Class cv::xfeatures2d::BOWImgDescriptorExtractor#

Class to compute an image descriptor using the bag of visual words. View details

#include <opencv2/xfeatures2d.hpp>

Collaboration diagram for cv::xfeatures2d::BOWImgDescriptorExtractor:

cv::xfeatures2d::BOWImgDescriptorExtractor Node1 cv::xfeatures2d::BOWImgDescriptor Extractor   + BOWImgDescriptorExtractor() + BOWImgDescriptorExtractor() + ~BOWImgDescriptorExtractor() + compute() + compute() + compute2() + descriptorSize() + descriptorType() + getVocabulary() + setVocabulary() Node2 cv::Mat   + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() and 152 more... + diag() + eye() + eye() + getDefaultAllocator() + getStdAllocator() + ones() + ones() + ones() + ones() + setDefaultAllocator() + zeros() + zeros() + zeros() + zeros() # forEach_impl() Node2->Node1 #vocabulary Node3 int     Node3->Node2 +cols +dims +dummy +flags +rows Node4 uint8_t     Node4->Node2 +data +dataend +datalimit +datastart Node5 cv::MatAllocator   + MatAllocator() + ~MatAllocator() + allocate() + allocate() + copy() + deallocate() + download() + getBufferPoolController() + map() + unmap() + upload() Node5->Node2 +allocator Node6 UMatData *     Node6->Node2 +u Node7 MatSize     Node7->Node2 +size Node8 MatStep     Node8->Node2 +step Node9 Ptr< cv::Feature2D >     Node9->Node1 #dextractor Node10 Ptr< cv::DescriptorMatcher >     Node10->Node1 #dmatcher

cv::xfeatures2d::BOWImgDescriptorExtractor Node1 cv::xfeatures2d::BOWImgDescriptor Extractor   + BOWImgDescriptorExtractor() + BOWImgDescriptorExtractor() + ~BOWImgDescriptorExtractor() + compute() + compute() + compute2() + descriptorSize() + descriptorType() + getVocabulary() + setVocabulary() Node2 cv::Mat   + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() + Mat() and 152 more... + diag() + eye() + eye() + getDefaultAllocator() + getStdAllocator() + ones() + ones() + ones() + ones() + setDefaultAllocator() + zeros() + zeros() + zeros() + zeros() # forEach_impl() Node2->Node1 #vocabulary Node3 int     Node3->Node2 +cols +dims +dummy +flags +rows Node4 uint8_t     Node4->Node2 +data +dataend +datalimit +datastart Node5 cv::MatAllocator   + MatAllocator() + ~MatAllocator() + allocate() + allocate() + copy() + deallocate() + download() + getBufferPoolController() + map() + unmap() + upload() Node5->Node2 +allocator Node6 UMatData *     Node6->Node2 +u Node7 MatSize     Node7->Node2 +size Node8 MatStep     Node8->Node2 +step Node9 Ptr< cv::Feature2D >     Node9->Node1 #dextractor Node10 Ptr< cv::DescriptorMatcher >     Node10->Node1 #dmatcher

Detailed Description#

Class to compute an image descriptor using the bag of visual words.

Such a computation consists of the following steps:

  1. Compute descriptors for a given image and its keypoints set.

  2. Find the nearest visual words from the vocabulary for each keypoint descriptor.

  3. Compute the bag-of-words image descriptor as is a normalized histogram of vocabulary words encountered in the image. The i-th bin of the histogram is a frequency of i-th word of the vocabulary in the given image.

Constructor & Destructor Documentation#

BOWImgDescriptorExtractor()#

cv::xfeatures2d::BOWImgDescriptorExtractor::BOWImgDescriptorExtractor(const Ptr< DescriptorMatcher > & dmatcher)

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

BOWImgDescriptorExtractor()#

cv::xfeatures2d::BOWImgDescriptorExtractor::BOWImgDescriptorExtractor(
const Ptr< Feature2D > & dextractor,
const Ptr< DescriptorMatcher > & dmatcher )

The constructor.

Parameters

  • dextractor — Descriptor extractor that is used to compute descriptors for an input image and its keypoints.

  • dmatcher — Descriptor matcher that is used to find the nearest word of the trained vocabulary for each keypoint descriptor of the image.

~BOWImgDescriptorExtractor()#

cv::xfeatures2d::BOWImgDescriptorExtractor::~BOWImgDescriptorExtractor()

Member Function Documentation#

compute()#

void cv::xfeatures2d::BOWImgDescriptorExtractor::compute(
InputArray image,
std::vector< KeyPoint > & keypoints,
OutputArray imgDescriptor,
std::vector< std::vector< int > > * pointIdxsOfClusters = 0,
Mat * descriptors = 0 )

Computes an image descriptor using the set visual vocabulary.

Parameters

  • image — Image, for which the descriptor is computed.

  • keypoints — Keypoints detected in the input image.

  • imgDescriptor — Computed output image descriptor.

  • pointIdxsOfClusters — Indices of keypoints that belong to the cluster. This means that pointIdxsOfClusters[i] are keypoint indices that belong to the i -th cluster (word of vocabulary) returned if it is non-zero.

  • descriptors — Descriptors of the image keypoints that are returned if they are non-zero.

compute()#

void cv::xfeatures2d::BOWImgDescriptorExtractor::compute(
InputArray keypointDescriptors,
OutputArray imgDescriptor,
std::vector< std::vector< int > > * pointIdxsOfClusters = 0 )

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Parameters

  • keypointDescriptors — Computed descriptors to match with vocabulary.

  • imgDescriptor — Computed output image descriptor.

  • pointIdxsOfClusters — Indices of keypoints that belong to the cluster. This means that pointIdxsOfClusters[i] are keypoint indices that belong to the i -th cluster (word of vocabulary) returned if it is non-zero.

compute2()#

void cv::xfeatures2d::BOWImgDescriptorExtractor::compute2(
const Mat & image,
std::vector< KeyPoint > & keypoints,
Mat & imgDescriptor )

descriptorSize()#

int cv::xfeatures2d::BOWImgDescriptorExtractor::descriptorSize()

Returns an image descriptor size if the vocabulary is set. Otherwise, it returns 0.

descriptorType()#

int cv::xfeatures2d::BOWImgDescriptorExtractor::descriptorType()

Returns an image descriptor type.

getVocabulary()#

const Mat & cv::xfeatures2d::BOWImgDescriptorExtractor::getVocabulary()

Returns the set vocabulary.

setVocabulary()#

void cv::xfeatures2d::BOWImgDescriptorExtractor::setVocabulary(const Mat & vocabulary)

Sets a visual vocabulary.

Parameters

  • vocabulary — Vocabulary (can be trained using the inheritor of BOWTrainer ). Each row of the vocabulary is a visual word (cluster center).

Member Data Documentation#

dextractor#

Ptr< DescriptorExtractor > cv::xfeatures2d::BOWImgDescriptorExtractor::dextractor

dmatcher#

Ptr< DescriptorMatcher > cv::xfeatures2d::BOWImgDescriptorExtractor::dmatcher

vocabulary#

Mat cv::xfeatures2d::BOWImgDescriptorExtractor::vocabulary

Source file#

The documentation for this class was generated from the following file: