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Merge pull request #2352 from ilya-lavrenov:flann

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pull/2341/merge
Andrey Pavlenko 11 years ago committed by OpenCV Buildbot
parent 2409812803 6ad7b64912
commit ff9a0815b9
8 changed files with 82 additions and 72 deletions
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  1. 20
      modules/features2d/doc/common_interfaces_of_descriptor_matchers.rst
  2. 24
      modules/features2d/doc/common_interfaces_of_generic_descriptor_matchers.rst
  3. 38
      modules/features2d/include/opencv2/features2d.hpp
  4. 48
      modules/features2d/src/matchers.cpp
  5. 8
      modules/features2d/src/mser.cpp
  6. 8
      modules/legacy/include/opencv2/legacy.hpp
  7. 4
      modules/legacy/src/oneway.cpp
  8. 4
      modules/legacy/src/planardetect.cpp

20
modules/features2d/doc/common_interfaces_of_descriptor_matchers.rst
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@ -28,7 +28,7 @@ with an image set. ::
public:
virtual ~DescriptorMatcher();
virtual void add( InputArray descriptors );
virtual void add( InputArrayOfArrays descriptors );
const vector<Mat>& getTrainDescriptors() const;
virtual void clear();
@ -44,20 +44,20 @@ with an image set. ::
vector<DMatch>& matches, InputArray mask=noArray() ) const;
void knnMatch( InputArray queryDescriptors, InputArray trainDescriptors,
vector<vector<DMatch> >& matches, int k,
InputArray mask=Mat(), bool compactResult=false ) const;
InputArray mask=noArray(), bool compactResult=false ) const;
void radiusMatch( InputArray queryDescriptors, InputArray trainDescriptors,
vector<vector<DMatch> >& matches, float maxDistance,
InputArray mask=Mat(), bool compactResult=false ) const;
InputArray mask=noArray(), bool compactResult=false ) const;
/*
* Group of methods to match descriptors from one image to an image set.
*/
void match( InputArray queryDescriptors, vector<DMatch>& matches,
const vector<Mat>& masks=noArray() );
InputArrayOfArrays masks=noArray() );
void knnMatch( InputArray queryDescriptors, vector<vector<DMatch> >& matches,
int k, const vector<Mat>& masks=vector<Mat>(),
int k, InputArrayOfArrays masks=noArray(),
bool compactResult=false );
void radiusMatch( InputArray queryDescriptors, vector<vector<DMatch> >& matches,
float maxDistance, const vector<Mat>& masks=vector<Mat>(),
float maxDistance, InputArrayOfArrays masks=noArray(),
bool compactResult=false );
virtual void read( const FileNode& );
@ -133,7 +133,7 @@ Finds the best match for each descriptor from a query set.
.. ocv:function:: void DescriptorMatcher::match( InputArray queryDescriptors, InputArray trainDescriptors, vector<DMatch>& matches, InputArray mask=noArray() ) const
.. ocv:function:: void DescriptorMatcher::match(InputArray queryDescriptors, vector<DMatch>& matches, const vector<Mat>& masks=vector<Mat>() )
.. ocv:function:: void DescriptorMatcher::match(InputArray queryDescriptors, vector<DMatch>& matches, InputArrayOfArrays masks=noArray() )
:param queryDescriptors: Query set of descriptors.
@ -155,7 +155,7 @@ Finds the k best matches for each descriptor from a query set.
.. ocv:function:: void DescriptorMatcher::knnMatch(InputArray queryDescriptors, InputArray trainDescriptors, vector<vector<DMatch> >& matches, int k, InputArray mask=noArray(), bool compactResult=false ) const
.. ocv:function:: void DescriptorMatcher::knnMatch( InputArray queryDescriptors, vector<vector<DMatch> >& matches, int k, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
.. ocv:function:: void DescriptorMatcher::knnMatch( InputArray queryDescriptors, vector<vector<DMatch> >& matches, int k, InputArrayOfArrays masks=noArray(), bool compactResult=false )
:param queryDescriptors: Query set of descriptors.
