* Group of methods to match descriptors from an image pair.
*/
void match( InputArray queryDescriptors, InputArray trainDescriptors,
- vector<DMatch>& matches, InputArray mask=Mat() ) const;
+ 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;
* Group of methods to match descriptors from one image to an image set.
*/
void match( InputArray queryDescriptors, vector<DMatch>& matches,
- const vector<Mat>& masks=vector<Mat>() );
+ const vector<Mat>& masks=noArray() );
void knnMatch( InputArray queryDescriptors, vector<vector<DMatch> >& matches,
int k, const vector<Mat>& masks=vector<Mat>(),
bool compactResult=false );
----------------------------
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=Mat() ) const
+.. 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>() )
-------------------------------
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=Mat(), bool compactResult=false ) const
+.. 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 )
----------------------------------
For each query descriptor, finds the training descriptors not farther than the specified distance.
-.. ocv:function:: void DescriptorMatcher::radiusMatch( InputArray queryDescriptors, InputArray trainDescriptors, vector<vector<DMatch> >& matches, float maxDistance, InputArray mask=Mat(), bool compactResult=false ) const
+.. 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 )
public:
virtual ~FeatureDetector();
- void detect( const Mat& image, vector<KeyPoint>& keypoints,
- const Mat& mask=Mat() ) const;
+ void detect( InputArray image, vector<KeyPoint>& keypoints,
+ InputArray mask=noArray() ) const;
- void detect( const vector<Mat>& images,
+ void detect( InputArrayOfArrays images,
vector<vector<KeyPoint> >& keypoints,
- const vector<Mat>& masks=vector<Mat>() ) const;
+ InputArrayOfArrays masks=noArray() ) const;
virtual void read(const FileNode&);
virtual void write(FileStorage&) const;
---------------------------
Detects keypoints in an image (first variant) or image set (second variant).
-.. ocv:function:: void FeatureDetector::detect( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask=Mat() ) const
+.. ocv:function:: void FeatureDetector::detect( InputArray image, vector<KeyPoint>& keypoints, InputArray mask=noArray() ) const
-.. ocv:function:: void FeatureDetector::detect( const vector<Mat>& images, vector<vector<KeyPoint> >& keypoints, const vector<Mat>& masks=vector<Mat>() ) const
+.. ocv:function:: void FeatureDetector::detect( InputArrayOfArrays images, vector<vector<KeyPoint> >& keypoints, InputArrayOfArrays masks=noArray() ) const
.. ocv:pyfunction:: cv2.FeatureDetector_create.detect(image[, mask]) -> keypoints