Package org.opencv.features2d
Class DescriptorMatcher
- java.lang.Object
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- org.opencv.core.Algorithm
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- org.opencv.features2d.DescriptorMatcher
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- Direct Known Subclasses:
BFMatcher,FlannBasedMatcher
public class DescriptorMatcher extends Algorithm
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.
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Field Summary
Fields Modifier and Type Field Description static intBRUTEFORCEstatic intBRUTEFORCE_HAMMINGstatic intBRUTEFORCE_HAMMINGLUTstatic intBRUTEFORCE_L1static intBRUTEFORCE_SL2static intFLANNBASED
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Constructor Summary
Constructors Modifier Constructor Description protectedDescriptorMatcher(long addr)
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static DescriptorMatcher__fromPtr__(long addr)voidadd(List<Mat> descriptors)Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) descriptor collection.voidclear()Clears the train descriptor collections.DescriptorMatcherclone()Clones the matcher.DescriptorMatcherclone(boolean emptyTrainData)Clones the matcher.static DescriptorMatchercreate(int matcherType)static DescriptorMatchercreate(String descriptorMatcherType)Creates a descriptor matcher of a given type with the default parameters (using default constructor).booleanempty()Returns true if there are no train descriptors in the both collections.protected voidfinalize()List<Mat>getTrainDescriptors()Returns a constant link to the train descriptor collection trainDescCollection .booleanisMaskSupported()Returns true if the descriptor matcher supports masking permissible matches.voidknnMatch(Mat queryDescriptors, List<MatOfDMatch> matches, int k)voidknnMatch(Mat queryDescriptors, List<MatOfDMatch> matches, int k, List<Mat> masks)voidknnMatch(Mat queryDescriptors, List<MatOfDMatch> matches, int k, List<Mat> masks, boolean compactResult)voidknnMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, int k)Finds the k best matches for each descriptor from a query set.voidknnMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, int k, Mat mask)Finds the k best matches for each descriptor from a query set.voidknnMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, int k, Mat mask, boolean compactResult)Finds the k best matches for each descriptor from a query set.voidmatch(Mat queryDescriptors, MatOfDMatch matches)voidmatch(Mat queryDescriptors, MatOfDMatch matches, List<Mat> masks)voidmatch(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches)Finds the best match for each descriptor from a query set.voidmatch(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches, Mat mask)Finds the best match for each descriptor from a query set.voidradiusMatch(Mat queryDescriptors, List<MatOfDMatch> matches, float maxDistance)voidradiusMatch(Mat queryDescriptors, List<MatOfDMatch> matches, float maxDistance, List<Mat> masks)voidradiusMatch(Mat queryDescriptors, List<MatOfDMatch> matches, float maxDistance, List<Mat> masks, boolean compactResult)voidradiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, float maxDistance)For each query descriptor, finds the training descriptors not farther than the specified distance.voidradiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, float maxDistance, Mat mask)For each query descriptor, finds the training descriptors not farther than the specified distance.voidradiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, float maxDistance, Mat mask, boolean compactResult)For each query descriptor, finds the training descriptors not farther than the specified distance.voidread(String fileName)voidtrain()Trains a descriptor matcher Trains a descriptor matcher (for example, the flann index).voidwrite(String fileName)-
Methods inherited from class org.opencv.core.Algorithm
getDefaultName, getNativeObjAddr, save
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Field Detail
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FLANNBASED
public static final int FLANNBASED
- See Also:
- Constant Field Values
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BRUTEFORCE
public static final int BRUTEFORCE
- 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_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_SL2
public static final int BRUTEFORCE_SL2
- See Also:
- Constant Field Values
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Method Detail
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__fromPtr__
public static DescriptorMatcher __fromPtr__(long addr)
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clone
public DescriptorMatcher clone(boolean emptyTrainData)
Clones the matcher.- Parameters:
emptyTrainData- If emptyTrainData is false, the method creates a deep copy of the object, that is, copies both parameters and train data. If emptyTrainData is true, the method creates an object copy with the current parameters but with empty train data.- Returns:
- automatically generated
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clone
public DescriptorMatcher clone()
Clones the matcher. that is, copies both parameters and train data. If emptyTrainData is true, the method creates an object copy with the current parameters but with empty train data.