@ -181,7 +181,7 @@ For each query descriptor, finds the training descriptors not farther than the s
.. ocv:function:: void DescriptorMatcher::radiusMatch( InputArray queryDescriptors, InputArray trainDescriptors, vector<vector<DMatch> >& matches, float maxDistance, InputArray mask=noArray(), bool compactResult=false ) const
.. ocv:function:: void DescriptorMatcher::radiusMatch( InputArray queryDescriptors, vector<vector<DMatch> >& matches, float maxDistance, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
.. ocv:function:: void DescriptorMatcher::radiusMatch( InputArray queryDescriptors, vector<vector<DMatch> >& matches, float maxDistance, InputArrayOfArrays masks=noArray(), bool compactResult=false )
:param queryDescriptors: Query set of descriptors.
@ -265,7 +265,7 @@ Flann-based descriptor matcher. This matcher trains :ocv:class:`flann::Index_` o
const Ptr<flann::IndexParams>& indexParams=new flann::KDTreeIndexParams(),
const Ptr<flann::SearchParams>& searchParams=new flann::SearchParams() );
virtual void add( const vector<Mat>& descriptors );
virtual void add( InputArrayOfArrays descriptors );
virtual void clear();
virtual void train();

24
modules/features2d/doc/common_interfaces_of_generic_descriptor_matchers.rst
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@ -52,26 +52,26 @@ Abstract interface for extracting and matching a keypoint descriptor. There are
*/
void match( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
InputArray trainImage, vector<KeyPoint>& trainKeypoints,
vector<DMatch>& matches, const Mat& mask=Mat() ) const;
vector<DMatch>& matches, InputArray mask=noArray() ) const;
void knnMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
InputArray trainImage, vector<KeyPoint>& trainKeypoints,
vector<vector<DMatch> >& matches, int k,
const Mat& mask=Mat(), bool compactResult=false ) const;
InputArray mask=noArray(), bool compactResult=false ) const;
void radiusMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
InputArray trainImage, vector<KeyPoint>& trainKeypoints,
vector<vector<DMatch> >& matches, float maxDistance,
const Mat& mask=Mat(), bool compactResult=false ) const;
InputArray mask=noArray(), bool compactResult=false ) const;
/*
* Group of methods to match keypoints from one image to an image set.
*/
void match( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
vector<DMatch>& matches, const vector<Mat>& masks=vector<Mat>() );
vector<DMatch>& matches, InputArrayOfArrays masks=noArray() );
void knnMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
vector<vector<DMatch> >& matches, int k,
const vector<Mat>& masks=vector<Mat>(), bool compactResult=false );
InputArrayOfArrays masks=noArray(), bool compactResult=false );
void radiusMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints,
vector<vector<DMatch> >& matches, float maxDistance,
const vector<Mat>& masks=vector<Mat>(), bool compactResult=false );
InputArrayOfArrays masks=noArray(), bool compactResult=false );
virtual void read( const FileNode& );
virtual void write( FileStorage& ) const;
@ -170,9 +170,9 @@ GenericDescriptorMatcher::match
-----------------------------------
Finds the best match in the training set for each keypoint from the query set.
.. ocv:function:: void GenericDescriptorMatcher::match(InputArray queryImage, vector<KeyPoint>& queryKeypoints, InputArray trainImage, vector<KeyPoint>& trainKeypoints, vector<DMatch>& matches, const Mat& mask=Mat() ) const
.. ocv:function:: void GenericDescriptorMatcher::match(InputArray queryImage, vector<KeyPoint>& queryKeypoints, InputArray trainImage, vector<KeyPoint>& trainKeypoints, vector<DMatch>& matches, InputArray mask=noArray() ) const
.. ocv:function:: void GenericDescriptorMatcher::match( InputArray queryImage, vector<KeyPoint>& queryKeypoints, vector<DMatch>& matches, const vector<Mat>& masks=vector<Mat>() )
.. ocv:function:: void GenericDescriptorMatcher::match( InputArray queryImage, vector<KeyPoint>& queryKeypoints, vector<DMatch>& matches, InputArrayOfArrays masks=noArray() )
:param queryImage: Query image.
