DescriptorMatcher

Overview

Package

Class

Tree

Index

Help

OpenCV 2.4.6

PREV CLASS NEXT CLASS

FRAMES NO FRAMES

SUMMARY: NESTED | FIELD | CONSTR | METHOD

DETAIL: FIELD | CONSTR | METHOD

org.opencv.features2d
Class DescriptorMatcher

java.lang.Object
  org.opencv.features2d.DescriptorMatcher

public class DescriptorMatcher
extends java.lang.Object
extends java.lang.Object

Abstract base class for matching keypoint descriptors. It has two groups of match methods: for matching descriptors of an image with another image or with an image set.

class DescriptorMatcher



 // C++ code:


 public:

 virtual ~DescriptorMatcher();

 virtual void add(const vector& descriptors);

 const vector& getTrainDescriptors() const;

 virtual void clear();

 bool empty() const;

 virtual bool isMaskSupported() const = 0;

 virtual void train();

 / *
 
    Group of methods to match descriptors from an image pair.
   
 /
 

 void match(const Mat& queryDescriptors, const Mat& trainDescriptors,

 vector& matches, const Mat& mask=Mat()) const;

 void knnMatch(const Mat& queryDescriptors, const Mat& trainDescriptors,

 vector >& matches, int k,

 const Mat& mask=Mat(), bool compactResult=false) const;

 void radiusMatch(const Mat& queryDescriptors, const Mat& trainDescriptors,

 vector >& matches, float maxDistance,

 const Mat& mask=Mat(), bool compactResult=false) const;

 / *
 
    Group of methods to match descriptors from one image to an image set.
   
 /
 

 void match(const Mat& queryDescriptors, vector& matches,

 const vector& masks=vector());

 void knnMatch(const Mat& queryDescriptors, vector >& matches,

 int k, const vector& masks=vector(),

 bool compactResult=false);

 void radiusMatch(const Mat& queryDescriptors, vector >&
 matches,

 float maxDistance, const vector& masks=vector(),

 bool compactResult=false);

 virtual void read(const FileNode&);

 virtual void write(FileStorage&) const;

 virtual Ptr clone(bool emptyTrainData=false) const = 0;

 static Ptr create(const string& descriptorMatcherType);

 protected:

 vector trainDescCollection;...

 };




See Also:
org.opencv.features2d.DescriptorMatcher : public Algorithm









Field Summary



static int
BRUTEFORCE



           



static int
BRUTEFORCE_HAMMING



           



static int
BRUTEFORCE_HAMMINGLUT



           



static int
BRUTEFORCE_L1



           



static int
BRUTEFORCE_SL2



           



static int
FLANNBASED



           


 






Method Summary



 void
add(java.util.List<Mat> descriptors)



          Adds descriptors to train a descriptor collection.



 void
clear()



          Clears the train descriptor collection.



 DescriptorMatcher
clone()



           



 DescriptorMatcher
clone(boolean emptyTrainData)



           



static DescriptorMatcher
create(int matcherType)



          Creates a descriptor matcher of a given type with the default parameters
 (using default constructor).



 boolean
empty()



          Returns true if there are no train descriptors in the collection.



 java.util.List<Mat>
getTrainDescriptors()



          Returns a constant link to the train descriptor collection trainDescCollection.



 boolean
isMaskSupported()



          Returns true if the descriptor matcher supports masking permissible matches.



 void
knnMatch(Mat queryDescriptors,
         java.util.List<MatOfDMatch> matches,
         int k)



          Finds the k best matches for each descriptor from a query set.



 void
knnMatch(Mat queryDescriptors,
         java.util.List<MatOfDMatch> matches,
         int k,
         java.util.List<Mat> masks,
         boolean compactResult)



          Finds the k best matches for each descriptor from a query set.



 void
knnMatch(Mat queryDescriptors,
         Mat trainDescriptors,
         java.util.List<MatOfDMatch> matches,
         int k)



          Finds the k best matches for each descriptor from a query set.



 void
knnMatch(Mat queryDescriptors,
         Mat trainDescriptors,
         java.util.List<MatOfDMatch> matches,
         int k,
         Mat mask,
         boolean compactResult)



