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Commit ec65e5b2 authored by Alexander Alekhin's avatar Alexander Alekhin
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xfeatures2d: apply CV_OVERRIDE/CV_FINAL

parent 874edea9
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Showing with 203 additions and 203 deletions
modules/xfeatures2d/include/opencv2/xfeatures2d.hpp
View file @ ec65e5b2
...@@ -210,11 +210,11 @@ public: ...@@ -210,11 +210,11 @@ public:
* @param keypoints of interest within image * @param keypoints of interest within image
* @param descriptors resulted descriptors array * @param descriptors resulted descriptors array
*/ */
virtual void compute( InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors ) = 0; virtual void compute( InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors ) CV_OVERRIDE = 0;
virtual void compute( InputArrayOfArrays images, virtual void compute( InputArrayOfArrays images,
std::vector<std::vector<KeyPoint> >& keypoints, std::vector<std::vector<KeyPoint> >& keypoints,
OutputArrayOfArrays descriptors ); OutputArrayOfArrays descriptors ) CV_OVERRIDE;
/** @overload /** @overload
* @param image image to extract descriptors * @param image image to extract descriptors
......
modules/xfeatures2d/src/affine_feature2d.cpp
View file @ ec65e5b2
...@@ -589,7 +589,7 @@ namespace cv ...@@ -589,7 +589,7 @@ namespace cv
{ {
namespace xfeatures2d namespace xfeatures2d
{ {
class AffineFeature2D_Impl : public AffineFeature2D class AffineFeature2D_Impl CV_FINAL : public AffineFeature2D
{ {
public: public:
AffineFeature2D_Impl( AffineFeature2D_Impl(
...@@ -599,12 +599,12 @@ public: ...@@ -599,12 +599,12 @@ public:
, m_descriptor_extractor(descriptor_extractor) {} , m_descriptor_extractor(descriptor_extractor) {}
protected: protected:
using Feature2D::detect; // overload, don't hide using Feature2D::detect; // overload, don't hide
void detect(InputArray image, std::vector<Elliptic_KeyPoint>& keypoints, InputArray mask); void detect(InputArray image, std::vector<Elliptic_KeyPoint>& keypoints, InputArray mask) CV_OVERRIDE;
void detectAndCompute(InputArray image, InputArray mask, std::vector<Elliptic_KeyPoint>& keypoints, OutputArray descriptors, bool useProvidedKeypoints); void detectAndCompute(InputArray image, InputArray mask, std::vector<Elliptic_KeyPoint>& keypoints, OutputArray descriptors, bool useProvidedKeypoints) CV_OVERRIDE;
void detectAndCompute(InputArray image, InputArray mask, std::vector<KeyPoint>& keypoints, OutputArray descriptors, bool useProvidedKeypoints); void detectAndCompute(InputArray image, InputArray mask, std::vector<KeyPoint>& keypoints, OutputArray descriptors, bool useProvidedKeypoints) CV_OVERRIDE;
int descriptorSize() const; int descriptorSize() const CV_OVERRIDE;
int descriptorType() const; int descriptorType() const CV_OVERRIDE;
int defaultNorm() const; int defaultNorm() const CV_OVERRIDE;
private: private:
Ptr<FeatureDetector> m_keypoint_detector; Ptr<FeatureDetector> m_keypoint_detector;
Ptr<DescriptorExtractor> m_descriptor_extractor; Ptr<DescriptorExtractor> m_descriptor_extractor;
......
modules/xfeatures2d/src/boostdesc.cpp
View file @ ec65e5b2
...@@ -68,7 +68,7 @@ namespace xfeatures2d ...@@ -68,7 +68,7 @@ namespace xfeatures2d
/* /*
!BoostDesc implementation !BoostDesc implementation
*/ */
class BoostDesc_Impl : public BoostDesc class BoostDesc_Impl CV_FINAL : public BoostDesc
{ {
public: public:
...@@ -79,26 +79,26 @@ public: ...@@ -79,26 +79,26 @@ public:
float scale_factor = 6.25f ); float scale_factor = 6.25f );
// destructor // destructor
virtual ~BoostDesc_Impl(); virtual ~BoostDesc_Impl() CV_OVERRIDE;
// returns the descriptor length in bytes // returns the descriptor length in bytes
virtual int descriptorSize() const { return m_descriptor_size; } virtual int descriptorSize() const CV_OVERRIDE { return m_descriptor_size; }
// returns the descriptor type // returns the descriptor type
virtual int descriptorType() const { return m_descriptor_type; } virtual int descriptorType() const CV_OVERRIDE { return m_descriptor_type; }
// returns the default norm type // returns the default norm type
virtual int defaultNorm() const { return m_descriptor_norm; } virtual int defaultNorm() const CV_OVERRIDE { return m_descriptor_norm; }
// compute descriptors given keypoints // compute descriptors given keypoints
virtual void compute( InputArray image, vector<KeyPoint>& keypoints, OutputArray descriptors ); virtual void compute( InputArray image, vector<KeyPoint>& keypoints, OutputArray descriptors ) CV_OVERRIDE;
// getter / setter // getter / setter
virtual void setUseScaleOrientation(const bool use_scale_orientation) { m_use_scale_orientation = use_scale_orientation; } virtual void setUseScaleOrientation(const bool use_scale_orientation) CV_OVERRIDE { m_use_scale_orientation = use_scale_orientation; }
virtual bool getUseScaleOrientation() const { return m_use_scale_orientation; } virtual bool getUseScaleOrientation() const CV_OVERRIDE { return m_use_scale_orientation; }
virtual void setScaleFactor(const float scale_factor) { m_scale_factor = scale_factor; } virtual void setScaleFactor(const float scale_factor) CV_OVERRIDE { m_scale_factor = scale_factor; }
virtual float getScaleFactor() const { return m_scale_factor; } virtual float getScaleFactor() const CV_OVERRIDE { return m_scale_factor; }
protected: protected:
...@@ -415,7 +415,7 @@ struct ComputeBoostDescInvoker : ParallelLoopBody ...@@ -415,7 +415,7 @@ struct ComputeBoostDescInvoker : ParallelLoopBody
use_scale_orientation = _use_scale_orientation; use_scale_orientation = _use_scale_orientation;
} }
void operator ()( const cv::Range& range ) const void operator ()( const cv::Range& range ) const CV_OVERRIDE
{ {
// maps // maps
vector<Mat> gradMap, integralMap; vector<Mat> gradMap, integralMap;
......
modules/xfeatures2d/src/brief.cpp
View file @ ec65e5b2
...@@ -63,14 +63,14 @@ public: ...@@ -63,14 +63,14 @@ public:
// bytes is a length of descriptor in bytes. It can be equal 16, 32 or 64 bytes. // bytes is a length of descriptor in bytes. It can be equal 16, 32 or 64 bytes.