@ -196,9 +196,9 @@ GenericDescriptorMatcher::knnMatch
--------------------------------------
Finds the ``k`` best matches for each query keypoint.
.. ocv:function:: void GenericDescriptorMatcher::knnMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, InputArray trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, int k, const Mat& mask=Mat(), bool compactResult=false ) const
.. ocv:function:: void GenericDescriptorMatcher::knnMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, InputArray trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, int k, InputArray mask=noArray(), bool compactResult=false ) const
.. ocv:function:: void GenericDescriptorMatcher::knnMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, int k, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
.. ocv:function:: void GenericDescriptorMatcher::knnMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, int k, InputArrayOfArrays masks=noArray(), bool compactResult=false )
The methods are extended variants of ``GenericDescriptorMatch::match``. The parameters are similar, and the semantics is similar to ``DescriptorMatcher::knnMatch``. But this class does not require explicitly computed keypoint descriptors.
@ -208,9 +208,9 @@ GenericDescriptorMatcher::radiusMatch
-----------------------------------------
For each query keypoint, finds the training keypoints not farther than the specified distance.
.. ocv:function:: void GenericDescriptorMatcher::radiusMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, InputArray trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, float maxDistance, const Mat& mask=Mat(), bool compactResult=false ) const
.. ocv:function:: void GenericDescriptorMatcher::radiusMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, InputArray trainImage, vector<KeyPoint>& trainKeypoints, vector<vector<DMatch> >& matches, float maxDistance, InputArray mask=noArray(), bool compactResult=false ) const
.. ocv:function:: void GenericDescriptorMatcher::radiusMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, float maxDistance, const vector<Mat>& masks=vector<Mat>(), bool compactResult=false )
.. ocv:function:: void GenericDescriptorMatcher::radiusMatch( InputArray queryImage, vector<KeyPoint>& queryKeypoints, vector<vector<DMatch> >& matches, float maxDistance, InputArrayOfArrays masks=noArray(), bool compactResult=false )
The methods are similar to ``DescriptorMatcher::radius``. But this class does not require explicitly computed keypoint descriptors.

38
modules/features2d/include/opencv2/features2d.hpp
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@ -465,8 +465,8 @@ public:
double _min_margin=0.003, int _edge_blur_size=5 );
//! the operator that extracts the MSERs from the image or the specific part of it
CV_WRAP_AS(detect) void operator()( const Mat& image, CV_OUT std::vector<std::vector<Point> >& msers,
const Mat& mask=Mat() ) const;
CV_WRAP_AS(detect) void operator()( InputArray image, CV_OUT std::vector<std::vector<Point> >& msers,
InputArray mask=noArray() ) const;
AlgorithmInfo* info() const;
protected:
@ -1053,11 +1053,11 @@ public:
* See description of similar methods for matching image pair above.
*/
CV_WRAP void match( InputArray queryDescriptors, CV_OUT std::vector<DMatch>& matches,
const std::vector<Mat>& masks=std::vector<Mat>() );
InputArrayOfArrays masks=noArray() );
CV_WRAP void knnMatch( InputArray queryDescriptors, CV_OUT std::vector<std::vector<DMatch> >& matches, int k,
const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false );
InputArrayOfArrays masks=noArray(), bool compactResult=false );
void radiusMatch( InputArray queryDescriptors, std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false );
InputArrayOfArrays masks=noArray(), bool compactResult=false );
// Reads matcher object from a file node
virtual void read( const FileNode& );
@ -1106,11 +1106,11 @@ protected:
virtual void radiusMatchImpl( InputArray queryDescriptors, std::vector<std::vector<DMatch> >& matches, float maxDistance,
InputArrayOfArrays masks=noArray(), bool compactResult=false ) = 0;
static bool isPossibleMatch( const Mat& mask, int queryIdx, int trainIdx );
static bool isMaskedOut( const std::vector<Mat>& masks, int queryIdx );
static bool isPossibleMatch( InputArray mask, int queryIdx, int trainIdx );
static bool isMaskedOut( InputArrayOfArrays masks, int queryIdx );
static Mat clone_op( Mat m ) { return m.clone(); }
void checkMasks( const std::vector<Mat>& masks, int queryDescriptorsCount ) const;
void checkMasks( InputArrayOfArrays masks, int queryDescriptorsCount ) const;
// Collection of descriptors from train images.
std::vector<Mat> trainDescCollection;
@ -1157,7 +1157,7 @@ public:
CV_WRAP FlannBasedMatcher( const Ptr<flann::IndexParams>& indexParams=makePtr<flann::KDTreeIndexParams>(),
const Ptr<flann::SearchParams>& searchParams=makePtr<flann::SearchParams>() );
virtual void add( const std::vector<Mat>& descriptors );
virtual void add( InputArrayOfArrays descriptors );
virtual void clear();
// Reads matcher object from a file node
@ -1256,7 +1256,7 @@ public:
// Find one best match for each query descriptor (if mask is empty).
void match( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
InputArray trainImage, std::vector<KeyPoint>& trainKeypoints,
std::vector<DMatch>& matches, const Mat& mask=Mat() ) const;
std::vector<DMatch>& matches, InputArray mask=noArray() ) const;
// Find k best matches for each query keypoint (in increasing order of distances).
// compactResult is used when mask is not empty. If compactResult is false matches
// vector will have the same size as queryDescriptors rows.
@ -1264,24 +1264,24 @@ public:
void knnMatch( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
InputArray trainImage, std::vector<KeyPoint>& trainKeypoints,
std::vector<std::vector<DMatch> >& matches, int k,
const Mat& mask=Mat(), bool compactResult=false ) const;
InputArray mask=noArray(), bool compactResult=false ) const;
// Find best matches for each query descriptor which have distance less than maxDistance (in increasing order of distances).
void radiusMatch( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
InputArray trainImage, std::vector<KeyPoint>& trainKeypoints,
std::vector<std::vector<DMatch> >& matches, float maxDistance,
const Mat& mask=Mat(), bool compactResult=false ) const;
InputArray mask=noArray(), bool compactResult=false ) const;
/*
* Group of methods to match keypoints from one image to image set.
* See description of similar methods for matching image pair above.
*/
void match( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<DMatch>& matches, const std::vector<Mat>& masks=std::vector<Mat>() );
std::vector<DMatch>& matches, InputArrayOfArrays masks=noArray() );
void knnMatch( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, int k,
const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false );
InputArrayOfArrays masks=noArray(), bool compactResult=false );
void radiusMatch(InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& masks=std::vector<Mat>(), bool compactResult=false );
InputArrayOfArrays masks=noArray(), bool compactResult=false );
// Reads matcher object from a file node
virtual void read( const FileNode& fn );
@ -1305,10 +1305,10 @@ protected:
// after calling train().