          Finds the k best matches for each descriptor from a query set.



 void
match(Mat queryDescriptors,
      Mat trainDescriptors,
      MatOfDMatch matches)



          Finds the best match for each descriptor from a query set.



 void
match(Mat queryDescriptors,
      Mat trainDescriptors,
      MatOfDMatch matches,
      Mat mask)



          Finds the best match for each descriptor from a query set.



 void
match(Mat queryDescriptors,
      MatOfDMatch matches)



          Finds the best match for each descriptor from a query set.



 void
match(Mat queryDescriptors,
      MatOfDMatch matches,
      java.util.List<Mat> masks)



          Finds the best match for each descriptor from a query set.



 void
radiusMatch(Mat queryDescriptors,
            java.util.List<MatOfDMatch> matches,
            float maxDistance)



          For each query descriptor, finds the training descriptors not farther than
 the specified distance.



 void
radiusMatch(Mat queryDescriptors,
            java.util.List<MatOfDMatch> matches,
            float maxDistance,
            java.util.List<Mat> masks,
            boolean compactResult)



          For each query descriptor, finds the training descriptors not farther than
 the specified distance.



 void
radiusMatch(Mat queryDescriptors,
            Mat trainDescriptors,
            java.util.List<MatOfDMatch> matches,
            float maxDistance)



          For each query descriptor, finds the training descriptors not farther than
 the specified distance.



 void
radiusMatch(Mat queryDescriptors,
            Mat trainDescriptors,
            java.util.List<MatOfDMatch> matches,
            float maxDistance,
            Mat mask,
            boolean compactResult)



          For each query descriptor, finds the training descriptors not farther than
 the specified distance.



 void
read(java.lang.String fileName)



           



 void
train()



          Trains a descriptor matcher



 void
write(java.lang.String fileName)



           


 


Methods inherited from class java.lang.Object


equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait


 








Field Detail




BRUTEFORCE
public static final int BRUTEFORCE


See Also:
Constant Field Values




BRUTEFORCE_HAMMING
public static final int BRUTEFORCE_HAMMING


See Also:
Constant Field Values




BRUTEFORCE_HAMMINGLUT
public static final int BRUTEFORCE_HAMMINGLUT


See Also:
Constant Field Values




BRUTEFORCE_L1
public static final int BRUTEFORCE_L1


See Also:
Constant Field Values




BRUTEFORCE_SL2
public static final int BRUTEFORCE_SL2


See Also:
Constant Field Values




FLANNBASED
public static final int FLANNBASED


See Also:
Constant Field Values








Method Detail




add
public void add(java.util.List<Mat> descriptors)

Adds descriptors to train a descriptor collection. If the collection
 trainDescCollectionis is not empty, the new descriptors are
 added to existing train descriptors.


Parameters:
descriptors - Descriptors to add. Each descriptors[i] is a
 set of descriptors from the same train image.
See Also:
org.opencv.features2d.DescriptorMatcher.add





clear
public void clear()

Clears the train descriptor collection.


See Also:
org.opencv.features2d.DescriptorMatcher.clear





clone
public DescriptorMatcher clone()


Overrides:
clone in class java.lang.Object








clone
public DescriptorMatcher clone(boolean emptyTrainData)








create
public static DescriptorMatcher create(int matcherType)

Creates a descriptor matcher of a given type with the default parameters
 (using default constructor).


Parameters:
matcherType - a matcherType
See Also:
org.opencv.features2d.DescriptorMatcher.create





empty
public boolean empty()

Returns true if there are no train descriptors in the collection.


See Also:
org.opencv.features2d.DescriptorMatcher.empty





getTrainDescriptors
public java.util.List<Mat> getTrainDescriptors()

Returns a constant link to the train descriptor collection trainDescCollection.


See Also:
org.opencv.features2d.DescriptorMatcher.getTrainDescriptors





isMaskSupported
public boolean isMaskSupported()

Returns true if the descriptor matcher supports masking permissible matches.