BriefDescriptorExtractorImpl( int bytes = 32, bool use_orientation = false ); BriefDescriptorExtractorImpl( int bytes = 32, bool use_orientation = false );
virtual void read( const FileNode& ); virtual void read( const FileNode& ) CV_OVERRIDE;
virtual void write( FileStorage& ) const; virtual void write( FileStorage& ) const CV_OVERRIDE;
virtual int descriptorSize() const; virtual int descriptorSize() const CV_OVERRIDE;
virtual int descriptorType() const; virtual int descriptorType() const CV_OVERRIDE;
virtual int defaultNorm() const; virtual int defaultNorm() const CV_OVERRIDE;
virtual void compute(InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors); virtual void compute(InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors) CV_OVERRIDE;
protected: protected:
typedef void(*PixelTestFn)(InputArray, const std::vector<KeyPoint>&, OutputArray, bool use_orientation ); typedef void(*PixelTestFn)(InputArray, const std::vector<KeyPoint>&, OutputArray, bool use_orientation );
......
modules/xfeatures2d/src/daisy.cpp
View file @ ec65e5b2
...@@ -83,7 +83,7 @@ void DAISY::compute( InputArrayOfArrays images, ...@@ -83,7 +83,7 @@ void DAISY::compute( InputArrayOfArrays images,
/* /*
!DAISY implementation !DAISY implementation
*/ */
class DAISY_Impl : public DAISY class DAISY_Impl CV_FINAL : public DAISY
{ {
public: public:
...@@ -101,39 +101,39 @@ public: ...@@ -101,39 +101,39 @@ public:
int norm = DAISY::NRM_NONE, InputArray H = noArray(), int norm = DAISY::NRM_NONE, InputArray H = noArray(),
bool interpolation = true, bool use_orientation = false); bool interpolation = true, bool use_orientation = false);
virtual ~DAISY_Impl(); virtual ~DAISY_Impl() CV_OVERRIDE;
/** returns the descriptor length in bytes */ /** returns the descriptor length in bytes */
virtual int descriptorSize() const { virtual int descriptorSize() const CV_OVERRIDE {
// +1 is for center pixel // +1 is for center pixel
return ( (m_rad_q_no * m_th_q_no + 1) * m_hist_th_q_no ); return ( (m_rad_q_no * m_th_q_no + 1) * m_hist_th_q_no );
}; };
/** returns the descriptor type */ /** returns the descriptor type */
virtual int descriptorType() const { return CV_32F; } virtual int descriptorType() const CV_OVERRIDE { return CV_32F; }
/** returns the default norm type */ /** returns the default norm type */
virtual int defaultNorm() const { return NORM_L2; } virtual int defaultNorm() const CV_OVERRIDE { return NORM_L2; }
/** /**
* @param image image to extract descriptors * @param image image to extract descriptors
* @param keypoints of interest within image * @param keypoints of interest within image
* @param descriptors resulted descriptors array * @param descriptors resulted descriptors array
*/ */
virtual void compute( InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors ); virtual void compute( InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors ) CV_OVERRIDE;
/** @overload /** @overload
* @param image image to extract descriptors * @param image image to extract descriptors
* @param roi region of interest within image * @param roi region of interest within image
* @param descriptors resulted descriptors array * @param descriptors resulted descriptors array
*/ */
virtual void compute( InputArray image, Rect roi, OutputArray descriptors ); virtual void compute( InputArray image, Rect roi, OutputArray descriptors ) CV_OVERRIDE;
/** @overload /** @overload
* @param image image to extract descriptors * @param image image to extract descriptors
* @param descriptors resulted descriptors array * @param descriptors resulted descriptors array
*/ */
virtual void compute( InputArray image, OutputArray descriptors ); virtual void compute( InputArray image, OutputArray descriptors ) CV_OVERRIDE;
/** /**
* @param y position y on image * @param y position y on image
...@@ -141,7 +141,7 @@ public: ...@@ -141,7 +141,7 @@ public:
* @param orientation orientation on image (0->360) * @param orientation orientation on image (0->360)
* @param descriptor supplied array for descriptor storage * @param descriptor supplied array for descriptor storage
*/ */
virtual void GetDescriptor( double y, double x, int orientation, float* descriptor ) const; virtual void GetDescriptor( double y, double x, int orientation, float* descriptor ) const CV_OVERRIDE;
/** /**
* @param y position y on image * @param y position y on image
...@@ -150,7 +150,7 @@ public: ...@@ -150,7 +150,7 @@ public:
* @param descriptor supplied array for descriptor storage * @param descriptor supplied array for descriptor storage
* @param H homography matrix for warped grid * @param H homography matrix for warped grid
*/ */
virtual bool GetDescriptor( double y, double x, int orientation, float* descriptor, double* H ) const; virtual bool GetDescriptor( double y, double x, int orientation, float* descriptor, double* H ) const CV_OVERRIDE;
/** /**
* @param y position y on image * @param y position y on image
...@@ -158,7 +158,7 @@ public: ...@@ -158,7 +158,7 @@ public:
* @param orientation orientation on image (0->360) * @param orientation orientation on image (0->360)
* @param descriptor supplied array for descriptor storage * @param descriptor supplied array for descriptor storage
*/ */
virtual void GetUnnormalizedDescriptor( double y, double x, int orientation, float* descriptor ) const; virtual void GetUnnormalizedDescriptor( double y, double x, int orientation, float* descriptor ) const CV_OVERRIDE;
/** /**
* @param y position y on image * @param y position y on image
...@@ -167,7 +167,7 @@ public: ...@@ -167,7 +167,7 @@ public:
* @param descriptor supplied array for descriptor storage * @param descriptor supplied array for descriptor storage
* @param H homography matrix for warped grid * @param H homography matrix for warped grid
*/ */
virtual bool GetUnnormalizedDescriptor( double y, double x, int orientation, float* descriptor, double* H ) const; virtual bool GetUnnormalizedDescriptor( double y, double x, int orientation, float* descriptor, double* H ) const CV_OVERRIDE;
protected: protected:
...@@ -410,7 +410,7 @@ struct LayeredGradientInvoker : ParallelLoopBody ...@@ -410,7 +410,7 @@ struct LayeredGradientInvoker : ParallelLoopBody
layer_no = layers->size[0]; layer_no = layers->size[0];
} }
void operator ()(const cv::Range& range) const void operator ()(const cv::Range& range) const CV_OVERRIDE
{ {
for (int l = range.start; l < range.end; ++l) for (int l = range.start; l < range.end; ++l)
{ {
...@@ -450,7 +450,7 @@ struct SmoothLayersInvoker : ParallelLoopBody ...@@ -450,7 +450,7 @@ struct SmoothLayersInvoker : ParallelLoopBody
ks = filter_size( sigma, 5.0f ); ks = filter_size( sigma, 5.0f );
} }
void operator ()(const cv::Range& range) const void operator ()(const cv::Range& range) const CV_OVERRIDE
{ {
for (int l = range.start; l < range.end; ++l) for (int l = range.start; l < range.end; ++l)
{ {
...@@ -1003,7 +1003,7 @@ struct ComputeDescriptorsInvoker : ParallelLoopBody ...@@ -1003,7 +1003,7 @@ struct ComputeDescriptorsInvoker : ParallelLoopBody
orientation_shift_table = _orientation_shift_table; orientation_shift_table = _orientation_shift_table;
} }
void operator ()(const cv::Range& range) const void operator ()(const cv::Range& range) const CV_OVERRIDE
{ {
int index, orientation; int index, orientation;
for (int y = range.start; y < range.end; ++y) for (int y = range.start; y < range.end; ++y)
...@@ -1064,7 +1064,7 @@ struct NormalizeDescriptorsInvoker : ParallelLoopBody ...@@ -1064,7 +1064,7 @@ struct NormalizeDescriptorsInvoker : ParallelLoopBody
descriptor_size = _descriptor_size; descriptor_size = _descriptor_size;
} }
void operator ()(const cv::Range& range) const void operator ()(const cv::Range& range) const CV_OVERRIDE
{ {
for (int d = range.start; d < range.end; ++d) for (int d = range.start; d < range.end; ++d)
{ {
...@@ -1146,7 +1146,7 @@ struct ComputeHistogramsInvoker : ParallelLoopBody ...@@ -1146,7 +1146,7 @@ struct ComputeHistogramsInvoker : ParallelLoopBody
_hist_th_q_no = layers->at(r).size[2]; _hist_th_q_no = layers->at(r).size[2];
} }
void operator ()(const cv::Range& range) const void operator ()(const cv::Range& range) const CV_OVERRIDE
{ {
for (int y = range.start; y < range.end; ++y) for (int y = range.start; y < range.end; ++y)
{ {
...@@ -1251,7 +1251,7 @@ struct MaxDoGInvoker : ParallelLoopBody ...@@ -1251,7 +1251,7 @@ struct MaxDoGInvoker : ParallelLoopBody
scale_map = _scale_map; scale_map = _scale_map;
} }
void operator ()(const cv::Range& range) const void operator ()(const cv::Range& range) const CV_OVERRIDE
{ {
for (int c = range.start; c < range.end; ++c) for (int c = range.start; c < range.end; ++c)
{ {
...@@ -1277,7 +1277,7 @@ struct RoundingInvoker : ParallelLoopBody ...@@ -1277,7 +1277,7 @@ struct RoundingInvoker : ParallelLoopBody
scale_map = _scale_map; scale_map = _scale_map;
} }
void operator ()(const cv::Range& range) const void operator ()(const cv::Range& range) const CV_OVERRIDE
{ {
for (int c = range.start; c < range.end; ++c) for (int c = range.start; c < range.end; ++c)
{ {
......
modules/xfeatures2d/src/freak.cpp
View file @ ec65e5b2
...@@ -49,7 +49,7 @@ namespace xfeatures2d ...@@ -49,7 +49,7 @@ namespace xfeatures2d
/*! /*!
FREAK implementation FREAK implementation
*/ */
class FREAK_Impl : public FREAK class FREAK_Impl CV_FINAL : public FREAK
{ {
public: public:
/** Constructor /** Constructor
...@@ -68,13 +68,13 @@ public: ...@@ -68,13 +68,13 @@ public:
virtual ~FREAK_Impl(); virtual ~FREAK_Impl();
/** returns the descriptor length in bytes */ /** returns the descriptor length in bytes */
virtual int descriptorSize() const; virtual int descriptorSize() const CV_OVERRIDE;
/** returns the descriptor type */ /** returns the descriptor type */
virtual int descriptorType() const; virtual int descriptorType() const CV_OVERRIDE;
/** returns the default norm type */ /** returns the default norm type */
virtual int defaultNorm() const; virtual int defaultNorm() const CV_OVERRIDE;
/** select the 512 "best description pairs" /** select the 512 "best description pairs"
* @param images grayscale images set * @param images grayscale images set
...@@ -85,7 +85,7 @@ public: ...@@ -85,7 +85,7 @@ public:
*/ */
std::vector<int> selectPairs( const std::vector<Mat>& images, std::vector<std::vector<KeyPoint> >& keypoints, std::vector<int> selectPairs( const std::vector<Mat>& images, std::vector<std::vector<KeyPoint> >& keypoints,
const double corrThresh = 0.7, bool verbose = true ); const double corrThresh = 0.7, bool verbose = true );
virtual void compute( InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors ); virtual void compute( InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors ) CV_OVERRIDE;
protected: protected:
......
modules/xfeatures2d/src/harris_lapace_detector.cpp
View file @ ec65e5b2
...@@ -315,7 +315,7 @@ namespace xfeatures2d ...@@ -315,7 +315,7 @@ namespace xfeatures2d
/* /*
* HarrisLaplaceFeatureDetector_Impl * HarrisLaplaceFeatureDetector_Impl
*/ */
class HarrisLaplaceFeatureDetector_Impl : public HarrisLaplaceFeatureDetector class HarrisLaplaceFeatureDetector_Impl CV_FINAL : public HarrisLaplaceFeatureDetector
{ {
public: public:
HarrisLaplaceFeatureDetector_Impl( HarrisLaplaceFeatureDetector_Impl(
...@@ -325,11 +325,11 @@ public: ...@@ -325,11 +325,11 @@ public:
int maxCorners=5000, int maxCorners=5000,
int num_layers=4 int num_layers=4
); );
virtual void read( const FileNode& fn ); virtual void read( const FileNode& fn ) CV_OVERRIDE;
virtual void write( FileStorage& fs ) const; virtual void write( FileStorage& fs ) const CV_OVERRIDE;
protected: protected:
void detect( InputArray image, std::vector<KeyPoint>& keypoints, InputArray mask=noArray() ); void detect( InputArray image, std::vector<KeyPoint>& keypoints, InputArray mask=noArray() ) CV_OVERRIDE;
int numOctaves; int numOctaves;
float corn_thresh; float corn_thresh;
......
modules/xfeatures2d/src/latch.cpp
View file @ ec65e5b2
...@@ -58,21 +58,21 @@ namespace cv ...@@ -58,21 +58,21 @@ namespace cv
/* /*
* LATCH Descriptor * LATCH Descriptor
*/ */
class LATCHDescriptorExtractorImpl : public LATCH class LATCHDescriptorExtractorImpl CV_FINAL : public LATCH
{ {
public: public:
enum { PATCH_SIZE = 48 }; enum { PATCH_SIZE = 48 };
LATCHDescriptorExtractorImpl(int bytes = 32, bool rotationInvariance = true, int half_ssd_size = 3, double sigma = 2.0); LATCHDescriptorExtractorImpl(int bytes = 32, bool rotationInvariance = true, int half_ssd_size = 3, double sigma = 2.0);
virtual void read( const FileNode& ); virtual void read( const FileNode& ) CV_OVERRIDE;
virtual void write( FileStorage& ) const; virtual void write( FileStorage& ) const CV_OVERRIDE;
virtual int descriptorSize() const; virtual int descriptorSize() const CV_OVERRIDE;
virtual int descriptorType() const; virtual int descriptorType() const CV_OVERRIDE;
virtual int defaultNorm() const; virtual int defaultNorm() const CV_OVERRIDE;
virtual void compute(InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors); virtual void compute(InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors) CV_OVERRIDE;
protected: protected:
typedef void(*PixelTestFn)(const Mat& input_image, const std::vector<KeyPoint>& keypoints, OutputArray, const std::vector<int> &points, bool rotationInvariance, int half_ssd_size); typedef void(*PixelTestFn)(const Mat& input_image, const std::vector<KeyPoint>& keypoints, OutputArray, const std::vector<int> &points, bool rotationInvariance, int half_ssd_size);
......
modules/xfeatures2d/src/lucid.cpp
View file @ ec65e5b2
...@@ -62,15 +62,15 @@ namespace cv { ...@@ -62,15 +62,15 @@ namespace cv {
LUCIDImpl(const int lucid_kernel = 1, const int blur_kernel = 2); LUCIDImpl(const int lucid_kernel = 1, const int blur_kernel = 2);
/** returns the descriptor length */ /** returns the descriptor length */
virtual int descriptorSize() const; virtual int descriptorSize() const CV_OVERRIDE;
/** returns the descriptor type */ /** returns the descriptor type */
virtual int descriptorType() const; virtual int descriptorType() const CV_OVERRIDE;
/** returns the default norm type */ /** returns the default norm type */
virtual int defaultNorm() const; virtual int defaultNorm() const CV_OVERRIDE;
virtual void compute(InputArray _src, std::vector<KeyPoint> &keypoints, OutputArray _desc); virtual void compute(InputArray _src, std::vector<KeyPoint> &keypoints, OutputArray _desc) CV_OVERRIDE;
protected: protected:
int l_kernel, b_kernel; int l_kernel, b_kernel;
......
modules/xfeatures2d/src/msd.cpp
View file @ ec65e5b2
...@@ -78,7 +78,7 @@ namespace cv ...@@ -78,7 +78,7 @@ namespace cv
} }
void operator()(const Range& range) const void operator()(const Range& range) const CV_OVERRIDE
{ {
for (int lvl = range.start; lvl < range.end; lvl++) for (int lvl = range.start; lvl < range.end; lvl++)
{ {
...@@ -152,7 +152,7 @@ namespace cv ...@@ -152,7 +152,7 @@ namespace cv
remains = w - chunkSize*split; remains = w - chunkSize*split;
} }
void operator()(const Range& range) const void operator()(const Range& range) const CV_OVERRIDE
{ {
for (int i = range.start; i < range.end; i++) for (int i = range.start; i < range.end; i++)
{ {
...@@ -199,7 +199,7 @@ namespace cv ...@@ -199,7 +199,7 @@ namespace cv
{ {
} }
void detect(InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask) void detect(InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask) CV_OVERRIDE
{ {
m_mask = _mask.getMat(); m_mask = _mask.getMat();
......
modules/xfeatures2d/src/pct_signatures.cpp
View file @ ec65e5b2
...@@ -49,7 +49,7 @@ Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com> ...@@ -49,7 +49,7 @@ Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
References: References:
Martin Krulis, Jakub Lokoc, Tomas Skopal. Martin Krulis, Jakub Lokoc, Tomas Skopal.
Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures. Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
Multimedia tools and applications, 75(13), pp.: 80718103, Springer, ISSN: 1380-7501, 2016 Multimedia tools and applications, 75(13), pp.: 8071�8103, Springer, ISSN: 1380-7501, 2016
Christian Beecks, Merih Seran Uysal, Thomas Seidl. Christian Beecks, Merih Seran Uysal, Thomas Seidl.
Signature quadratic form distance. Signature quadratic form distance.
...@@ -121,66 +121,66 @@ namespace cv ...@@ -121,66 +121,66 @@ namespace cv
mClusterizer = PCTClusterizer::create(initClusterSeedIndexes); mClusterizer = PCTClusterizer::create(initClusterSeedIndexes);
} }
void computeSignature(InputArray image, OutputArray signature) const; void computeSignature(InputArray image, OutputArray signature) const CV_OVERRIDE;
void computeSignatures(const std::vector<Mat>& images, std::vector<Mat>& signatures) const; void computeSignatures(const std::vector<Mat>& images, std::vector<Mat>& signatures) const CV_OVERRIDE;
void getGrayscaleBitmap(OutputArray _grayscaleBitmap, bool normalize) const; void getGrayscaleBitmap(OutputArray _grayscaleBitmap, bool normalize) const;
/**** sampler ****/ /**** sampler ****/
int getSampleCount() const { return mSampler->getGrayscaleBits(); } int getSampleCount() const CV_OVERRIDE { return mSampler->getGrayscaleBits(); }
int getGrayscaleBits() const { return mSampler->getGrayscaleBits(); } int getGrayscaleBits() const CV_OVERRIDE { return mSampler->getGrayscaleBits(); }
int getWindowRadius() const { return mSampler->getWindowRadius(); } int getWindowRadius() const CV_OVERRIDE { return mSampler->getWindowRadius(); }
float getWeightX() const { return mSampler->getWeightX(); } float getWeightX() const CV_OVERRIDE { return mSampler->getWeightX(); }
float getWeightY() const { return mSampler->getWeightY(); } float getWeightY() const CV_OVERRIDE { return mSampler->getWeightY(); }
float getWeightL() const { return mSampler->getWeightL(); } float getWeightL() const CV_OVERRIDE { return mSampler->getWeightL(); }
float getWeightA() const { return mSampler->getWeightA(); } float getWeightA() const CV_OVERRIDE { return mSampler->getWeightA(); }
float getWeightB() const { return mSampler->getWeightB(); } float getWeightB() const CV_OVERRIDE { return mSampler->getWeightB(); }
float getWeightContrast() const { return mSampler->getWeightContrast(); } float getWeightContrast() const CV_OVERRIDE { return mSampler->getWeightContrast(); }
float getWeightEntropy() const { return mSampler->getWeightEntropy(); } float getWeightEntropy() const CV_OVERRIDE { return mSampler->getWeightEntropy(); }
std::vector<Point2f> getSamplingPoints() const { return mSampler->getSamplingPoints(); } std::vector<Point2f> getSamplingPoints() const CV_OVERRIDE { return mSampler->getSamplingPoints(); }
void setGrayscaleBits(int grayscaleBits) { mSampler->setGrayscaleBits(grayscaleBits); } void setGrayscaleBits(int grayscaleBits) CV_OVERRIDE { mSampler->setGrayscaleBits(grayscaleBits); }
void setWindowRadius(int windowRadius) { mSampler->setWindowRadius(windowRadius); } void setWindowRadius(int windowRadius) CV_OVERRIDE { mSampler->setWindowRadius(windowRadius); }
void setWeightX(float weight) { mSampler->setWeightX(weight); } void setWeightX(float weight) CV_OVERRIDE { mSampler->setWeightX(weight); }
void setWeightY(float weight) { mSampler->setWeightY(weight); } void setWeightY(float weight) CV_OVERRIDE { mSampler->setWeightY(weight); }
void setWeightL(float weight) { mSampler->setWeightL(weight); } void setWeightL(float weight) CV_OVERRIDE { mSampler->setWeightL(weight); }
void setWeightA(float weight) { mSampler->setWeightA(weight); } void setWeightA(float weight) CV_OVERRIDE { mSampler->setWeightA(weight); }
void setWeightB(float weight) { mSampler->setWeightB(weight); } void setWeightB(float weight) CV_OVERRIDE { mSampler->setWeightB(weight); }
void setWeightContrast(float weight) { mSampler->setWeightContrast(weight); } void setWeightContrast(float weight) CV_OVERRIDE { mSampler->setWeightContrast(weight); }
void setWeightEntropy(float weight) { mSampler->setWeightEntropy(weight); } void setWeightEntropy(float weight) CV_OVERRIDE { mSampler->setWeightEntropy(weight); }
void setWeight(int idx, float value) { mSampler->setWeight(idx, value); } void setWeight(int idx, float value) CV_OVERRIDE { mSampler->setWeight(idx, value); }
void setWeights(const std::vector<float>& weights) { mSampler->setWeights(weights); } void setWeights(const std::vector<float>& weights) CV_OVERRIDE { mSampler->setWeights(weights); }
void setTranslation(int idx, float value) { mSampler->setTranslation(idx, value); } void setTranslation(int idx, float value) CV_OVERRIDE { mSampler->setTranslation(idx, value); }
void setTranslations(const std::vector<float>& translations) { mSampler->setTranslations(translations); } void setTranslations(const std::vector<float>& translations) CV_OVERRIDE { mSampler->setTranslations(translations); }
void setSamplingPoints(std::vector<Point2f> samplingPoints) { mSampler->setSamplingPoints(samplingPoints); } void setSamplingPoints(std::vector<Point2f> samplingPoints) CV_OVERRIDE { mSampler->setSamplingPoints(samplingPoints); }
/**** clusterizer ****/ /**** clusterizer ****/
int getIterationCount() const { return mClusterizer->getIterationCount(); } int getIterationCount() const CV_OVERRIDE { return mClusterizer->getIterationCount(); }
std::vector<int> getInitSeedIndexes() const { return mClusterizer->getInitSeedIndexes(); } std::vector<int> getInitSeedIndexes() const CV_OVERRIDE { return mClusterizer->getInitSeedIndexes(); }
int getInitSeedCount() const { return (int)mClusterizer->getInitSeedIndexes().size(); } int getInitSeedCount() const CV_OVERRIDE { return (int)mClusterizer->getInitSeedIndexes().size(); }
int getMaxClustersCount() const { return mClusterizer->getMaxClustersCount(); } int getMaxClustersCount() const CV_OVERRIDE { return mClusterizer->getMaxClustersCount(); }
int getClusterMinSize() const { return mClusterizer->getClusterMinSize(); } int getClusterMinSize() const CV_OVERRIDE { return mClusterizer->getClusterMinSize(); }
float getJoiningDistance() const { return mClusterizer->getJoiningDistance(); } float getJoiningDistance() const CV_OVERRIDE { return mClusterizer->getJoiningDistance(); }
float getDropThreshold() const { return mClusterizer->getDropThreshold(); } float getDropThreshold() const CV_OVERRIDE { return mClusterizer->getDropThreshold(); }
int getDistanceFunction() const int getDistanceFunction() const CV_OVERRIDE
{ return mClusterizer->getDistanceFunction(); } { return mClusterizer->getDistanceFunction(); }
void setIterationCount(int iterations) { mClusterizer->setIterationCount(iterations); } void setIterationCount(int iterations) CV_OVERRIDE { mClusterizer->setIterationCount(iterations); }
void setInitSeedIndexes(std::vector<int> initSeedIndexes) void setInitSeedIndexes(std::vector<int> initSeedIndexes) CV_OVERRIDE
{ mClusterizer->setInitSeedIndexes(initSeedIndexes); } { mClusterizer->setInitSeedIndexes(initSeedIndexes); }
void setMaxClustersCount(int maxClusters) { mClusterizer->setMaxClustersCount(maxClusters); } void setMaxClustersCount(int maxClusters) CV_OVERRIDE { mClusterizer->setMaxClustersCount(maxClusters); }
void setClusterMinSize(int clusterMinSize) { mClusterizer->setClusterMinSize(clusterMinSize); } void setClusterMinSize(int clusterMinSize) CV_OVERRIDE { mClusterizer->setClusterMinSize(clusterMinSize); }
void setJoiningDistance(float joiningDistance) { mClusterizer->setJoiningDistance(joiningDistance); } void setJoiningDistance(float joiningDistance) CV_OVERRIDE { mClusterizer->setJoiningDistance(joiningDistance); }
void setDropThreshold(float dropThreshold) { mClusterizer->setDropThreshold(dropThreshold); } void setDropThreshold(float dropThreshold) CV_OVERRIDE { mClusterizer->setDropThreshold(dropThreshold); }
void setDistanceFunction(int distanceFunction) void setDistanceFunction(int distanceFunction) CV_OVERRIDE
{ mClusterizer->setDistanceFunction(distanceFunction); } { mClusterizer->setDistanceFunction(distanceFunction); }
private: private:
...@@ -236,7 +236,7 @@ namespace cv ...@@ -236,7 +236,7 @@ namespace cv
mSignatures->resize(images->size()); mSignatures->resize(images->size());
} }
void operator()(const Range& range) const void operator()(const Range& range) const CV_OVERRIDE
{ {
for (int i = range.start; i < range.end; i++) for (int i = range.start; i < range.end; i++)
{ {
......
modules/xfeatures2d/src/pct_signatures/pct_clusterizer.cpp
View file @ ec65e5b2
...@@ -49,7 +49,7 @@ Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com> ...@@ -49,7 +49,7 @@ Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
References: References:
Martin Krulis, Jakub Lokoc, Tomas Skopal. Martin Krulis, Jakub Lokoc, Tomas Skopal.
Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures. Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
Multimedia tools and applications, 75(13), pp.: 8071–8103, Springer, ISSN: 1380-7501, 2016 Multimedia tools and applications, 75(13), pp.: 8071�8103, Springer, ISSN: 1380-7501, 2016
Christian Beecks, Merih Seran Uysal, Thomas Seidl. Christian Beecks, Merih Seran Uysal, Thomas Seidl.
Signature quadratic form distance. Signature quadratic form distance.
...@@ -68,7 +68,7 @@ namespace cv ...@@ -68,7 +68,7 @@ namespace cv
{ {
namespace pct_signatures namespace pct_signatures
{ {
class PCTClusterizer_Impl : public PCTClusterizer class PCTClusterizer_Impl CV_FINAL : public PCTClusterizer
{ {
public: public:
...@@ -95,21 +95,21 @@ namespace cv ...@@ -95,21 +95,21 @@ namespace cv
} }
int getIterationCount() const { return mIterationCount; } int getIterationCount() const CV_OVERRIDE { return mIterationCount; }
std::vector<int> getInitSeedIndexes() const { return mInitSeedIndexes; } std::vector<int> getInitSeedIndexes() const CV_OVERRIDE { return mInitSeedIndexes; }
int getMaxClustersCount() const { return mMaxClustersCount; } int getMaxClustersCount() const CV_OVERRIDE { return mMaxClustersCount; }
int getClusterMinSize() const { return mClusterMinSize; } int getClusterMinSize() const CV_OVERRIDE { return mClusterMinSize; }
float getJoiningDistance() const { return mJoiningDistance; } float getJoiningDistance() const CV_OVERRIDE { return mJoiningDistance; }
float getDropThreshold() const { return mDropThreshold; } float getDropThreshold() const CV_OVERRIDE { return mDropThreshold; }
int getDistanceFunction() const { return mDistanceFunction; } int getDistanceFunction() const CV_OVERRIDE { return mDistanceFunction; }
void setIterationCount(int iterationCount) { mIterationCount = iterationCount; } void setIterationCount(int iterationCount) CV_OVERRIDE { mIterationCount = iterationCount; }
void setInitSeedIndexes(std::vector<int> initSeedIndexes) { mInitSeedIndexes = initSeedIndexes; } void setInitSeedIndexes(std::vector<int> initSeedIndexes) CV_OVERRIDE { mInitSeedIndexes = initSeedIndexes; }
void setMaxClustersCount(int maxClustersCount) { mMaxClustersCount = maxClustersCount; } void setMaxClustersCount(int maxClustersCount) CV_OVERRIDE { mMaxClustersCount = maxClustersCount; }
void setClusterMinSize(int clusterMinSize) { mClusterMinSize = clusterMinSize; } void setClusterMinSize(int clusterMinSize) CV_OVERRIDE { mClusterMinSize = clusterMinSize; }
void setJoiningDistance(float joiningDistance) { mJoiningDistance = joiningDistance; } void setJoiningDistance(float joiningDistance) CV_OVERRIDE { mJoiningDistance = joiningDistance; }
void setDropThreshold(float dropThreshold) { mDropThreshold = dropThreshold; } void setDropThreshold(float dropThreshold) CV_OVERRIDE { mDropThreshold = dropThreshold; }
void setDistanceFunction(int distanceFunction) { mDistanceFunction = distanceFunction; } void setDistanceFunction(int distanceFunction) CV_OVERRIDE { mDistanceFunction = distanceFunction; }
/** /**
...@@ -117,7 +117,7 @@ namespace cv ...@@ -117,7 +117,7 @@ namespace cv
* @param samples List of sampled points. * @param samples List of sampled points.
