Class implementing the Harris-Laplace feature detector as described in [179].
More...
#include <opencv2/xfeatures2d.hpp>
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virtual float | getCornThresh () const =0 |
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String | getDefaultName () const CV_OVERRIDE |
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virtual float | getDOGThresh () const =0 |
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virtual int | getMaxCorners () const =0 |
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virtual int | getNumLayers () const =0 |
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virtual int | getNumOctaves () const =0 |
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virtual void | setCornThresh (float corn_thresh_)=0 |
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virtual void | setDOGThresh (float DOG_thresh_)=0 |
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virtual void | setMaxCorners (int maxCorners_)=0 |
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virtual void | setNumLayers (int num_layers_)=0 |
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virtual void | setNumOctaves (int numOctaves_)=0 |
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virtual | ~Feature2D () |
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virtual void | compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray descriptors) |
| Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant). More...
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virtual void | compute (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors) |
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virtual int | defaultNorm () const |
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virtual int | descriptorSize () const |
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virtual int | descriptorType () const |
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virtual void | detect (InputArray image, std::vector< KeyPoint > &keypoints, InputArray mask=noArray()) |
| Detects keypoints in an image (first variant) or image set (second variant). More...
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virtual void | detect (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray()) |
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virtual void | detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false) |
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virtual bool | empty () const CV_OVERRIDE |
| Return true if detector object is empty. More...
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void | read (const String &fileName) |
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virtual void | read (const FileNode &) CV_OVERRIDE |
| Reads algorithm parameters from a file storage. More...
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void | write (const String &fileName) const |
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virtual void | write (FileStorage &) const CV_OVERRIDE |
| Stores algorithm parameters in a file storage. More...
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void | write (FileStorage &fs, const String &name) const |
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void | write (const Ptr< FileStorage > &fs, const String &name) const |
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| Algorithm () |
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virtual | ~Algorithm () |
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virtual void | clear () |
| Clears the algorithm state. More...
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virtual void | save (const String &filename) const |
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void | write (FileStorage &fs, const String &name) const |
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void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
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Class implementing the Harris-Laplace feature detector as described in [179].
◆ create()
static Ptr<HarrisLaplaceFeatureDetector> cv::xfeatures2d::HarrisLaplaceFeatureDetector::create |
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int |
numOctaves = 6 , |
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float |
corn_thresh = 0.01f , |
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float |
DOG_thresh = 0.01f , |
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int |
maxCorners = 5000 , |
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int |
num_layers = 4 |
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) |
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static |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.create( | [, numOctaves[, corn_thresh[, DOG_thresh[, maxCorners[, num_layers]]]]] | ) -> | retval |
| cv.xfeatures2d.HarrisLaplaceFeatureDetector_create( | [, numOctaves[, corn_thresh[, DOG_thresh[, maxCorners[, num_layers]]]]] | ) -> | retval |
Creates a new implementation instance.
- Parameters
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numOctaves | the number of octaves in the scale-space pyramid |
corn_thresh | the threshold for the Harris cornerness measure |
DOG_thresh | the threshold for the Difference-of-Gaussians scale selection |
maxCorners | the maximum number of corners to consider |
num_layers | the number of intermediate scales per octave |
◆ getCornThresh()
virtual float cv::xfeatures2d::HarrisLaplaceFeatureDetector::getCornThresh |
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const |
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pure virtual |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.getCornThresh( | | ) -> | retval |
◆ getDefaultName()
String cv::xfeatures2d::HarrisLaplaceFeatureDetector::getDefaultName |
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const |
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virtual |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.getDefaultName( | | ) -> | retval |
Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.
Reimplemented from cv::Feature2D.
◆ getDOGThresh()
virtual float cv::xfeatures2d::HarrisLaplaceFeatureDetector::getDOGThresh |
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const |
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pure virtual |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.getDOGThresh( | | ) -> | retval |
◆ getMaxCorners()
virtual int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getMaxCorners |
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const |
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pure virtual |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.getMaxCorners( | | ) -> | retval |
◆ getNumLayers()
virtual int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getNumLayers |
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const |
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pure virtual |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.getNumLayers( | | ) -> | retval |
◆ getNumOctaves()
virtual int cv::xfeatures2d::HarrisLaplaceFeatureDetector::getNumOctaves |
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const |
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pure virtual |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.getNumOctaves( | | ) -> | retval |
◆ setCornThresh()
virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setCornThresh |
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float |
corn_thresh_ | ) |
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pure virtual |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.setCornThresh( | corn_thresh_ | ) -> | None |
◆ setDOGThresh()
virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setDOGThresh |
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float |
DOG_thresh_ | ) |
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pure virtual |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.setDOGThresh( | DOG_thresh_ | ) -> | None |
◆ setMaxCorners()
virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setMaxCorners |
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int |
maxCorners_ | ) |
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pure virtual |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.setMaxCorners( | maxCorners_ | ) -> | None |
◆ setNumLayers()
virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setNumLayers |
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int |
num_layers_ | ) |
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pure virtual |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.setNumLayers( | num_layers_ | ) -> | None |
◆ setNumOctaves()
virtual void cv::xfeatures2d::HarrisLaplaceFeatureDetector::setNumOctaves |
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int |
numOctaves_ | ) |
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pure virtual |
Python: |
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| cv.xfeatures2d.HarrisLaplaceFeatureDetector.setNumOctaves( | numOctaves_ | ) -> | None |
The documentation for this class was generated from the following file: