OpenCV
3.2.0
Open Source Computer Vision
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This is a base class for all more or less complex algorithms in OpenCV. More...
#include "core.hpp"
Public Member Functions | |
Algorithm () | |
virtual | ~Algorithm () |
virtual void | clear () |
Clears the algorithm state. More... | |
virtual bool | empty () const |
Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More... | |
virtual String | getDefaultName () const |
virtual void | read (const FileNode &fn) |
Reads algorithm parameters from a file storage. More... | |
virtual void | save (const String &filename) const |
virtual void | write (FileStorage &fs) const |
Stores algorithm parameters in a file storage. More... | |
Static Public Member Functions | |
template<typename _Tp > | |
static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
Loads algorithm from the file. More... | |
template<typename _Tp > | |
static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
Loads algorithm from a String. More... | |
template<typename _Tp > | |
static Ptr< _Tp > | read (const FileNode &fn) |
Reads algorithm from the file node. More... | |
Protected Member Functions | |
void | writeFormat (FileStorage &fs) const |
This is a base class for all more or less complex algorithms in OpenCV.
especially for classes of algorithms, for which there can be multiple implementations. The examples are stereo correspondence (for which there are algorithms like block matching, semi-global block matching, graph-cut etc.), background subtraction (which can be done using mixture-of-gaussians models, codebook-based algorithm etc.), optical flow (block matching, Lucas-Kanade, Horn-Schunck etc.).
Here is example of SIFT use in your application via Algorithm interface:
cv::Algorithm::Algorithm | ( | ) |
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Clears the algorithm state.
Reimplemented in cv::line_descriptor::BinaryDescriptorMatcher, cv::FlannBasedMatcher, cv::DescriptorMatcher, and cv::cuda::DescriptorMatcher.
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Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
Reimplemented in cv::DescriptorMatcher, cv::ml::StatModel, cv::Feature2D, cv::BaseCascadeClassifier, and cv::cuda::DescriptorMatcher.
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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.
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Loads algorithm from the file.
filename | Name of the file to read. |
objname | The optional name of the node to read (if empty, the first top-level node will be used) |
This is static template method of Algorithm. It's usage is following (in the case of SVM):
In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn).
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Loads algorithm from a String.
strModel | The string variable containing the model you want to load. |
objname | The optional name of the node to read (if empty, the first top-level node will be used) |
This is static template method of Algorithm. It's usage is following (in the case of SVM):
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Reads algorithm parameters from a file storage.
Reimplemented in cv::FlannBasedMatcher, cv::DescriptorMatcher, cv::Tracker, cv::optflow::GPCForest< T >, cv::line_descriptor::BinaryDescriptor, cv::Feature2D, cv::optflow::GPCTree, and cv::saliency::StaticSaliencySpectralResidual.
Reads algorithm from the file node.
This is static template method of Algorithm. It's usage is following (in the case of SVM):
In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn) and also have static create() method without parameters (or with all the optional parameters)
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Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).
Reimplemented in cv::face::FaceRecognizer.
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Stores algorithm parameters in a file storage.
Reimplemented in cv::FlannBasedMatcher, cv::DescriptorMatcher, cv::Tracker, cv::optflow::GPCForest< T >, cv::line_descriptor::BinaryDescriptor, cv::bioinspired::Retina, cv::Feature2D, cv::optflow::GPCTree, cv::bioinspired::TransientAreasSegmentationModule, and cv::saliency::StaticSaliencySpectralResidual.
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