* @param signature Output list of computed centroids - the signature of the image. * @param signature Output list of computed centroids - the signature of the image.
*/ */
void clusterize(InputArray _samples, OutputArray _signature) void clusterize(InputArray _samples, OutputArray _signature) CV_OVERRIDE
{ {
CV_Assert(!_samples.empty()); CV_Assert(!_samples.empty());
......
modules/xfeatures2d/src/pct_signatures/pct_sampler.cpp
View file @ ec65e5b2
...@@ -49,7 +49,7 @@ Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com> ...@@ -49,7 +49,7 @@ Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
References: References:
Martin Krulis, Jakub Lokoc, Tomas Skopal. Martin Krulis, Jakub Lokoc, Tomas Skopal.
Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures. Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
Multimedia tools and applications, 75(13), pp.: 8071–8103, Springer, ISSN: 1380-7501, 2016 Multimedia tools and applications, 75(13), pp.: 8071�8103, Springer, ISSN: 1380-7501, 2016
Christian Beecks, Merih Seran Uysal, Thomas Seidl. Christian Beecks, Merih Seran Uysal, Thomas Seidl.
Signature quadratic form distance. Signature quadratic form distance.
...@@ -67,7 +67,7 @@ namespace cv ...@@ -67,7 +67,7 @@ namespace cv
{ {
namespace pct_signatures namespace pct_signatures
{ {
class PCTSampler_Impl : public PCTSampler class PCTSampler_Impl CV_FINAL : public PCTSampler
{ {
private: private:
/** /**
...@@ -119,40 +119,40 @@ namespace cv ...@@ -119,40 +119,40 @@ namespace cv
/**** Acessors ****/ /**** Acessors ****/
int getSampleCount() const { return (int)mInitSamplingPoints.size(); } int getSampleCount() const CV_OVERRIDE { return (int)mInitSamplingPoints.size(); }
int getGrayscaleBits() const { return mGrayscaleBits; } int getGrayscaleBits() const CV_OVERRIDE { return mGrayscaleBits; }
int getWindowRadius() const { return mWindowRadius; } int getWindowRadius() const CV_OVERRIDE { return mWindowRadius; }
float getWeightX() const { return mWeights[X_IDX]; } float getWeightX() const CV_OVERRIDE { return mWeights[X_IDX]; }
float getWeightY() const { return mWeights[Y_IDX]; } float getWeightY() const CV_OVERRIDE { return mWeights[Y_IDX]; }
float getWeightL() const { return mWeights[L_IDX]; } float getWeightL() const CV_OVERRIDE { return mWeights[L_IDX]; }
float getWeightA() const { return mWeights[A_IDX]; } float getWeightA() const CV_OVERRIDE { return mWeights[A_IDX]; }
float getWeightB() const { return mWeights[B_IDX]; } float getWeightB() const CV_OVERRIDE { return mWeights[B_IDX]; }
float getWeightContrast() const { return mWeights[CONTRAST_IDX]; } float getWeightContrast() const CV_OVERRIDE { return mWeights[CONTRAST_IDX]; }
float getWeightEntropy() const { return mWeights[ENTROPY_IDX]; } float getWeightEntropy() const CV_OVERRIDE { return mWeights[ENTROPY_IDX]; }
std::vector<Point2f> getSamplingPoints() const std::vector<Point2f> getSamplingPoints() const CV_OVERRIDE
{ return mInitSamplingPoints; } { return mInitSamplingPoints; }
void setGrayscaleBits(int grayscaleBits) { mGrayscaleBits = grayscaleBits; } void setGrayscaleBits(int grayscaleBits) CV_OVERRIDE { mGrayscaleBits = grayscaleBits; }
void setWindowRadius(int windowRadius) { mWindowRadius = windowRadius; } void setWindowRadius(int windowRadius) CV_OVERRIDE { mWindowRadius = windowRadius; }
void setWeightX(float weight) { mWeights[X_IDX] = weight; } void setWeightX(float weight) CV_OVERRIDE { mWeights[X_IDX] = weight; }
void setWeightY(float weight) { mWeights[Y_IDX] = weight; } void setWeightY(float weight) CV_OVERRIDE { mWeights[Y_IDX] = weight; }
void setWeightL(float weight) { mWeights[L_IDX] = weight; } void setWeightL(float weight) CV_OVERRIDE { mWeights[L_IDX] = weight; }
void setWeightA(float weight) { mWeights[A_IDX] = weight; } void setWeightA(float weight) CV_OVERRIDE { mWeights[A_IDX] = weight; }
void setWeightB(float weight) { mWeights[B_IDX] = weight; } void setWeightB(float weight) CV_OVERRIDE { mWeights[B_IDX] = weight; }
void setWeightContrast(float weight) { mWeights[CONTRAST_IDX] = weight; } void setWeightContrast(float weight) CV_OVERRIDE { mWeights[CONTRAST_IDX] = weight; }
void setWeightEntropy(float weight) { mWeights[ENTROPY_IDX] = weight; } void setWeightEntropy(float weight) CV_OVERRIDE { mWeights[ENTROPY_IDX] = weight; }
void setWeight(int idx, float value) void setWeight(int idx, float value) CV_OVERRIDE
{ {
mWeights[idx] = value; mWeights[idx] = value;
} }
void setWeights(const std::vector<float>& weights) void setWeights(const std::vector<float>& weights) CV_OVERRIDE
{ {
if (weights.size() != mWeights.size()) if (weights.size() != mWeights.size())
{ {
...@@ -168,12 +168,12 @@ namespace cv ...@@ -168,12 +168,12 @@ namespace cv
} }
} }
void setTranslation(int idx, float value) void setTranslation(int idx, float value) CV_OVERRIDE
{ {
mTranslations[idx] = value; mTranslations[idx] = value;
} }
void setTranslations(const std::vector<float>& translations) void setTranslations(const std::vector<float>& translations) CV_OVERRIDE
{ {
if (translations.size() != mTranslations.size()) if (translations.size() != mTranslations.size())
{ {
...@@ -189,10 +189,10 @@ namespace cv ...@@ -189,10 +189,10 @@ namespace cv
} }
} }
void setSamplingPoints(std::vector<Point2f> samplingPoints) { mInitSamplingPoints = samplingPoints; } void setSamplingPoints(std::vector<Point2f> samplingPoints) CV_OVERRIDE { mInitSamplingPoints = samplingPoints; }
void sample(InputArray _image, OutputArray _samples) const void sample(InputArray _image, OutputArray _samples) const CV_OVERRIDE
{ {
// prepare matrices // prepare matrices
Mat image = _image.getMat(); Mat image = _image.getMat();
......
modules/xfeatures2d/src/pct_signatures_sqfd.cpp
View file @ ec65e5b2
...@@ -49,7 +49,7 @@ Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com> ...@@ -49,7 +49,7 @@ Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
References: References:
Martin Krulis, Jakub Lokoc, Tomas Skopal. Martin Krulis, Jakub Lokoc, Tomas Skopal.
Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures. Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
Multimedia tools and applications, 75(13), pp.: 80718103, Springer, ISSN: 1380-7501, 2016 Multimedia tools and applications, 75(13), pp.: 8071�8103, Springer, ISSN: 1380-7501, 2016
Christian Beecks, Merih Seran Uysal, Thomas Seidl. Christian Beecks, Merih Seran Uysal, Thomas Seidl.
Signature quadratic form distance. Signature quadratic form distance.
...@@ -84,12 +84,12 @@ namespace cv ...@@ -84,12 +84,12 @@ namespace cv
float computeQuadraticFormDistance( float computeQuadraticFormDistance(
InputArray _signature0, InputArray _signature0,
InputArray _signature1) const; InputArray _signature1) const CV_OVERRIDE;
void computeQuadraticFormDistances( void computeQuadraticFormDistances(
const Mat& sourceSignature, const Mat& sourceSignature,
const std::vector<Mat>& imageSignatures, const std::vector<Mat>& imageSignatures,
std::vector<float>& distances) const; std::vector<float>& distances) const CV_OVERRIDE;
private: private:
...@@ -129,7 +129,7 @@ namespace cv ...@@ -129,7 +129,7 @@ namespace cv
mDistances->resize(imageSignatures->size()); mDistances->resize(imageSignatures->size());
} }
void operator()(const Range& range) const void operator()(const Range& range) const CV_OVERRIDE
{ {
if (mSourceSignature->empty()) if (mSourceSignature->empty())
{ {
......
modules/xfeatures2d/src/sift.cpp
View file @ ec65e5b2
...@@ -125,20 +125,20 @@ public: ...@@ -125,20 +125,20 @@ public:
double sigma = 1.6); double sigma = 1.6);
//! returns the descriptor size in floats (128) //! returns the descriptor size in floats (128)
int descriptorSize() const; int descriptorSize() const CV_OVERRIDE;
//! returns the descriptor type //! returns the descriptor type
int descriptorType() const; int descriptorType() const CV_OVERRIDE;
//! returns the default norm type //! returns the default norm type
int defaultNorm() const; int defaultNorm() const CV_OVERRIDE;
//! finds the keypoints and computes descriptors for them using SIFT algorithm. //! finds the keypoints and computes descriptors for them using SIFT algorithm.
//! Optionally it can compute descriptors for the user-provided keypoints //! Optionally it can compute descriptors for the user-provided keypoints
void detectAndCompute(InputArray img, InputArray mask, void detectAndCompute(InputArray img, InputArray mask,
std::vector<KeyPoint>& keypoints, std::vector<KeyPoint>& keypoints,
OutputArray descriptors, OutputArray descriptors,
bool useProvidedKeypoints = false); bool useProvidedKeypoints = false) CV_OVERRIDE;
void buildGaussianPyramid( const Mat& base, std::vector<Mat>& pyr, int nOctaves ) const; void buildGaussianPyramid( const Mat& base, std::vector<Mat>& pyr, int nOctaves ) const;
void buildDoGPyramid( const std::vector<Mat>& pyr, std::vector<Mat>& dogpyr ) const; void buildDoGPyramid( const std::vector<Mat>& pyr, std::vector<Mat>& dogpyr ) const;
...@@ -302,7 +302,7 @@ public: ...@@ -302,7 +302,7 @@ public:
gpyr(_gpyr), gpyr(_gpyr),
dogpyr(_dogpyr) { } dogpyr(_dogpyr) { }
void operator()( const cv::Range& range ) const void operator()( const cv::Range& range ) const CV_OVERRIDE
{ {
const int begin = range.start; const int begin = range.start;
const int end = range.end; const int end = range.end;
...@@ -605,7 +605,7 @@ public: ...@@ -605,7 +605,7 @@ public:
gauss_pyr(_gauss_pyr), gauss_pyr(_gauss_pyr),
dog_pyr(_dog_pyr), dog_pyr(_dog_pyr),
tls_kpts_struct(_tls_kpts_struct) { } tls_kpts_struct(_tls_kpts_struct) { }
void operator()( const cv::Range& range ) const void operator()( const cv::Range& range ) const CV_OVERRIDE
{ {
const int begin = range.start; const int begin = range.start;
const int end = range.end; const int end = range.end;
...@@ -1046,7 +1046,7 @@ public: ...@@ -1046,7 +1046,7 @@ public:
nOctaveLayers(_nOctaveLayers), nOctaveLayers(_nOctaveLayers),
firstOctave(_firstOctave) { } firstOctave(_firstOctave) { }
void operator()( const cv::Range& range ) const void operator()( const cv::Range& range ) const CV_OVERRIDE
{ {
const int begin = range.start; const int begin = range.start;
const int end = range.end; const int end = range.end;
......
modules/xfeatures2d/src/stardetector.cpp
View file @ ec65e5b2
...@@ -60,7 +60,7 @@ public: ...@@ -60,7 +60,7 @@ public:
int _lineThresholdBinarized=8, int _lineThresholdBinarized=8,
int _suppressNonmaxSize=5); int _suppressNonmaxSize=5);
void detect( InputArray image, std::vector<KeyPoint>& keypoints, InputArray mask=noArray() ); void detect( InputArray image, std::vector<KeyPoint>& keypoints, InputArray mask=noArray() ) CV_OVERRIDE;
protected: protected:
int maxSize; int maxSize;
......
modules/xfeatures2d/src/surf.cpp
View file @ ec65e5b2
...@@ -274,7 +274,7 @@ struct SURFBuildInvoker : ParallelLoopBody ...@@ -274,7 +274,7 @@ struct SURFBuildInvoker : ParallelLoopBody
traces = &_traces; traces = &_traces;
} }
void operator()(const Range& range) const void operator()(const Range& range) const CV_OVERRIDE
{ {
for( int i=range.start; i<range.end; i++ ) for( int i=range.start; i<range.end; i++ )
calcLayerDetAndTrace( *sum, (*sizes)[i], (*sampleSteps)[i], (*dets)[i], (*traces)[i] ); calcLayerDetAndTrace( *sum, (*sizes)[i], (*sampleSteps)[i], (*dets)[i], (*traces)[i] );
...@@ -313,7 +313,7 @@ struct SURFFindInvoker : ParallelLoopBody ...@@ -313,7 +313,7 @@ struct SURFFindInvoker : ParallelLoopBody
const std::vector<int>& sizes, std::vector<KeyPoint>& keypoints, const std::vector<int>& sizes, std::vector<KeyPoint>& keypoints,
int octave, int layer, float hessianThreshold, int sampleStep ); int octave, int layer, float hessianThreshold, int sampleStep );
void operator()(const Range& range) const void operator()(const Range& range) const CV_OVERRIDE
{ {
for( int i=range.start; i<range.end; i++ ) for( int i=range.start; i<range.end; i++ )
{ {
...@@ -563,7 +563,7 @@ struct SURFInvoker : ParallelLoopBody ...@@ -563,7 +563,7 @@ struct SURFInvoker : ParallelLoopBody
} }
} }
void operator()(const Range& range) const void operator()(const Range& range) const CV_OVERRIDE
{ {
/* X and Y gradient wavelet data */ /* X and Y gradient wavelet data */
const int NX=2, NY=2; const int NX=2, NY=2;
......