See Also:
org.opencv.features2d.DescriptorMatcher.isMaskSupported





knnMatch
public void knnMatch(Mat queryDescriptors,
                     java.util.List<MatOfDMatch> matches,
                     int k)

Finds the k best matches for each descriptor from a query set.

 These extended variants of "DescriptorMatcher.match" methods find several
 best matches for each query descriptor. The matches are returned in the
 distance increasing order. See "DescriptorMatcher.match" for the details
 about query and train descriptors.


Parameters:
queryDescriptors - Query set of descriptors.
matches - Matches. Each matches[i] is k or less matches for
 the same query descriptor.
k - Count of best matches found per each query descriptor or less if a
 query descriptor has less than k possible matches in total.
See Also:
org.opencv.features2d.DescriptorMatcher.knnMatch





knnMatch
public void knnMatch(Mat queryDescriptors,
                     java.util.List<MatOfDMatch> matches,
                     int k,
                     java.util.List<Mat> masks,
                     boolean compactResult)

Finds the k best matches for each descriptor from a query set.

 These extended variants of "DescriptorMatcher.match" methods find several
 best matches for each query descriptor. The matches are returned in the
 distance increasing order. See "DescriptorMatcher.match" for the details
 about query and train descriptors.


Parameters:
queryDescriptors - Query set of descriptors.
matches - Matches. Each matches[i] is k or less matches for
 the same query descriptor.
k - Count of best matches found per each query descriptor or less if a
 query descriptor has less than k possible matches in total.
masks - Set of masks. Each masks[i] specifies permissible
 matches between the input query descriptors and stored train descriptors from
 the i-th image trainDescCollection[i].
compactResult - Parameter used when the mask (or masks) is not empty. If
 compactResult is false, the matches vector has the
 same size as queryDescriptors rows. If compactResult
 is true, the matches vector does not contain matches for fully
 masked-out query descriptors.
See Also:
org.opencv.features2d.DescriptorMatcher.knnMatch





knnMatch
public void knnMatch(Mat queryDescriptors,
                     Mat trainDescriptors,
                     java.util.List<MatOfDMatch> matches,
                     int k)

Finds the k best matches for each descriptor from a query set.

 These extended variants of "DescriptorMatcher.match" methods find several
 best matches for each query descriptor. The matches are returned in the
 distance increasing order. See "DescriptorMatcher.match" for the details
 about query and train descriptors.


Parameters:
queryDescriptors - Query set of descriptors.
trainDescriptors - Train set of descriptors. This set is not added to
 the train descriptors collection stored in the class object.
matches - Matches. Each matches[i] is k or less matches for
 the same query descriptor.
k - Count of best matches found per each query descriptor or less if a
 query descriptor has less than k possible matches in total.
See Also:
org.opencv.features2d.DescriptorMatcher.knnMatch





knnMatch
public void knnMatch(Mat queryDescriptors,
                     Mat trainDescriptors,
                     java.util.List<MatOfDMatch> matches,
                     int k,
                     Mat mask,
                     boolean compactResult)

Finds the k best matches for each descriptor from a query set.

 These extended variants of "DescriptorMatcher.match" methods find several
 best matches for each query descriptor. The matches are returned in the
 distance increasing order. See "DescriptorMatcher.match" for the details
 about query and train descriptors.


Parameters:
queryDescriptors - Query set of descriptors.
trainDescriptors - Train set of descriptors. This set is not added to
 the train descriptors collection stored in the class object.
matches - Matches. Each matches[i] is k or less matches for
 the same query descriptor.
k - Count of best matches found per each query descriptor or less if a
 query descriptor has less than k possible matches in total.
mask - Mask specifying permissible matches between an input query and
 train matrices of descriptors.
compactResult - Parameter used when the mask (or masks) is not empty. If
 compactResult is false, the matches vector has the
 same size as queryDescriptors rows. If compactResult
 is true, the matches vector does not contain matches for fully
 masked-out query descriptors.
See Also:
org.opencv.features2d.DescriptorMatcher.knnMatch





match
public void match(Mat queryDescriptors,
                  Mat trainDescriptors,
                  MatOfDMatch matches)

Finds the best match for each descriptor from a query set.

