Abstract base class for 2D image feature detectors and descriptor extractors.
More...
#include "features2d.hpp"
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virtual | ~Feature2D () |
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virtual void | compute (InputArray image, 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). More...
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virtual void | compute (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors) |
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virtual int | defaultNorm () const |
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virtual int | descriptorSize () const |
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virtual int | descriptorType () const |
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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...
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virtual void | detect (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray()) |
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virtual void | detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false) |
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virtual bool | empty () const |
| Return true if detector object is empty. More...
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| Algorithm () |
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virtual | ~Algorithm () |
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virtual void | clear () |
| Clears the algorithm state. More...
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virtual String | getDefaultName () const |
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virtual void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage. More...
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virtual void | save (const String &filename) const |
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virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage. More...
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Abstract base class for 2D image feature detectors and descriptor extractors.
virtual cv::Feature2D::~Feature2D |
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Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
- Parameters
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image | Image. |
keypoints | Input collection of keypoints. Keypoints for which a descriptor cannot be computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint with several dominant orientations (for each orientation). |
descriptors | Computed descriptors. In the second variant of the method descriptors[i] are descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the descriptor for keypoint j-th keypoint. |
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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images | Image set. |
keypoints | Input collection of keypoints. Keypoints for which a descriptor cannot be computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint with several dominant orientations (for each orientation). |
descriptors | Computed descriptors. In the second variant of the method descriptors[i] are descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the descriptor for keypoint j-th keypoint. |
virtual int cv::Feature2D::defaultNorm |
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const |
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virtual int cv::Feature2D::descriptorSize |
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const |
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virtual int cv::Feature2D::descriptorType |
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const |
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Detects keypoints in an image (first variant) or image set (second variant).
- Parameters
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image | Image. |
keypoints | The detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] . |
mask | Mask specifying where to look for keypoints (optional). It must be a 8-bit integer matrix with non-zero values in the region of interest. |
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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images | Image set. |
keypoints | The detected keypoints. In the second variant of the method keypoints[i] is a set of keypoints detected in images[i] . |
masks | Masks for each input image specifying where to look for keypoints (optional). masks[i] is a mask for images[i]. |
Detects keypoints and computes the descriptors
virtual bool cv::Feature2D::empty |
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const |
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Return true if detector object is empty.
Reimplemented from cv::Algorithm.
The documentation for this class was generated from the following file: