Abstract base class for 2D image feature detectors and descriptor extractors.
More...
#include <opencv2/features2d.hpp>
|
virtual | ~Feature2D () |
|
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...
|
|
virtual void | compute (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors) |
|
virtual int | defaultNorm () const |
|
virtual int | descriptorSize () const |
|
virtual int | descriptorType () const |
|
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...
|
|
virtual void | detect (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray()) |
|
virtual void | detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false) |
|
virtual bool | empty () const CV_OVERRIDE |
| Return true if detector object is empty. More...
|
|
virtual String | getDefaultName () const CV_OVERRIDE |
|
void | read (const String &fileName) |
|
virtual void | read (const FileNode &) CV_OVERRIDE |
| Reads algorithm parameters from a file storage. More...
|
|
void | write (const String &fileName) const |
|
virtual void | write (FileStorage &) const CV_OVERRIDE |
| Stores algorithm parameters in a file storage. More...
|
|
void | write (FileStorage &fs, const String &name) const |
|
void | write (const Ptr< FileStorage > &fs, const String &name) const |
|
| Algorithm () |
|
virtual | ~Algorithm () |
|
virtual void | clear () |
| Clears the algorithm state. More...
|
|
virtual void | save (const String &filename) const |
|
void | write (FileStorage &fs, const String &name) const |
|
void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
|
Abstract base class for 2D image feature detectors and descriptor extractors.
◆ ~Feature2D()
virtual cv::Feature2D::~Feature2D |
( |
| ) |
|
|
virtual |
◆ compute() [1/2]
Python: |
---|
| cv.Feature2D.compute( | image, keypoints[, descriptors] | ) -> | keypoints, descriptors |
| cv.Feature2D.compute( | images, keypoints[, descriptors] | ) -> | keypoints, descriptors |
Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant).
- Parameters
-
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. |
Reimplemented in cv::xfeatures2d::DAISY.
◆ compute() [2/2]
Python: |
---|
| cv.Feature2D.compute( | image, keypoints[, descriptors] | ) -> | keypoints, descriptors |
| cv.Feature2D.compute( | images, keypoints[, descriptors] | ) -> | keypoints, descriptors |
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
-
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. |
Reimplemented in cv::xfeatures2d::DAISY.
◆ defaultNorm()
virtual int cv::Feature2D::defaultNorm |
( |
| ) |
const |
|
virtual |
Python: |
---|
| cv.Feature2D.defaultNorm( | | ) -> | retval |
◆ descriptorSize()
virtual int cv::Feature2D::descriptorSize |
( |
| ) |
const |
|
virtual |
Python: |
---|
| cv.Feature2D.descriptorSize( | | ) -> | retval |
◆ descriptorType()
virtual int cv::Feature2D::descriptorType |
( |
| ) |
const |
|
virtual |
Python: |
---|
| cv.Feature2D.descriptorType( | | ) -> | retval |
◆ detect() [1/2]
Python: |
---|
| cv.Feature2D.detect( | image[, mask] | ) -> | keypoints |
| cv.Feature2D.detect( | images[, masks] | ) -> | keypoints |
Detects keypoints in an image (first variant) or image set (second variant).
- Parameters
-
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. |
◆ detect() [2/2]
Python: |
---|
| cv.Feature2D.detect( | image[, mask] | ) -> | keypoints |
| cv.Feature2D.detect( | images[, masks] | ) -> | keypoints |
This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
- Parameters
-
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]. |
◆ detectAndCompute()
Python: |
---|
| cv.Feature2D.detectAndCompute( | image, mask[, descriptors[, useProvidedKeypoints]] | ) -> | keypoints, descriptors |
Detects keypoints and computes the descriptors
◆ empty()
virtual bool cv::Feature2D::empty |
( |
| ) |
const |
|
virtual |
Python: |
---|
| cv.Feature2D.empty( | | ) -> | retval |
Return true if detector object is empty.
Reimplemented from cv::Algorithm.
◆ getDefaultName()
virtual String cv::Feature2D::getDefaultName |
( |
| ) |
const |
|
virtual |
Python: |
---|
| cv.Feature2D.getDefaultName( | | ) -> | retval |
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.
Reimplemented from cv::Algorithm.
Reimplemented in cv::AKAZE, cv::KAZE, cv::SimpleBlobDetector, cv::GFTTDetector, cv::AgastFeatureDetector, cv::FastFeatureDetector, cv::MSER, cv::ORB, cv::BRISK, cv::SIFT, and cv::AffineFeature.
◆ read() [1/2]
void cv::Feature2D::read |
( |
const String & |
fileName | ) |
|
Python: |
---|
| cv.Feature2D.read( | fileName | ) -> | None |
| cv.Feature2D.read( | arg1 | ) -> | None |
◆ read() [2/2]
virtual void cv::Feature2D::read |
( |
const FileNode & |
fn | ) |
|
|
virtual |
Python: |
---|
| cv.Feature2D.read( | fileName | ) -> | None |
| cv.Feature2D.read( | arg1 | ) -> | None |
Reads algorithm parameters from a file storage.
Reimplemented from cv::Algorithm.
◆ write() [1/4]
void cv::Feature2D::write |
( |
const String & |
fileName | ) |
const |
Python: |
---|
| cv.Feature2D.write( | fileName | ) -> | None |
| cv.Feature2D.write( | fs, name | ) -> | None |
◆ write() [2/4]
virtual void cv::Feature2D::write |
( |
FileStorage & |
fs | ) |
const |
|
virtual |
Python: |
---|
| cv.Feature2D.write( | fileName | ) -> | None |
| cv.Feature2D.write( | fs, name | ) -> | None |
Stores algorithm parameters in a file storage.
Reimplemented from cv::Algorithm.
◆ write() [3/4]
Python: |
---|
| cv.Feature2D.write( | fileName | ) -> | None |
| cv.Feature2D.write( | fs, name | ) -> | None |
◆ write() [4/4]
Python: |
---|
| cv.Feature2D.write( | fileName | ) -> | None |
| cv.Feature2D.write( | fs, name | ) -> | None |
The documentation for this class was generated from the following file: