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fixed #1044
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@ -266,7 +266,7 @@ 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 2 needed by now static methods.
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* it has only 3 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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@ -281,6 +281,10 @@ public:
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* Remove keypoints of sizes out of range.
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*/
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static void runByKeypointSize( vector<KeyPoint>& keypoints, float minSize, float maxSize=std::numeric_limits<float>::max() );
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/*
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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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/*!
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@ -1243,13 +1247,7 @@ public:
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static Ptr<FeatureDetector> create( const string& detectorType );
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protected:
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virtual void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const = 0;
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/*
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* Remove keypoints that are not in the mask.
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* Helper function, useful when wrapping a library call for keypoint detection that
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* does not support a mask argument.
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*/
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static void removeInvalidPoints( const Mat& mask, vector<KeyPoint>& keypoints );
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virtual void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const = 0;
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};
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class CV_EXPORTS FastFeatureDetector : public FeatureDetector
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@ -48,17 +48,6 @@ namespace cv
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/*
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* FeatureDetector
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*/
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class MaskPredicate
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{
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public:
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MaskPredicate( const Mat& _mask ) : mask(_mask) {}
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bool operator() (const KeyPoint& key_pt) const
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{
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return mask.at<uchar>( (int)(key_pt.pt.y + 0.5f), (int)(key_pt.pt.x + 0.5f) ) == 0;
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}
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private:
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const Mat mask;
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};
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FeatureDetector::~FeatureDetector()
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{}
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@ -82,14 +71,6 @@ void FeatureDetector::detect(const vector<Mat>& imageCollection, vector<vector<K
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detect( imageCollection[i], pointCollection[i], masks.empty() ? Mat() : masks[i] );
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}
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void FeatureDetector::removeInvalidPoints( const Mat& mask, vector<KeyPoint>& keypoints )
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{
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if( mask.empty() )
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return;
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keypoints.erase(remove_if(keypoints.begin(), keypoints.end(), MaskPredicate(mask)), keypoints.end());
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};
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void FeatureDetector::read( const FileNode& )
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{}
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@ -179,7 +160,7 @@ void FastFeatureDetector::detectImpl( const Mat& image, vector<KeyPoint>& keypoi
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Mat grayImage = image;
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if( image.type() != CV_8U ) cvtColor( image, grayImage, CV_BGR2GRAY );
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FAST( grayImage, keypoints, threshold, nonmaxSuppression );
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removeInvalidPoints( mask, keypoints );
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KeyPointsFilter::runByPixelsMask( keypoints, mask );
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}
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/*
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@ -360,7 +341,7 @@ void StarFeatureDetector::detectImpl( const Mat& image, vector<KeyPoint>& keypoi
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if( image.type() != CV_8U ) cvtColor( image, grayImage, CV_BGR2GRAY );
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star(grayImage, keypoints);
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removeInvalidPoints(mask, keypoints);
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KeyPointsFilter::runByPixelsMask( keypoints, mask );
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}
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/*
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@ -482,7 +463,7 @@ void DenseFeatureDetector::detectImpl( const Mat& image, vector<KeyPoint>& keypo
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if( params.varyImgBoundWithScale ) curBound = static_cast<int>( curBound * params.featureScaleMul + 0.5f );
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}
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removeInvalidPoints( mask, keypoints );
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KeyPointsFilter::runByPixelsMask( keypoints, mask );
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}
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/*
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@ -566,7 +547,7 @@ void PyramidAdaptedFeatureDetector::detectImpl( const Mat& image, vector<KeyPoin
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{
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// Detect on current level of the pyramid
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vector<KeyPoint> new_pts;
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detector->detect(src, new_pts);
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detector->detect( src, new_pts, mask );
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for( vector<KeyPoint>::iterator it = new_pts.begin(), end = new_pts.end(); it != end; ++it)
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{
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it->pt.x *= multiplier;
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@ -574,7 +555,6 @@ void PyramidAdaptedFeatureDetector::detectImpl( const Mat& image, vector<KeyPoin
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it->size *= multiplier;
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it->octave = l;
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}
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removeInvalidPoints( mask, new_pts );
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keypoints.insert( keypoints.end(), new_pts.begin(), new_pts.end() );
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// Downsample
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@ -200,4 +200,25 @@ void KeyPointsFilter::runByKeypointSize( vector<KeyPoint>& keypoints, float minS
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keypoints.end() );
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}
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class MaskPredicate
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{
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public:
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MaskPredicate( const Mat& _mask ) : mask(_mask) {}
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bool operator() (const KeyPoint& key_pt) const
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{
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return mask.at<uchar>( (int)(key_pt.pt.y + 0.5f), (int)(key_pt.pt.x + 0.5f) ) == 0;