virtual void knnMatchImpl( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, int k,
const std::vector<Mat>& masks, bool compactResult ) = 0;
InputArrayOfArrays masks, bool compactResult ) = 0;
virtual void radiusMatchImpl( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& masks, bool compactResult ) = 0;
InputArrayOfArrays masks, bool compactResult ) = 0;
/*
* A storage for sets of keypoints together with corresponding images and class IDs
*/
@ -1383,10 +1383,10 @@ public:
protected:
virtual void knnMatchImpl( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, int k,
const std::vector<Mat>& masks, bool compactResult );
InputArrayOfArrays masks, bool compactResult );
virtual void radiusMatchImpl( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& masks, bool compactResult );
InputArrayOfArrays masks, bool compactResult );
Ptr<DescriptorExtractor> extractor;
Ptr<DescriptorMatcher> matcher;

48
modules/features2d/src/matchers.cpp
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@ -791,15 +791,18 @@ void DescriptorMatcher::radiusMatch( InputArray queryDescriptors, InputArray tra
tempMatcher->radiusMatch( queryDescriptors, matches, maxDistance, std::vector<Mat>(1, mask.getMat()), compactResult );
}
void DescriptorMatcher::match( InputArray queryDescriptors, std::vector<DMatch>& matches, const std::vector<Mat>& masks )
void DescriptorMatcher::match( InputArray queryDescriptors, std::vector<DMatch>& matches, InputArrayOfArrays masks )
{
std::vector<std::vector<DMatch> > knnMatches;
knnMatch( queryDescriptors, knnMatches, 1, masks, true /*compactResult*/ );
convertMatches( knnMatches, matches );
}
void DescriptorMatcher::checkMasks( const std::vector<Mat>& masks, int queryDescriptorsCount ) const
void DescriptorMatcher::checkMasks( InputArrayOfArrays _masks, int queryDescriptorsCount ) const
{
std::vector<Mat> masks;
_masks.getMatVector(masks);
if( isMaskSupported() && !masks.empty() )
{
// Check masks
@ -819,7 +822,7 @@ void DescriptorMatcher::checkMasks( const std::vector<Mat>& masks, int queryDesc
}
void DescriptorMatcher::knnMatch( InputArray queryDescriptors, std::vector<std::vector<DMatch> >& matches, int knn,
const std::vector<Mat>& masks, bool compactResult )
InputArrayOfArrays masks, bool compactResult )
{
if( empty() || queryDescriptors.empty() )
return;
@ -833,7 +836,7 @@ void DescriptorMatcher::knnMatch( InputArray queryDescriptors, std::vector<std::
}
void DescriptorMatcher::radiusMatch( InputArray queryDescriptors, std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& masks, bool compactResult )
InputArrayOfArrays masks, bool compactResult )
{
matches.clear();
if( empty() || queryDescriptors.empty() )
@ -853,13 +856,17 @@ void DescriptorMatcher::read( const FileNode& )
void DescriptorMatcher::write( FileStorage& ) const
{}
bool DescriptorMatcher::isPossibleMatch( const Mat& mask, int queryIdx, int trainIdx )
bool DescriptorMatcher::isPossibleMatch( InputArray _mask, int queryIdx, int trainIdx )
{
Mat mask = _mask.getMat();
return mask.empty() || mask.at<uchar>(queryIdx, trainIdx);
}
bool DescriptorMatcher::isMaskedOut( const std::vector<Mat>& masks, int queryIdx )
bool DescriptorMatcher::isMaskedOut( InputArrayOfArrays _masks, int queryIdx )
{
std::vector<Mat> masks;
_masks.getMatVector(masks);
size_t outCount = 0;
for( size_t i = 0; i < masks.size(); i++ )
{
@ -1199,9 +1206,12 @@ FlannBasedMatcher::FlannBasedMatcher( const Ptr<flann::IndexParams>& _indexParam
CV_Assert( _searchParams );
}
void FlannBasedMatcher::add( const std::vector<Mat>& descriptors )
void FlannBasedMatcher::add( InputArrayOfArrays _descriptors )
{
DescriptorMatcher::add( descriptors );
DescriptorMatcher::add( _descriptors );
std::vector<Mat> descriptors;
_descriptors.getMatVector(descriptors);
for( size_t i = 0; i < descriptors.size(); i++ )
{
addedDescCount += descriptors[i].rows;