 In the first variant of this method, the train descriptors are passed as an
 input argument. In the second variant of the method, train descriptors
 collection that was set by DescriptorMatcher.add is used.
 Optional mask (or masks) can be passed to specify which query and training
 descriptors can be matched. Namely, queryDescriptors[i] can be
 matched with trainDescriptors[j] only if mask.at(i,j)
 is non-zero.


Parameters:
queryDescriptors - Query set of descriptors.
trainDescriptors - Train set of descriptors. This set is not added to
 the train descriptors collection stored in the class object.
matches - Matches. If a query descriptor is masked out in
 mask, no match is added for this descriptor. So,
 matches size may be smaller than the query descriptors count.
See Also:
org.opencv.features2d.DescriptorMatcher.match





match
public void match(Mat queryDescriptors,
                  Mat trainDescriptors,
                  MatOfDMatch matches,
                  Mat mask)

Finds the best match for each descriptor from a query set.

 In the first variant of this method, the train descriptors are passed as an
 input argument. In the second variant of the method, train descriptors
 collection that was set by DescriptorMatcher.add is used.
 Optional mask (or masks) can be passed to specify which query and training
 descriptors can be matched. Namely, queryDescriptors[i] can be
 matched with trainDescriptors[j] only if mask.at(i,j)
 is non-zero.


Parameters:
queryDescriptors - Query set of descriptors.
trainDescriptors - Train set of descriptors. This set is not added to
 the train descriptors collection stored in the class object.
matches - Matches. If a query descriptor is masked out in
 mask, no match is added for this descriptor. So,
 matches size may be smaller than the query descriptors count.
mask - Mask specifying permissible matches between an input query and
 train matrices of descriptors.
See Also:
org.opencv.features2d.DescriptorMatcher.match





match
public void match(Mat queryDescriptors,
                  MatOfDMatch matches)

Finds the best match for each descriptor from a query set.

 In the first variant of this method, the train descriptors are passed as an
 input argument. In the second variant of the method, train descriptors
 collection that was set by DescriptorMatcher.add is used.
 Optional mask (or masks) can be passed to specify which query and training
 descriptors can be matched. Namely, queryDescriptors[i] can be
 matched with trainDescriptors[j] only if mask.at(i,j)
 is non-zero.


Parameters:
queryDescriptors - Query set of descriptors.
matches - Matches. If a query descriptor is masked out in
 mask, no match is added for this descriptor. So,
 matches size may be smaller than the query descriptors count.
See Also:
org.opencv.features2d.DescriptorMatcher.match





match
public void match(Mat queryDescriptors,
                  MatOfDMatch matches,
                  java.util.List<Mat> masks)

Finds the best match for each descriptor from a query set.

 In the first variant of this method, the train descriptors are passed as an
 input argument. In the second variant of the method, train descriptors
 collection that was set by DescriptorMatcher.add is used.
 Optional mask (or masks) can be passed to specify which query and training
 descriptors can be matched. Namely, queryDescriptors[i] can be
 matched with trainDescriptors[j] only if mask.at(i,j)
 is non-zero.


Parameters:
queryDescriptors - Query set of descriptors.
matches - Matches. If a query descriptor is masked out in
 mask, no match is added for this descriptor. So,
 matches size may be smaller than the query descriptors count.
masks - Set of masks. Each masks[i] specifies permissible
 matches between the input query descriptors and stored train descriptors from
 the i-th image trainDescCollection[i].
See Also:
org.opencv.features2d.DescriptorMatcher.match





radiusMatch
public void radiusMatch(Mat queryDescriptors,
                        java.util.List<MatOfDMatch> matches,
                        float maxDistance)

For each query descriptor, finds the training descriptors not farther than
 the specified distance.

 For each query descriptor, the methods find such training descriptors that
 the distance between the query descriptor and the training descriptor is
 equal or smaller than maxDistance. Found matches are returned in
 the distance increasing order.


