OpenCV453
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#include <xfeatures2d.hpp>
cv::Feature2Dを継承しています。
静的公開メンバ関数 | |
static CV_WRAP Ptr< LATCH > | create (int bytes=32, bool rotationInvariance=true, int half_ssd_size=3, double sigma=2.0) |
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template<typename _Tp > | |
static Ptr< _Tp > | read (const FileNode &fn) |
Reads algorithm from the file node [詳解] | |
template<typename _Tp > | |
static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
Loads algorithm from the file [詳解] | |
template<typename _Tp > | |
static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
Loads algorithm from a String [詳解] | |
その他の継承メンバ | |
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virtual CV_WRAP void | detect (InputArray image, CV_OUT std::vector< KeyPoint > &keypoints, InputArray mask=noArray()) |
Detects keypoints in an image (first variant) or image set (second variant). [詳解] | |
virtual CV_WRAP void | detect (InputArrayOfArrays images, CV_OUT std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray()) |
virtual CV_WRAP void | compute (InputArray image, CV_OUT CV_IN_OUT 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). [詳解] | |
virtual CV_WRAP void | compute (InputArrayOfArrays images, CV_OUT CV_IN_OUT std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors) |
virtual CV_WRAP void | detectAndCompute (InputArray image, InputArray mask, CV_OUT std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false) |
virtual CV_WRAP int | descriptorSize () const |
virtual CV_WRAP int | descriptorType () const |
virtual CV_WRAP int | defaultNorm () const |
CV_WRAP void | write (const String &fileName) const |
CV_WRAP void | read (const String &fileName) |
virtual void | write (FileStorage &) const CV_OVERRIDE |
Stores algorithm parameters in a file storage [詳解] | |
virtual CV_WRAP void | read (const FileNode &) CV_OVERRIDE |
Reads algorithm parameters from a file storage [詳解] | |
virtual CV_WRAP bool | empty () const CV_OVERRIDE |
Return true if detector object is empty [詳解] | |
virtual CV_WRAP String | getDefaultName () const CV_OVERRIDE |
CV_WRAP void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
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virtual CV_WRAP void | clear () |
Clears the algorithm state [詳解] | |
CV_WRAP void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
simplified API for language bindings これはオーバーロードされたメンバ関数です。利便性のために用意されています。元の関数との違いは引き数のみです。 | |
virtual CV_WRAP void | save (const String &filename) const |
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void | writeFormat (FileStorage &fs) const |
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