Class to compute an image descriptor using the bag of visual words.
More...
#include "features2d.hpp"
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| BOWImgDescriptorExtractor (const Ptr< DescriptorExtractor > &dextractor, const Ptr< DescriptorMatcher > &dmatcher) |
| The constructor. More...
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| BOWImgDescriptorExtractor (const Ptr< DescriptorMatcher > &dmatcher) |
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virtual | ~BOWImgDescriptorExtractor () |
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void | 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. More...
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void | compute (InputArray keypointDescriptors, OutputArray imgDescriptor, std::vector< std::vector< int > > *pointIdxsOfClusters=0) |
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void | compute2 (const Mat &image, std::vector< KeyPoint > &keypoints, Mat &imgDescriptor) |
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int | descriptorSize () const |
| Returns an image descriptor size if the vocabulary is set. Otherwise, it returns 0. More...
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int | descriptorType () const |
| Returns an image descriptor type. More...
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const Mat & | getVocabulary () const |
| Returns the set vocabulary. More...
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void | setVocabulary (const Mat &vocabulary) |
| Sets a visual vocabulary. More...
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Class to compute an image descriptor using the bag of visual words.
Such a computation consists of the following steps:
- Compute descriptors for a given image and its keypoints set.
- Find the nearest visual words from the vocabulary for each keypoint descriptor.
- 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.
§ BOWImgDescriptorExtractor() [1/2]
Python: |
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| <BOWImgDescriptorExtractor object> | = | cv.BOWImgDescriptorExtractor( | dextractor, dmatcher | ) |
The constructor.
- Parameters
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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() [2/2]
cv::BOWImgDescriptorExtractor::BOWImgDescriptorExtractor |
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const Ptr< DescriptorMatcher > & |
dmatcher | ) |
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Python: |
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| <BOWImgDescriptorExtractor object> | = | cv.BOWImgDescriptorExtractor( | dextractor, dmatcher | ) |
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
§ ~BOWImgDescriptorExtractor()
virtual cv::BOWImgDescriptorExtractor::~BOWImgDescriptorExtractor |
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virtual |
§ compute() [1/2]
void cv::BOWImgDescriptorExtractor::compute |
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InputArray |
image, |
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std::vector< KeyPoint > & |
keypoints, |
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OutputArray |
imgDescriptor, |
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std::vector< std::vector< int > > * |
pointIdxsOfClusters = 0 , |
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Mat * |
descriptors = 0 |
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Computes an image descriptor using the set visual vocabulary.
- Parameters
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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() [2/2]
void cv::BOWImgDescriptorExtractor::compute |
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InputArray |
keypointDescriptors, |
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OutputArray |
imgDescriptor, |
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std::vector< std::vector< int > > * |
pointIdxsOfClusters = 0 |
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This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
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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::BOWImgDescriptorExtractor::compute2 |
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const Mat & |
image, |
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std::vector< KeyPoint > & |
keypoints, |
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Mat & |
imgDescriptor |
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inline |
Python: |
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| imgDescriptor | = | cv.BOWImgDescriptorExtractor.compute( | image, keypoints[, imgDescriptor] | ) |
§ descriptorSize()
int cv::BOWImgDescriptorExtractor::descriptorSize |
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const |
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| retval | = | cv.BOWImgDescriptorExtractor.descriptorSize( | | ) |
Returns an image descriptor size if the vocabulary is set. Otherwise, it returns 0.
§ descriptorType()
int cv::BOWImgDescriptorExtractor::descriptorType |
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const |
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| retval | = | cv.BOWImgDescriptorExtractor.descriptorType( | | ) |
Returns an image descriptor type.
§ getVocabulary()
const Mat& cv::BOWImgDescriptorExtractor::getVocabulary |
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const |
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| retval | = | cv.BOWImgDescriptorExtractor.getVocabulary( | | ) |
Returns the set vocabulary.
§ setVocabulary()
void cv::BOWImgDescriptorExtractor::setVocabulary |
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const Mat & |
vocabulary | ) |
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| None | = | cv.BOWImgDescriptorExtractor.setVocabulary( | vocabulary | ) |
Sets a visual vocabulary.
- Parameters
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vocabulary | Vocabulary (can be trained using the inheritor of BOWTrainer ). Each row of the vocabulary is a visual word (cluster center). |
§ dextractor
§ dmatcher
§ vocabulary
Mat cv::BOWImgDescriptorExtractor::vocabulary |
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protected |
The documentation for this class was generated from the following file: