OpenCV
3.2.0
Open Source Computer Vision
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Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in [141]. More...
#include "xfeatures2d.hpp"
Public Types | |
enum | { VGG_120 = 100, VGG_80 = 101, VGG_64 = 102, VGG_48 = 103 } |
Public Member Functions | |
virtual void | compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray descriptors)=0 |
Public Member Functions inherited from cv::Feature2D | |
virtual | ~Feature2D () |
virtual void | compute (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors) |
virtual int | defaultNorm () const |
virtual int | descriptorSize () const |
virtual int | descriptorType () const |
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... | |
virtual void | detect (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray()) |
virtual void | detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false) |
virtual bool | empty () const |
Return true if detector object is empty. More... | |
void | read (const String &fileName) |
virtual void | read (const FileNode &) |
Reads algorithm parameters from a file storage. More... | |
void | write (const String &fileName) const |
virtual void | write (FileStorage &) const |
Stores algorithm parameters in a file storage. More... | |
Public Member Functions inherited from cv::Algorithm | |
Algorithm () | |
virtual | ~Algorithm () |
virtual void | clear () |
Clears the algorithm state. More... | |
virtual String | getDefaultName () const |
virtual void | save (const String &filename) const |
Static Public Member Functions | |
static Ptr< VGG > | create (int desc=VGG::VGG_120, float isigma=1.4f, bool img_normalize=true, bool use_scale_orientation=true, float scale_factor=6.25f, bool dsc_normalize=false) |
Static Public Member Functions inherited from cv::Algorithm | |
template<typename _Tp > | |
static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
Loads algorithm from the file. More... | |
template<typename _Tp > | |
static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
Loads algorithm from a String. More... | |
template<typename _Tp > | |
static Ptr< _Tp > | read (const FileNode &fn) |
Reads algorithm from the file node. More... | |
Additional Inherited Members | |
Protected Member Functions inherited from cv::Algorithm | |
void | writeFormat (FileStorage &fs) const |
Class implementing VGG (Oxford Visual Geometry Group) descriptor trained end to end using "Descriptor Learning Using Convex Optimisation" (DLCO) aparatus described in [141].
desc | type of descriptor to use, VGG::VGG_120 is default (120 dimensions float) Available types are VGG::VGG_120, VGG::VGG_80, VGG::VGG_64, VGG::VGG_48 |
isigma | gaussian kernel value for image blur (default is 1.4f) |
img_normalize | use image sample intensity normalization (enabled by default) |
use_orientation | sample patterns using keypoints orientation, enabled by default |
scale_factor | adjust the sampling window of detected keypoints to 64.0f (VGG sampling window) 6.25f is default and fits for KAZE, SURF detected keypoints window ratio 6.75f should be the scale for SIFT detected keypoints window ratio 5.00f should be the scale for AKAZE, MSD, AGAST, FAST, BRISK keypoints window ratio 0.75f should be the scale for ORB keypoints ratio |
dsc_normalize | clamp descriptors to 255 and convert to uchar CV_8UC1 (disabled by default) |
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pure virtual |
image | image to extract descriptors |
keypoints | of interest within image |
descriptors | resulted descriptors array |
Reimplemented from cv::Feature2D.
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static |