Parameters:
queryDescriptors - Query set of descriptors.
matches - Found matches.
maxDistance - Threshold for the distance between matched descriptors.
 Distance means here metric distance (e.g. Hamming distance), not the distance
 between coordinates (which is measured in Pixels)!
See Also:
org.opencv.features2d.DescriptorMatcher.radiusMatch





radiusMatch
public void radiusMatch(Mat queryDescriptors,
                        java.util.List<MatOfDMatch> matches,
                        float maxDistance,
                        java.util.List<Mat> masks,
                        boolean compactResult)

For each query descriptor, finds the training descriptors not farther than
 the specified distance.

 For each query descriptor, the methods find such training descriptors that
 the distance between the query descriptor and the training descriptor is
 equal or smaller than maxDistance. Found matches are returned in
 the distance increasing order.


Parameters:
queryDescriptors - Query set of descriptors.
matches - Found matches.
maxDistance - Threshold for the distance between matched descriptors.
 Distance means here metric distance (e.g. Hamming distance), not the distance
 between coordinates (which is measured in Pixels)!
masks - Set of masks. Each masks[i] specifies permissible
 matches between the input query descriptors and stored train descriptors from
 the i-th image trainDescCollection[i].
compactResult - Parameter used when the mask (or masks) is not empty. If
 compactResult is false, the matches vector has the
 same size as queryDescriptors rows. If compactResult
 is true, the matches vector does not contain matches for fully
 masked-out query descriptors.
See Also:
org.opencv.features2d.DescriptorMatcher.radiusMatch





radiusMatch
public void radiusMatch(Mat queryDescriptors,
                        Mat trainDescriptors,
                        java.util.List<MatOfDMatch> matches,
                        float maxDistance)

For each query descriptor, finds the training descriptors not farther than
 the specified distance.

 For each query descriptor, the methods find such training descriptors that
 the distance between the query descriptor and the training descriptor is
 equal or smaller than maxDistance. Found matches are returned in
 the distance increasing order.


Parameters:
queryDescriptors - Query set of descriptors.
trainDescriptors - Train set of descriptors. This set is not added to
 the train descriptors collection stored in the class object.
matches - Found matches.
maxDistance - Threshold for the distance between matched descriptors.
 Distance means here metric distance (e.g. Hamming distance), not the distance
 between coordinates (which is measured in Pixels)!
See Also:
org.opencv.features2d.DescriptorMatcher.radiusMatch





radiusMatch
public void radiusMatch(Mat queryDescriptors,
                        Mat trainDescriptors,
                        java.util.List<MatOfDMatch> matches,
                        float maxDistance,
                        Mat mask,
                        boolean compactResult)

For each query descriptor, finds the training descriptors not farther than
 the specified distance.

 For each query descriptor, the methods find such training descriptors that
 the distance between the query descriptor and the training descriptor is
 equal or smaller than maxDistance. Found matches are returned in
 the distance increasing order.


Parameters:
queryDescriptors - Query set of descriptors.
trainDescriptors - Train set of descriptors. This set is not added to
 the train descriptors collection stored in the class object.
matches - Found matches.
maxDistance - Threshold for the distance between matched descriptors.
 Distance means here metric distance (e.g. Hamming distance), not the distance
 between coordinates (which is measured in Pixels)!
mask - Mask specifying permissible matches between an input query and
 train matrices of descriptors.
compactResult - Parameter used when the mask (or masks) is not empty. If
 compactResult is false, the matches vector has the
 same size as queryDescriptors rows. If compactResult
 is true, the matches vector does not contain matches for fully
 masked-out query descriptors.
See Also:
org.opencv.features2d.DescriptorMatcher.radiusMatch





read
public void read(java.lang.String fileName)








train
public void train()

Trains a descriptor matcher

 Trains a descriptor matcher (for example, the flann index). In all methods to
 match, the method train() is run every time before matching.
 Some descriptor matchers (for example, BruteForceMatcher) have
 an empty implementation of this method. Other matchers really train their
 inner structures (for example, FlannBasedMatcher trains
 flann.Index).