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}
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private:
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const Mat mask;
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};
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void KeyPointsFilter::runByPixelsMask( vector<KeyPoint>& keypoints, const Mat& mask )
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{
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if( mask.empty() )
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return;
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keypoints.erase(remove_if(keypoints.begin(), keypoints.end(), MaskPredicate(mask)), keypoints.end());
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}
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}
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@ -2194,16 +2194,49 @@ static void removeDuplicatedKeypoints(vector<KeyPoint>& keypoints)
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keypoints.resize(j);
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}
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// detectors
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void SIFT::operator()(const Mat& img, const Mat& mask,
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void SIFT::operator()(const Mat& image, const Mat& mask,
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vector<KeyPoint>& keypoints) const
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{
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if( img.empty() || img.type() != CV_8UC1 )
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CV_Error( CV_StsBadArg, "img is empty or has incorrect type" );
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if( image.empty() || image.type() != CV_8UC1 )
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CV_Error( CV_StsBadArg, "image is empty or has incorrect type (!=CV_8UC1)" );
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if( !mask.empty() && mask.type() != CV_8UC1 )
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CV_Error( CV_StsBadArg, "mask has incorrect type (!=CV_8UC1)" );
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Mat subImage, subMask;
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Rect brect( 0, 0, image.cols, image.rows );
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if( mask.empty() )
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{
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subImage = image;
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}
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else
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{
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vector<Point> points;
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points.reserve( image.rows * image.cols );
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for( int y = 0; y < mask.rows; y++ )
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{
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for( int x = 0; x < mask.cols; x++ )
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{
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if( mask.at<uchar>(y,x) )
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points.push_back( cv::Point(x,y) );
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}
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}
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brect = cv::boundingRect( points );
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if( brect.x == 0 && brect.y == 0 && brect.width == mask.cols && brect.height == mask.rows )
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{
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subImage = image;
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}
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else
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{
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subImage = image( brect );
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subMask = mask( brect );
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}
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}
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Mat fimg;
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img.convertTo(fimg, CV_32FC1, 1.0/255.0);
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subImage.convertTo( fimg, CV_32FC1, 1.0/255.0 );
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const double sigman = .5 ;
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const double sigma0 = 1.6 * powf(2.0f, 1.0f / commParams.nOctaveLayers) ;
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@ -2225,7 +2258,20 @@ void SIFT::operator()(const Mat& img, const Mat& mask,
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keypoints.push_back( vlKeypointToOcv(vlsift, *iter, angleVal*a_180divPI) );
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}
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}
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removeDuplicatedKeypoints(keypoints);
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if( !subMask.empty() )
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{
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// filter points by subMask and convert the points coordinates from subImage size to image size
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KeyPointsFilter::runByPixelsMask( keypoints, subMask );
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int dx = brect.x, dy = brect.y;
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for( vector<KeyPoint>::iterator it = keypoints.begin(); it != keypoints.end(); ++it )
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{
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it->pt.x += dx;
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it->pt.y += dy;
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}
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}
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}
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struct InvalidKeypoint
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@ -2234,16 +2280,16 @@ struct InvalidKeypoint
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};
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// descriptors
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void SIFT::operator()(const Mat& img, const Mat& mask,
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void SIFT::operator()(const Mat& image, const Mat& mask,
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vector<KeyPoint>& keypoints,
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Mat& descriptors,
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bool useProvidedKeypoints) const
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{
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if( img.empty() || img.type() != CV_8UC1 )
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if( image.empty() || image.type() != CV_8UC1 )
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CV_Error( CV_StsBadArg, "img is empty or has incorrect type" );
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Mat fimg;
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img.convertTo(fimg, CV_32FC1, 1.0/255.0);
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image.convertTo(fimg, CV_32FC1, 1.0/255.0);
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const double sigman = .5 ;
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const double sigma0 = 1.6 * powf(2.0f, 1.0f / commParams.nOctaveLayers) ;
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@ -2251,7 +2297,12 @@ void SIFT::operator()(const Mat& img, const Mat& mask,
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const double a_PIdiv180 = CV_PI/180.;
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if( !useProvidedKeypoints )
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(*this)(img, mask, keypoints);
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(*this)(image, mask, keypoints);
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else
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{
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// filter keypoints by mask
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KeyPointsFilter::runByPixelsMask( keypoints, mask );
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}
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VL::Sift vlsift((float*)fimg.data, fimg.cols, fimg.rows,
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sigman, sigma0, commParams.nOctaves, commParams.nOctaveLayers,
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