org.opencv.features2d
public class DescriptorMatcher 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;...
};
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Field Summary
Fields
Modifier and Type
Field and Description
static int
BRUTEFORCE
static int
BRUTEFORCE_HAMMING
static int
BRUTEFORCE_HAMMINGLUT
static int
BRUTEFORCE_L1
static int
BRUTEFORCE_SL2
static int
FLANNBASED
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Method Summary
Methods
Modifier and Type
Method and Description
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)
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Field Detail
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BRUTEFORCE
public static final int BRUTEFORCE
- See Also:
- Constant Field Values
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BRUTEFORCE_HAMMING
public static final int BRUTEFORCE_HAMMING
- See Also:
- Constant Field Values
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BRUTEFORCE_HAMMINGLUT
public static final int BRUTEFORCE_HAMMINGLUT
- See Also:
- Constant Field Values
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BRUTEFORCE_L1
public static final int BRUTEFORCE_L1
- See Also:
- Constant Field Values
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BRUTEFORCE_SL2
public static final int BRUTEFORCE_SL2
- See Also:
- Constant Field Values
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FLANNBASED
public static final int FLANNBASED
- See Also:
- Constant Field Values
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Method Detail
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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
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clear
public void clear()
Clears the train descriptor collection.
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clone
public DescriptorMatcher clone()
- Overrides:
clone
in class java.lang.Object
-
clone
public DescriptorMatcher clone(boolean emptyTrainData)
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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
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empty
public boolean empty()
Returns true if there are no train descriptors in the collection.
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getTrainDescriptors
public java.util.List<Mat> getTrainDescriptors()
Returns a constant link to the train descriptor collection trainDescCollection
.
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isMaskSupported
public boolean isMaskSupported()
Returns true if the descriptor matcher supports masking permissible matches.
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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
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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
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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
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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
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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
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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
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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
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read
public void read(java.lang.String fileName)
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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
).
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write
public void write(java.lang.String fileName)