modules/xfeatures2d/src/surf.hpp
View file @ ec65e5b2
...@@ -24,13 +24,13 @@ public: ...@@ -24,13 +24,13 @@ public:
bool extended = true, bool upright = false); bool extended = true, bool upright = false);
//! returns the descriptor size in float's (64 or 128) //! returns the descriptor size in float's (64 or 128)
CV_WRAP int descriptorSize() const; CV_WRAP int descriptorSize() const CV_OVERRIDE;
//! returns the descriptor type //! returns the descriptor type
CV_WRAP int descriptorType() const; CV_WRAP int descriptorType() const CV_OVERRIDE;
//! returns the descriptor type //! returns the descriptor type
CV_WRAP int defaultNorm() const; CV_WRAP int defaultNorm() const CV_OVERRIDE;
void set(int, double); void set(int, double);
double get(int) const; double get(int) const;
...@@ -40,22 +40,22 @@ public: ...@@ -40,22 +40,22 @@ public:
void detectAndCompute(InputArray img, InputArray mask, void detectAndCompute(InputArray img, InputArray mask,
CV_OUT std::vector<KeyPoint>& keypoints, CV_OUT std::vector<KeyPoint>& keypoints,
OutputArray descriptors, OutputArray descriptors,
bool useProvidedKeypoints = false); bool useProvidedKeypoints = false) CV_OVERRIDE;
void setHessianThreshold(double hessianThreshold_) { hessianThreshold = hessianThreshold_; } void setHessianThreshold(double hessianThreshold_) CV_OVERRIDE { hessianThreshold = hessianThreshold_; }
double getHessianThreshold() const { return hessianThreshold; } double getHessianThreshold() const CV_OVERRIDE { return hessianThreshold; }
void setNOctaves(int nOctaves_) { nOctaves = nOctaves_; } void setNOctaves(int nOctaves_) CV_OVERRIDE { nOctaves = nOctaves_; }
int getNOctaves() const { return nOctaves; } int getNOctaves() const CV_OVERRIDE { return nOctaves; }
void setNOctaveLayers(int nOctaveLayers_) { nOctaveLayers = nOctaveLayers_; } void setNOctaveLayers(int nOctaveLayers_) CV_OVERRIDE { nOctaveLayers = nOctaveLayers_; }
int getNOctaveLayers() const { return nOctaveLayers; } int getNOctaveLayers() const CV_OVERRIDE { return nOctaveLayers; }
void setExtended(bool extended_) { extended = extended_; } void setExtended(bool extended_) CV_OVERRIDE { extended = extended_; }
bool getExtended() const { return extended; } bool getExtended() const CV_OVERRIDE { return extended; }
void setUpright(bool upright_) { upright = upright_; } void setUpright(bool upright_) CV_OVERRIDE { upright = upright_; }
bool getUpright() const { return upright; } bool getUpright() const CV_OVERRIDE { return upright; }
double hessianThreshold; double hessianThreshold;
int nOctaves; int nOctaves;
......
modules/xfeatures2d/src/vgg.cpp
View file @ ec65e5b2
...@@ -69,7 +69,7 @@ namespace xfeatures2d ...@@ -69,7 +69,7 @@ namespace xfeatures2d
/* /*
!VGG implementation !VGG implementation
*/ */
class VGG_Impl : public VGG class VGG_Impl CV_FINAL : public VGG
{ {
public: public:
...@@ -80,35 +80,35 @@ public: ...@@ -80,35 +80,35 @@ public:
float scale_factor = 6.25f, bool dsc_normalize = false ); float scale_factor = 6.25f, bool dsc_normalize = false );
// destructor // destructor
virtual ~VGG_Impl(); virtual ~VGG_Impl() CV_OVERRIDE;
// returns the descriptor length in bytes // returns the descriptor length in bytes
virtual int descriptorSize() const { return m_descriptor_size; } virtual int descriptorSize() const CV_OVERRIDE { return m_descriptor_size; }
// returns the descriptor type // returns the descriptor type
virtual int descriptorType() const { return CV_32F; } virtual int descriptorType() const CV_OVERRIDE { return CV_32F; }
// returns the default norm type // returns the default norm type
virtual int defaultNorm() const { return NORM_L2; } virtual int defaultNorm() const CV_OVERRIDE { return NORM_L2; }
// compute descriptors given keypoints // compute descriptors given keypoints
virtual void compute( InputArray image, vector<KeyPoint>& keypoints, OutputArray descriptors ); virtual void compute( InputArray image, vector<KeyPoint>& keypoints, OutputArray descriptors ) CV_OVERRIDE;
// getter / setter // getter / setter
virtual void setSigma(const float isigma) { m_isigma = isigma; } virtual void setSigma(const float isigma) CV_OVERRIDE { m_isigma = isigma; }
virtual float getSigma() const { return m_isigma; } virtual float getSigma() const CV_OVERRIDE { return m_isigma; }
virtual void setUseNormalizeImage(const bool img_normalize) { m_img_normalize = img_normalize; } virtual void setUseNormalizeImage(const bool img_normalize) CV_OVERRIDE { m_img_normalize = img_normalize; }
virtual bool getUseNormalizeImage() const { return m_img_normalize; } virtual bool getUseNormalizeImage() const CV_OVERRIDE { return m_img_normalize; }
virtual void setUseScaleOrientation(const bool use_scale_orientation) { m_use_scale_orientation = use_scale_orientation; } virtual void setUseScaleOrientation(const bool use_scale_orientation) CV_OVERRIDE { m_use_scale_orientation = use_scale_orientation; }
virtual bool getUseScaleOrientation() const { return m_use_scale_orientation; } virtual bool getUseScaleOrientation() const CV_OVERRIDE { return m_use_scale_orientation; }
virtual void setScaleFactor(const float scale_factor) { m_scale_factor = scale_factor; } virtual void setScaleFactor(const float scale_factor) CV_OVERRIDE { m_scale_factor = scale_factor; }
virtual float getScaleFactor() const { return m_scale_factor; } virtual float getScaleFactor() const CV_OVERRIDE { return m_scale_factor; }
virtual void setUseNormalizeDescriptor(const bool dsc_normalize) { m_dsc_normalize = dsc_normalize; } virtual void setUseNormalizeDescriptor(const bool dsc_normalize) CV_OVERRIDE { m_dsc_normalize = dsc_normalize; }
virtual bool getUseNormalizeDescriptor() const { return m_dsc_normalize; } virtual bool getUseNormalizeDescriptor() const CV_OVERRIDE { return m_dsc_normalize; }
protected: protected:
...@@ -352,7 +352,7 @@ struct ComputeVGGInvoker : ParallelLoopBody ...@@ -352,7 +352,7 @@ struct ComputeVGGInvoker : ParallelLoopBody
use_scale_orientation = _use_scale_orientation; use_scale_orientation = _use_scale_orientation;
} }
void operator ()(const cv::Range& range) const void operator ()(const cv::Range& range) const CV_OVERRIDE
{ {
Mat Desc, PatchTrans; Mat Desc, PatchTrans;
Mat Patch( 64, 64, CV_32F ); Mat Patch( 64, 64, CV_32F );
......
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