@ -1676,43 +1686,43 @@ void GenericDescriptorMatcher::classify( InputArray queryImage, std::vector<KeyP
void GenericDescriptorMatcher::match( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
InputArray _trainImage, std::vector<KeyPoint>& trainKeypoints,
std::vector<DMatch>& matches, const Mat& mask ) const
std::vector<DMatch>& matches, InputArray mask ) const
{
Mat trainImage = _trainImage.getMat();
Ptr<GenericDescriptorMatcher> tempMatcher = clone( true );
std::vector<std::vector<KeyPoint> > vecTrainPoints(1, trainKeypoints);
tempMatcher->add( std::vector<Mat>(1, trainImage), vecTrainPoints );
tempMatcher->match( queryImage, queryKeypoints, matches, std::vector<Mat>(1, mask) );
tempMatcher->match( queryImage, queryKeypoints, matches, std::vector<Mat>(1, mask.getMat()) );
vecTrainPoints[0].swap( trainKeypoints );
}
void GenericDescriptorMatcher::knnMatch( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
InputArray _trainImage, std::vector<KeyPoint>& trainKeypoints,
std::vector<std::vector<DMatch> >& matches, int knn, const Mat& mask, bool compactResult ) const
std::vector<std::vector<DMatch> >& matches, int knn, InputArray mask, bool compactResult ) const
{
Mat trainImage = _trainImage.getMat();
Ptr<GenericDescriptorMatcher> tempMatcher = clone( true );
std::vector<std::vector<KeyPoint> > vecTrainPoints(1, trainKeypoints);
tempMatcher->add( std::vector<Mat>(1, trainImage), vecTrainPoints );
tempMatcher->knnMatch( queryImage, queryKeypoints, matches, knn, std::vector<Mat>(1, mask), compactResult );
tempMatcher->knnMatch( queryImage, queryKeypoints, matches, knn, std::vector<Mat>(1, mask.getMat()), compactResult );
vecTrainPoints[0].swap( trainKeypoints );
}
void GenericDescriptorMatcher::radiusMatch( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
InputArray _trainImage, std::vector<KeyPoint>& trainKeypoints,
std::vector<std::vector<DMatch> >& matches, float maxDistance,
const Mat& mask, bool compactResult ) const
InputArray mask, bool compactResult ) const
{
Mat trainImage = _trainImage.getMat();
Ptr<GenericDescriptorMatcher> tempMatcher = clone( true );
std::vector<std::vector<KeyPoint> > vecTrainPoints(1, trainKeypoints);
tempMatcher->add( std::vector<Mat>(1, trainImage), vecTrainPoints );
tempMatcher->radiusMatch( queryImage, queryKeypoints, matches, maxDistance, std::vector<Mat>(1, mask), compactResult );
tempMatcher->radiusMatch( queryImage, queryKeypoints, matches, maxDistance, std::vector<Mat>(1, mask.getMat()), compactResult );
vecTrainPoints[0].swap( trainKeypoints );
}
void GenericDescriptorMatcher::match( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<DMatch>& matches, const std::vector<Mat>& masks )
std::vector<DMatch>& matches, InputArrayOfArrays masks )
{
std::vector<std::vector<DMatch> > knnMatches;
knnMatch( queryImage, queryKeypoints, knnMatches, 1, masks, false );
@ -1721,7 +1731,7 @@ void GenericDescriptorMatcher::match( InputArray queryImage, std::vector<KeyPoin
void GenericDescriptorMatcher::knnMatch( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, int knn,
const std::vector<Mat>& masks, bool compactResult )
InputArrayOfArrays masks, bool compactResult )
{
matches.clear();
@ -1737,7 +1747,7 @@ void GenericDescriptorMatcher::knnMatch( InputArray queryImage, std::vector<KeyP
void GenericDescriptorMatcher::radiusMatch( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& masks, bool compactResult )
InputArrayOfArrays masks, bool compactResult )
{
matches.clear();
@ -1828,7 +1838,7 @@ bool VectorDescriptorMatcher::isMaskSupported()
void VectorDescriptorMatcher::knnMatchImpl( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, int knn,
const std::vector<Mat>& masks, bool compactResult )
InputArrayOfArrays masks, bool compactResult )
{
Mat queryDescriptors;
extractor->compute( queryImage, queryKeypoints, queryDescriptors );