See Also:
org.opencv.features2d.DescriptorMatcher.train





write
public void write(java.lang.String fileName)

















  
      Overview 
      Package 
    Class 
      Tree 
      Index 
      Help 
  



OpenCV 2.4.6 Documentation





 PREV CLASS 
 NEXT CLASS

  FRAMES   
 NO FRAMES   
 







  SUMMARY: NESTED | FIELD | CONSTR | METHOD

DETAIL: FIELD | CONSTR | METHOD

Field Summary
`static int`	`BRUTEFORCE`
`static int`	`BRUTEFORCE_HAMMING`
`static int`	`BRUTEFORCE_HAMMINGLUT`
`static int`	`BRUTEFORCE_L1`
`static int`	`BRUTEFORCE_SL2`
`static int`	`FLANNBASED`

Method Summary
`void`	`add(java.util.List<Mat> descriptors)` Adds descriptors to train a descriptor collection.
`void`	`clear()` Clears the train descriptor collection.
`DescriptorMatcher`	`clone()`
`DescriptorMatcher`	`clone(boolean emptyTrainData)`
`static DescriptorMatcher`	`create(int matcherType)` Creates a descriptor matcher of a given type with the default parameters (using default constructor).
`boolean`	`empty()` Returns true if there are no train descriptors in the collection.
`java.util.List<Mat>`	`getTrainDescriptors()` Returns a constant link to the train descriptor collection `trainDescCollection`.
`boolean`	`isMaskSupported()` Returns true if the descriptor matcher supports masking permissible matches.
`void`	`knnMatch(Mat queryDescriptors, java.util.List<MatOfDMatch> matches, int k)` Finds the k best matches for each descriptor from a query set.
`void`	`knnMatch(Mat queryDescriptors, java.util.List<MatOfDMatch> matches, int k, java.util.List<Mat> masks, boolean compactResult)` Finds the k best matches for each descriptor from a query set.
`void`	`knnMatch(Mat queryDescriptors, Mat trainDescriptors, java.util.List<MatOfDMatch> matches, int k)` Finds the k best matches for each descriptor from a query set.
`void`	`knnMatch(Mat queryDescriptors, Mat trainDescriptors, java.util.List<MatOfDMatch> matches, int k, Mat mask, boolean compactResult)` Finds the k best matches for each descriptor from a query set.
`void`	`match(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches)` Finds the best match for each descriptor from a query set.
`void`	`match(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches, Mat mask)` Finds the best match for each descriptor from a query set.
`void`	`match(Mat queryDescriptors, MatOfDMatch matches)` Finds the best match for each descriptor from a query set.
`void`	`match(Mat queryDescriptors, MatOfDMatch matches, java.util.List<Mat> masks)` Finds the best match for each descriptor from a query set.
`void`	`radiusMatch(Mat queryDescriptors, java.util.List<MatOfDMatch> matches, float maxDistance)` For each query descriptor, finds the training descriptors not farther than the specified distance.
`void`	`radiusMatch(Mat queryDescriptors, java.util.List<MatOfDMatch> matches, float maxDistance, java.util.List<Mat> masks, boolean compactResult)` For each query descriptor, finds the training descriptors not farther than the specified distance.
`void`	`radiusMatch(Mat queryDescriptors, Mat trainDescriptors, java.util.List<MatOfDMatch> matches, float maxDistance)` For each query descriptor, finds the training descriptors not farther than the specified distance.
`void`	`radiusMatch(Mat queryDescriptors, Mat trainDescriptors, java.util.List<MatOfDMatch> matches, float maxDistance, Mat mask, boolean compactResult)` For each query descriptor, finds the training descriptors not farther than the specified distance.
`void`	`read(java.lang.String fileName)`
`void`	`train()` Trains a descriptor matcher
`void`	`write(java.lang.String fileName)`

org.opencv.features2d Class DescriptorMatcher

BRUTEFORCE

BRUTEFORCE_HAMMING

BRUTEFORCE_HAMMINGLUT

BRUTEFORCE_L1

BRUTEFORCE_SL2

FLANNBASED

add

clear

clone

clone

create

empty

getTrainDescriptors

isMaskSupported

knnMatch

knnMatch

knnMatch

knnMatch

match

match

match

match

radiusMatch

radiusMatch

radiusMatch

radiusMatch

read

train

write

org.opencv.features2d
Class DescriptorMatcher