDescriptorExtractor::write( FileStorage &fs ) const
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fs << "nOctaves" << surf.nOctaves;
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fs << "nOctaveLayers" << surf.nOctaveLayers;
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fs << "extended" << surf.extended;
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fs << "upright" << surf.upright;
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}
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int SurfDescriptorExtractor::descriptorSize() const
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@ -407,8 +407,8 @@ void SiftFeatureDetector::detectImpl( const Mat& image, vector<KeyPoint>& keypoi
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/*
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* SurfFeatureDetector
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*/
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SurfFeatureDetector::SurfFeatureDetector( double hessianThreshold, int octaves, int octaveLayers)
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: surf(hessianThreshold, octaves, octaveLayers)
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SurfFeatureDetector::SurfFeatureDetector( double hessianThreshold, int octaves, int octaveLayers, bool upright )
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: surf(hessianThreshold, octaves, octaveLayers, false, upright)
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{}
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void SurfFeatureDetector::read (const FileNode& fn)
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@ -416,8 +416,9 @@ void SurfFeatureDetector::read (const FileNode& fn)
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double hessianThreshold = fn["hessianThreshold"];
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int octaves = fn["octaves"];
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int octaveLayers = fn["octaveLayers"];
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bool upright = (int)fn["upright"] != 0;
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surf = SURF( hessianThreshold, octaves, octaveLayers );
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surf = SURF( hessianThreshold, octaves, octaveLayers, false, upright );
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}
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void SurfFeatureDetector::write (FileStorage& fs) const
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@ -427,6 +428,7 @@ void SurfFeatureDetector::write (FileStorage& fs) const
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fs << "hessianThreshold" << surf.hessianThreshold;
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fs << "octaves" << surf.nOctaves;
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fs << "octaveLayers" << surf.nOctaveLayers;
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fs << "upright" << surf.upright;
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}
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void SurfFeatureDetector::detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask ) const
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@ -114,6 +114,7 @@ CvSURFParams cvSURFParams(double threshold, int extended)
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CvSURFParams params;
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params.hessianThreshold = threshold;
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params.extended = extended;
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params.upright = 0;
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params.nOctaves = 4;
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params.nOctaveLayers = 2;
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return params;
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@ -630,94 +631,130 @@ struct SURFInvoker
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kp->size = -1;
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continue;
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}
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icvResizeHaarPattern( dx_s, dx_t, NX, 4, grad_wav_size, sum->cols );
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icvResizeHaarPattern( dy_s, dy_t, NY, 4, grad_wav_size, sum->cols );
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for( kk = 0, nangle = 0; kk < nOriSamples; kk++ )
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{
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const int* ptr;
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float vx, vy;
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x = cvRound( center.x + apt[kk].x*s - (float)(grad_wav_size-1)/2 );
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y = cvRound( center.y + apt[kk].y*s - (float)(grad_wav_size-1)/2 );
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if( (unsigned)y >= (unsigned)(sum->rows - grad_wav_size) ||
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(unsigned)x >= (unsigned)(sum->cols - grad_wav_size) )
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continue;
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ptr = sum_ptr + x + y*sum_cols;
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vx = icvCalcHaarPattern( ptr, dx_t, 2 );
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vy = icvCalcHaarPattern( ptr, dy_t, 2 );
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X[nangle] = vx*aptw[kk]; Y[nangle] = vy*aptw[kk];
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nangle++;
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}
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if ( nangle == 0 )
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{
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/* No gradient could be sampled because the keypoint is too
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* near too one or more of the sides of the image. As we
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* therefore cannot find a dominant direction, we skip this
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* keypoint and mark it for later deletion from the sequence. */
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kp->size = -1;
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continue;
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}
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matX.cols = matY.cols = _angle.cols = nangle;
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cvCartToPolar( &matX, &matY, 0, &_angle, 1 );
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float bestx = 0, besty = 0, descriptor_mod = 0;
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for( i = 0; i < 360; i += ORI_SEARCH_INC )
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float descriptor_dir = 90.f;
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if (params->upright == 0)
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{
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float sumx = 0, sumy = 0, temp_mod;
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for( j = 0; j < nangle; j++ )
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icvResizeHaarPattern( dx_s, dx_t, NX, 4, grad_wav_size, sum->cols );
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icvResizeHaarPattern( dy_s, dy_t, NY, 4, grad_wav_size, sum->cols );
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for( kk = 0, nangle = 0; kk < nOriSamples; kk++ )
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{
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int d = std::abs(cvRound(angle[j]) - i);
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if( d < ORI_WIN/2 || d > 360-ORI_WIN/2 )
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const int* ptr;
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float vx, vy;
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x = cvRound( center.x + apt[kk].x*s - (float)(grad_wav_size-1)/2 );
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y = cvRound( center.y + apt[kk].y*s - (float)(grad_wav_size-1)/2 );
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if( (unsigned)y >= (unsigned)(sum->rows - grad_wav_size) ||
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(unsigned)x >= (unsigned)(sum->cols - grad_wav_size) )
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continue;
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ptr = sum_ptr + x + y*sum_cols;
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vx = icvCalcHaarPattern( ptr, dx_t, 2 );
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vy = icvCalcHaarPattern( ptr, dy_t, 2 );
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X[nangle] = vx*aptw[kk]; Y[nangle] = vy*aptw[kk];
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nangle++;
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}
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if ( nangle == 0 )
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{
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/* No gradient could be sampled because the keypoint is too
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* near too one or more of the sides of the image. As we
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* therefore cannot find a dominant direction, we skip this
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* keypoint and mark it for later deletion from the sequence. */
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kp->size = -1;
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continue;
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}
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matX.cols = matY.cols = _angle.cols = nangle;
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cvCartToPolar( &matX, &matY, 0, &_angle, 1 );
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float bestx = 0, besty = 0, descriptor_mod = 0;
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for( i = 0; i < 360; i += ORI_SEARCH_INC )
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{
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float sumx = 0, sumy = 0, temp_mod;
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for( j = 0; j < nangle; j++ )
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{
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sumx += X[j];
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sumy += Y[j];
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int d = std::abs(cvRound(angle[j]) - i);
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if( d < ORI_WIN/2 || d > 360-ORI_WIN/2 )
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{
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sumx += X[j];
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sumy += Y[j];
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}
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}
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temp_mod = sumx*sumx + sumy*sumy;
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if( temp_mod > descriptor_mod )
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{
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descriptor_mod = temp_mod;
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bestx = sumx;
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besty = sumy;
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}
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}
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temp_mod = sumx*sumx + sumy*sumy;
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if( temp_mod > descriptor_mod )
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{
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descriptor_mod = temp_mod;
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bestx = sumx;
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besty = sumy;
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}
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descriptor_dir = cvFastArctan( besty, bestx );
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}
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float descriptor_dir = cvFastArctan( besty, bestx );
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kp->dir = descriptor_dir;
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if( !descriptors )
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continue;
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descriptor_dir *= (float)(CV_PI/180);
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/* Extract a window of pixels around the keypoint of size 20s */
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int win_size = (int)((PATCH_SZ+1)*s);
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CV_Assert( winbuf->cols >= win_size*win_size );
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CvMat win = cvMat(win_size, win_size, CV_8U, winbuf->data.ptr);
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float sin_dir = sin(descriptor_dir);
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float cos_dir = cos(descriptor_dir) ;
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/* Subpixel interpolation version (slower). Subpixel not required since
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the pixels will all get averaged when we scale down to 20 pixels */
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/*
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float w[] = { cos_dir, sin_dir, center.x,
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-sin_dir, cos_dir , center.y };
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CvMat W = cvMat(2, 3, CV_32F, w);
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cvGetQuadrangleSubPix( img, &win, &W );
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*/
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/* Nearest neighbour version (faster) */
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float win_offset = -(float)(win_size-1)/2;
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float start_x = center.x + win_offset*cos_dir + win_offset*sin_dir;
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float start_y = center.y - win_offset*sin_dir + win_offset*cos_dir;
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uchar* WIN = win.data.ptr;
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for( i = 0; i < win_size; i++, start_x += sin_dir, start_y += cos_dir )
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if (params->upright == 0)
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{
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float pixel_x = start_x;
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float pixel_y = start_y;