@ -1837,7 +1847,7 @@ void VectorDescriptorMatcher::knnMatchImpl( InputArray queryImage, std::vector<K
void VectorDescriptorMatcher::radiusMatchImpl( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& masks, bool compactResult )
InputArrayOfArrays masks, bool compactResult )
{
Mat queryDescriptors;
extractor->compute( queryImage, queryKeypoints, queryDescriptors );

8
modules/features2d/src/mser.cpp
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@ -1266,11 +1266,11 @@ MSER::MSER( int _delta, int _min_area, int _max_area,
{
}
void MSER::operator()( const Mat& image, std::vector<std::vector<Point> >& dstcontours, const Mat& mask ) const
void MSER::operator()( InputArray image, std::vector<std::vector<Point> >& dstcontours, InputArray mask ) const
{
CvMat _image = image, _mask, *pmask = 0;
if( mask.data )
pmask = &(_mask = mask);
CvMat _image = image.getMat(), _mask, *pmask = 0;
if( !mask.empty() )
pmask = &(_mask = mask.getMat());
MemStorage storage(cvCreateMemStorage(0));
Seq<CvSeq*> contours;
extractMSER( &_image, pmask, &contours.seq, storage,

8
modules/legacy/include/opencv2/legacy.hpp
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@ -2674,10 +2674,10 @@ protected:
// loaded with DescriptorOneWay::Initialize, kd tree is used for finding minimum distances.
virtual void knnMatchImpl( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, int k,
const std::vector<Mat>& masks, bool compactResult );
InputArrayOfArrays masks, bool compactResult );
virtual void radiusMatchImpl( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& masks, bool compactResult );
InputArrayOfArrays masks, bool compactResult );
Ptr<OneWayDescriptorBase> base;
Params params;
@ -2737,10 +2737,10 @@ public:
protected:
virtual void knnMatchImpl( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, int k,
const std::vector<Mat>& masks, bool compactResult );
InputArrayOfArrays masks, bool compactResult );
virtual void radiusMatchImpl( InputArray queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& masks, bool compactResult );
InputArrayOfArrays masks, bool compactResult );
void trainFernClassifier();
void calcBestProbAndMatchIdx( const Mat& image, const Point2f& pt,

4
modules/legacy/src/oneway.cpp
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@ -2234,7 +2234,7 @@ namespace cv{
void OneWayDescriptorMatcher::knnMatchImpl( InputArray _queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, int knn,
const std::vector<Mat>& /*masks*/, bool /*compactResult*/ )
InputArrayOfArrays /*masks*/, bool /*compactResult*/ )
{
Mat queryImage = _queryImage.getMat();
train();
@ -2254,7 +2254,7 @@ namespace cv{
void OneWayDescriptorMatcher::radiusMatchImpl( InputArray _queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& /*masks*/, bool /*compactResult*/ )
InputArrayOfArrays /*masks*/, bool /*compactResult*/ )
{
Mat queryImage = _queryImage.getMat();

4
modules/legacy/src/planardetect.cpp
Unescape View File

@ -1299,7 +1299,7 @@ void FernDescriptorMatcher::calcBestProbAndMatchIdx( const Mat& image, const Poi
void FernDescriptorMatcher::knnMatchImpl( InputArray _queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, int knn,
const std::vector<Mat>& /*masks*/, bool /*compactResult*/ )
InputArrayOfArrays /*masks*/, bool /*compactResult*/ )
{
Mat queryImage = _queryImage.getMat();
@ -1337,7 +1337,7 @@ void FernDescriptorMatcher::knnMatchImpl( InputArray _queryImage, std::vector<Ke
void FernDescriptorMatcher::radiusMatchImpl( InputArray _queryImage, std::vector<KeyPoint>& queryKeypoints,
std::vector<std::vector<DMatch> >& matches, float maxDistance,
const std::vector<Mat>& /*masks*/, bool /*compactResult*/ )
InputArrayOfArrays /*masks*/, bool /*compactResult*/ )
{
Mat queryImage = _queryImage.getMat();
train();

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