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create
public static DescriptorMatcher create(String descriptorMatcherType)
Creates a descriptor matcher of a given type with the default parameters (using default constructor).- Parameters:
descriptorMatcherType- Descriptor matcher type. Now the following matcher types are supported:-
BruteForce(it uses L2 ) -
BruteForce-L1 -
BruteForce-Hamming -
BruteForce-Hamming(2) -
FlannBased
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- Returns:
- automatically generated
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create
public static DescriptorMatcher create(int matcherType)
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empty
public boolean empty()
Returns true if there are no train descriptors in the both collections.
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isMaskSupported
public boolean isMaskSupported()
Returns true if the descriptor matcher supports masking permissible matches.- Returns:
- automatically generated
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getTrainDescriptors
public List<Mat> getTrainDescriptors()
Returns a constant link to the train descriptor collection trainDescCollection .- Returns:
- automatically generated
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add
public void add(List<Mat> descriptors)
Adds descriptors to train a CPU(trainDescCollectionis) or GPU(utrainDescCollectionis) descriptor collection. If the collection 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.
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clear
public void clear()
Clears the train descriptor collections.
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knnMatch
public void knnMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, int k, Mat mask, boolean compactResult)
Finds the k best matches for each descriptor from a query set.- 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.mask- Mask specifying permissible matches between an input query and train matrices 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.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. 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.
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knnMatch
public void knnMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, int k, Mat mask)
Finds the k best matches for each descriptor from a query set.- 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.mask- Mask specifying permissible matches between an input query and train matrices 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. 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. 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.
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knnMatch
public void knnMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, int k)
Finds the k best matches for each descriptor from a query set.- 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. 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. 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. 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.
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knnMatch
public void knnMatch(Mat queryDescriptors, List<MatOfDMatch> matches, int k, List<Mat> masks, boolean compactResult)
- 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.
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knnMatch
public void knnMatch(Mat queryDescriptors, List<MatOfDMatch> matches, int k, List<Mat> masks)
- 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]. 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.
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knnMatch
public void knnMatch(Mat queryDescriptors, List<MatOfDMatch> matches, int k)
- 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. descriptors and stored train descriptors from the i-th image trainDescCollection[i]. 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.
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match
public void match(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches, Mat mask)
Finds the best match for each descriptor from a query set.- 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. 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<uchar>(i,j) is non-zero.
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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.- 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. descriptors. 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<uchar>(i,j) is non-zero.
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match
public void match(Mat queryDescriptors, MatOfDMatch matches, List<Mat> masks)
- 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].
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match
public void match(Mat queryDescriptors, MatOfDMatch matches)
- 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. descriptors and stored train descriptors from the i-th image trainDescCollection[i].
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radiusMatch
public void radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, float maxDistance, Mat mask, boolean compactResult)
For each query descriptor, finds the training descriptors not farther than the specified distance.- 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.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.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. 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.
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radiusMatch
public void radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, float maxDistance, Mat mask)
For each query descriptor, finds the training descriptors not farther than the specified distance.- 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. 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.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. 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.
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radiusMatch
public void radiusMatch(Mat queryDescriptors, Mat trainDescriptors, List<MatOfDMatch> matches, float maxDistance)
For each query descriptor, finds the training descriptors not farther than the specified distance.- 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. 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.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)! descriptors. 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.
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radiusMatch
public void radiusMatch(Mat queryDescriptors, List<MatOfDMatch> matches, float maxDistance, List<Mat> masks, boolean compactResult)
- 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.
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radiusMatch
public void radiusMatch(Mat queryDescriptors, List<MatOfDMatch> matches, float maxDistance, List<Mat> masks)
- 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]. 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.
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radiusMatch
public void radiusMatch(Mat queryDescriptors, List<MatOfDMatch> matches, float maxDistance)
- 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)! descriptors and stored train descriptors from the i-th image trainDescCollection[i]. 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.
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read
public void read(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(String fileName)
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