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replaced SIFT implementation (Some default parameters can be changed in the near future)
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@ -269,7 +269,7 @@ CV_EXPORTS void read(const FileNode& node, CV_OUT vector<KeyPoint>& keypoints);
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/*
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* A class filters a vector of keypoints.
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* Because now it is difficult to provide a convenient interface for all usage scenarios of the keypoints filter class,
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* it has only 3 needed by now static methods.
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* it has only 4 needed by now static methods.
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*/
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class CV_EXPORTS KeyPointsFilter
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{
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@ -288,6 +288,10 @@ public:
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* Remove keypoints from some image by mask for pixels of this image.
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*/
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static void runByPixelsMask( vector<KeyPoint>& keypoints, const Mat& mask );
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/*
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* Remove duplicated keypoints.
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*/
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static void removeDuplicated( vector<KeyPoint>& keypoints );
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};
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/*!
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@ -295,6 +299,7 @@ public:
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The class implements SIFT algorithm by D. Lowe.
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*/
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class CV_EXPORTS SIFT
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{
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public:
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@ -306,14 +311,15 @@ public:
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enum { FIRST_ANGLE = 0, AVERAGE_ANGLE = 1 };
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CommonParams();
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CommonParams( int _nOctaves, int _nOctaveLayers, int _firstOctave, int _angleMode );
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int nOctaves, nOctaveLayers, firstOctave;
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int angleMode;
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CommonParams( int _nOctaves, int _nOctaveLayers, int /*_firstOctave*/, int /*_angleMode*/ );
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int nOctaves, nOctaveLayers;
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int firstOctave; // it is not used now (firstOctave == 0 always)
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int angleMode; // it is not used now
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};
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struct CV_EXPORTS DetectorParams
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{
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static double GET_DEFAULT_THRESHOLD() { return 0.04 / SIFT::CommonParams::DEFAULT_NOCTAVE_LAYERS / 2.0; }
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static double GET_DEFAULT_THRESHOLD() { return 0.04; }
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static double GET_DEFAULT_EDGE_THRESHOLD() { return 10.0; }
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DetectorParams();
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@ -328,9 +334,10 @@ public:
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static const int DESCRIPTOR_SIZE = 128;
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DescriptorParams();
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DescriptorParams( double _magnification, bool _isNormalize, bool _recalculateAngles );
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DescriptorParams( double _magnification, bool /*_isNormalize*/, bool _recalculateAngles );
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DescriptorParams( bool _recalculateAngles );
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double magnification;
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bool isNormalize;
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bool isNormalize; // it is not used now (true always)
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bool recalculateAngles;
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};
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@ -234,4 +234,65 @@ void KeyPointsFilter::runByPixelsMask( vector<KeyPoint>& keypoints, const Mat& m
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keypoints.erase(remove_if(keypoints.begin(), keypoints.end(), MaskPredicate(mask)), keypoints.end());
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}
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struct KeyPoint_LessThan
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{
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KeyPoint_LessThan(const vector<KeyPoint>& _kp) : kp(&_kp) {}
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bool operator()(int i, int j) const
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{
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const KeyPoint& kp1 = (*kp)[i];
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const KeyPoint& kp2 = (*kp)[j];
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if( kp1.pt.x != kp2.pt.x )
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return kp1.pt.x < kp2.pt.x;
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if( kp1.pt.y != kp2.pt.y )
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return kp1.pt.y < kp2.pt.y;
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if( kp1.size != kp2.size )
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return kp1.size > kp2.size;
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if( kp1.size != kp2.size )
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return kp1.size > kp2.size;
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if( kp1.angle != kp2.angle )
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return kp1.angle < kp2.angle;
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if( kp1.response != kp2.response )
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return kp1.response > kp2.response;
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if( kp1.octave != kp2.octave )
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return kp1.octave > kp2.octave;
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if( kp1.class_id != kp2.class_id )
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return kp1.class_id > kp2.class_id;
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return i < j;
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}
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const vector<KeyPoint>* kp;
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};
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void KeyPointsFilter::removeDuplicated( vector<KeyPoint>& keypoints )
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{
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int i, j, n = (int)keypoints.size();
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vector<int> kpidx(n);
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vector<uchar> mask(n, (uchar)1);
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for( i = 0; i < n; i++ )
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kpidx[i] = i;
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std::sort(kpidx.begin(), kpidx.end(), KeyPoint_LessThan(keypoints));
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for( i = 1, j = 0; i < n; i++ )
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{
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KeyPoint& kp1 = keypoints[kpidx[i]];
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KeyPoint& kp2 = keypoints[kpidx[j]];
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if( kp1.pt.x != kp2.pt.x || kp1.pt.y != kp2.pt.y ||
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kp1.size != kp2.size || kp1.angle != kp2.angle )
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j = i;
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else
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mask[kpidx[i]] = 0;
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}
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for( i = j = 0; i < n; i++ )
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{
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if( mask[i] )
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{
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if( i != j )
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keypoints[j] = keypoints[i];
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j++;
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}
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}
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keypoints.resize(j);
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}
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}
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