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for( j = 0; j < win_size; j++, pixel_x += cos_dir, pixel_y -= sin_dir )
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descriptor_dir *= (float)(CV_PI/180);
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float sin_dir = sin(descriptor_dir);
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float cos_dir = cos(descriptor_dir);
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/* Subpixel interpolation version (slower). Subpixel not required since
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the pixels will all get averaged when we scale down to 20 pixels */
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/*
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float w[] = { cos_dir, sin_dir, center.x,
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-sin_dir, cos_dir , center.y };
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CvMat W = cvMat(2, 3, CV_32F, w);
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cvGetQuadrangleSubPix( img, &win, &W );
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*/
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/* Nearest neighbour version (faster) */
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float win_offset = -(float)(win_size-1)/2;
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float start_x = center.x + win_offset*cos_dir + win_offset*sin_dir;
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float start_y = center.y - win_offset*sin_dir + win_offset*cos_dir;
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uchar* WIN = win.data.ptr;
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for( i = 0; i < win_size; i++, start_x += sin_dir, start_y += cos_dir )
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{
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int x = std::min(std::max(cvRound(pixel_x), 0), img->cols-1);
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int y = std::min(std::max(cvRound(pixel_y), 0), img->rows-1);
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WIN[i*win_size + j] = img->data.ptr[y*img->step + x];
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float pixel_x = start_x;
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float pixel_y = start_y;
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for( j = 0; j < win_size; j++, pixel_x += cos_dir, pixel_y -= sin_dir )
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{
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int x = std::min(std::max(cvRound(pixel_x), 0), img->cols-1);
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int y = std::min(std::max(cvRound(pixel_y), 0), img->rows-1);
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WIN[i*win_size + j] = img->data.ptr[y*img->step + x];
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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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/* extract rect - slightly optimized version of the code above
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TODO: find faster code, as this is simply an extract rect operation,
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e.g. by using cvGetSubRect, problem is the border processing */
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// descriptor_dir == 90 grad
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// sin_dir == 1
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// cos_dir == 0
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float win_offset = -(float)(win_size-1)/2;
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int start_x = cvRound(center.x + win_offset);
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int start_y = cvRound(center.y - win_offset);
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uchar* WIN = win.data.ptr;
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for( i = 0; i < win_size; i++, start_x++ )
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{
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int pixel_x = start_x;
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int pixel_y = start_y;
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for( j=0; j<win_size; j++, pixel_y-- )
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{
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x = MAX( pixel_x, 0 );
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y = MAX( pixel_y, 0 );
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x = MIN( x, img->cols-1 );
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y = MIN( y, img->rows-1 );
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WIN[i*win_size + j] = img->data.ptr[y*img->step+x];
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}
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}
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}
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/* Scale the window to size PATCH_SZ so each pixel's size is s. This
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makes calculating the gradients with wavelets of size 2s easy */
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cvResize( &win, &_patch, CV_INTER_AREA );
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@ -886,8 +923,8 @@ cvExtractSURF( const CvArr* _img, const CvArr* _mask,
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cv::parallel_for(cv::BlockedRange(0, N),
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cv::SURFInvoker(¶ms, keypoints, descriptors, img, sum) );
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#else
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cv::SURFInvoker invoker(¶ms, keypoints, descriptors, img, sum);
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invoker(cv::BlockedRange(0, N));
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cv::SURFInvoker invoker(¶ms, keypoints, descriptors, img, sum);
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invoker(cv::BlockedRange(0, N));
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#endif
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}
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@ -924,14 +961,16 @@ SURF::SURF()
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{
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hessianThreshold = 100;
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extended = 1;
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upright = 0;
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nOctaves = 4;
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nOctaveLayers = 2;
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}
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SURF::SURF(double _threshold, int _nOctaves, int _nOctaveLayers, bool _extended)
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SURF::SURF(double _threshold, int _nOctaves, int _nOctaveLayers, bool _extended, bool _upright)
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{
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hessianThreshold = _threshold;
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extended = _extended;
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upright = _upright;
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nOctaves = _nOctaves;
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nOctaveLayers = _nOctaveLayers;
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}
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