Class cv::xfeatures2d::LATCH#
#include <opencv2/xfeatures2d.hpp>Collaboration diagram for cv::xfeatures2d::LATCH:
Public Member Functions#
Public Member Functions inherited from cv::Feature2D
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Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant). |
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Detects keypoints in an image (first variant) or image set (second variant). |
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Return true if detector object is empty. |
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Reads algorithm parameters from a file storage. |
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Stores algorithm parameters in a file storage. |
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Public Member Functions inherited from cv::Algorithm
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Clears the algorithm state. |
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Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. |
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Reads algorithm parameters from a file storage. |
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Stores algorithm parameters in a file storage. |
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Static Public Member Functions#
Static Public Member Functions inherited from cv::Algorithm
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Loads algorithm from the file. |
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Loads algorithm from a String. |
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Reads algorithm from the file node. |
Additional Inherited Members#
Protected Member Functions inherited from cv::Algorithm
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Detailed Description#
latch Class for computing the LATCH descriptor. If you find this code useful, please add a reference to the following paper in your work: Gil Levi and Tal Hassner, “LATCH: Learned Arrangements of Three Patch Codes”, arXiv preprint arXiv:1501.03719, 15 Jan. 2015
LATCH is a binary descriptor based on learned comparisons of triplets of image patches.
bytes is the size of the descriptor - can be 64, 32, 16, 8, 4, 2 or 1 rotationInvariance - whether or not the descriptor should compansate for orientation changes. half_ssd_size - the size of half of the mini-patches size. For example, if we would like to compare triplets of patches of size 7x7x then the half_ssd_size should be (7-1)/2 = 3. sigma - sigma value for GaussianBlur smoothing of the source image. Source image will be used without smoothing in case sigma value is 0.
Note: the descriptor can be coupled with any keypoint extractor. The only demand is that if you use set rotationInvariance = True then you will have to use an extractor which estimates the patch orientation (in degrees). Examples for such extractors are ORB and SIFT.
Note: a complete example can be found under /samples/cpp/tutorial_code/xfeatures2D/latch_match.cpp
Member Function Documentation#
create()#
static Ptr< LATCH > cv::xfeatures2d::LATCH::create(
int bytes = 32,
bool rotationInvariance = true,
int half_ssd_size = 3,
double sigma = 2.0 )
getBytes()#
int cv::xfeatures2d::LATCH::getBytes()
getDefaultName()#
String cv::xfeatures2d::LATCH::getDefaultName()
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.
getHalfSSDsize()#
int cv::xfeatures2d::LATCH::getHalfSSDsize()
getRotationInvariance()#
bool cv::xfeatures2d::LATCH::getRotationInvariance()
getSigma()#
double cv::xfeatures2d::LATCH::getSigma()
setBytes()#
void cv::xfeatures2d::LATCH::setBytes(int bytes)
setHalfSSDsize()#
void cv::xfeatures2d::LATCH::setHalfSSDsize(int half_ssd_size)
setRotationInvariance()#
void cv::xfeatures2d::LATCH::setRotationInvariance(bool rotationInvariance)
setSigma()#
void cv::xfeatures2d::LATCH::setSigma(double sigma)
Source file#
The documentation for this class was generated from the following file:
opencv2/xfeatures2d.hpp