OpenCV  4.9.0-dev
Open Source Computer Vision
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Public Member Functions | Static Public Member Functions | Protected Member Functions | List of all members
cv::Algorithm Class Reference

This is a base class for all more or less complex algorithms in OpenCV. More...

#include <opencv2/core.hpp>

Inheritance diagram for cv::Algorithm:
Collaboration diagram for cv::Algorithm:

Public Member Functions

 Algorithm ()
 
virtual ~Algorithm ()
 
virtual void clear ()
 Clears the algorithm state.
 
virtual bool empty () const
 Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.
 
virtual String getDefaultName () const
 
virtual void read (const FileNode &fn)
 Reads algorithm parameters from a file storage.
 
virtual void save (const String &filename) const
 
void write (const Ptr< FileStorage > &fs, const String &name=String()) const
 
virtual void write (FileStorage &fs) const
 Stores algorithm parameters in a file storage.
 
void write (FileStorage &fs, const String &name) const
 

Static Public Member Functions

template<typename _Tp >
static Ptr< _Tpload (const String &filename, const String &objname=String())
 Loads algorithm from the file.
 
template<typename _Tp >
static Ptr< _TploadFromString (const String &strModel, const String &objname=String())
 Loads algorithm from a String.
 
template<typename _Tp >
static Ptr< _Tpread (const FileNode &fn)
 Reads algorithm from the file node.
 

Protected Member Functions

void writeFormat (FileStorage &fs) const
 

Detailed Description

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 SimpleBlobDetector use in your application via Algorithm interface:

FileStorage fs_read("SimpleBlobDetector_params.xml", FileStorage::READ);
if (fs_read.isOpened()) // if we have file with parameters, read them
{
sbd->read(fs_read.root());
fs_read.release();
}
else // else modify the parameters and store them; user can later edit the file to use different parameters
{
fs_read.release();
FileStorage fs_write("SimpleBlobDetector_params.xml", FileStorage::WRITE);
sbd->write(fs_write);
fs_write.release();
}
Mat result, image = imread("../data/detect_blob.png", IMREAD_COLOR);
vector<KeyPoint> keypoints;
sbd->detect(image, keypoints, Mat());
drawKeypoints(image, keypoints, result);
for (vector<KeyPoint>::iterator k = keypoints.begin(); k != keypoints.end(); ++k)
circle(result, k->pt, (int)k->size, Scalar(0, 0, 255), 2);
imshow("result", result);
waitKey(0);
XML/YAML/JSON file storage class that encapsulates all the information necessary for writing or readi...
Definition persistence.hpp:304
@ WRITE
value, open the file for writing
Definition persistence.hpp:310
@ READ
value, open the file for reading
Definition persistence.hpp:309
static Ptr< SimpleBlobDetector > create(const SimpleBlobDetector::Params &parameters=SimpleBlobDetector::Params())
Scalar_< double > Scalar
Definition types.hpp:702
std::shared_ptr< _Tp > Ptr
Definition cvstd_wrapper.hpp:23
void drawKeypoints(InputArray image, const std::vector< KeyPoint > &keypoints, InputOutputArray outImage, const Scalar &color=Scalar::all(-1), DrawMatchesFlags flags=DrawMatchesFlags::DEFAULT)
Draws keypoints.
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
int waitKey(int delay=0)
Waits for a pressed key.
@ IMREAD_COLOR
If set, always convert image to the 3 channel BGR color image.
Definition imgcodecs.hpp:71
CV_EXPORTS_W Mat imread(const String &filename, int flags=IMREAD_COLOR)
Loads an image from a file.
void circle(InputOutputArray img, Point center, int radius, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
Draws a circle.

Constructor & Destructor Documentation

◆ Algorithm()

cv::Algorithm::Algorithm ( )

◆ ~Algorithm()

virtual cv::Algorithm::~Algorithm ( )
virtual

Member Function Documentation

◆ clear()

virtual void cv::Algorithm::clear ( )
inlinevirtual
Python:
cv.Algorithm.clear() -> None

◆ empty()

virtual bool cv::Algorithm::empty ( ) const
inlinevirtual
Python:
cv.Algorithm.empty() -> retval

◆ getDefaultName()

virtual String cv::Algorithm::getDefaultName ( ) const
virtual
Python:
cv.Algorithm.getDefaultName() -> retval

◆ load()

template<typename _Tp >
static Ptr< _Tp > cv::Algorithm::load ( const String filename,
const String objname = String() 
)
inlinestatic

Loads algorithm from the file.

Parameters
filenameName of the file to read.
objnameThe 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):

Ptr<SVM> svm = Algorithm::load<SVM>("my_svm_model.xml");

In order to make this method work, the derived class must overwrite Algorithm::read(const FileNode& fn).

Here is the call graph for this function:

◆ loadFromString()

template<typename _Tp >
static Ptr< _Tp > cv::Algorithm::loadFromString ( const String strModel,
const String objname = String() 
)
inlinestatic

Loads algorithm from a String.

Parameters
strModelThe string variable containing the model you want to load.
objnameThe 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):

Ptr<SVM> svm = Algorithm::loadFromString<SVM>(myStringModel);
Here is the call graph for this function:

◆ read() [1/2]

virtual void cv::Algorithm::read ( const FileNode fn)
inlinevirtual
Python:
cv.Algorithm.read(fn) -> None

◆ read() [2/2]

template<typename _Tp >
static Ptr< _Tp > cv::Algorithm::read ( const FileNode fn)
inlinestatic
Python:
cv.Algorithm.read(fn) -> None

Reads algorithm from the file node.

This is static template method of Algorithm. It's usage is following (in the case of SVM):

cv::FileStorage fsRead("example.xml", FileStorage::READ);
Ptr<SVM> svm = Algorithm::read<SVM>(fsRead.root());

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)

◆ save()

virtual void cv::Algorithm::save ( const String filename) const
virtual
Python:
cv.Algorithm.save(filename) -> None

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

◆ write() [1/3]

void cv::Algorithm::write ( const Ptr< FileStorage > &  fs,
const String name = String() 
) const
Python:
cv.Algorithm.write(fs) -> None
cv.Algorithm.write(fs, name) -> None

◆ write() [2/3]

virtual void cv::Algorithm::write ( FileStorage fs) const
inlinevirtual
Python:
cv.Algorithm.write(fs) -> None
cv.Algorithm.write(fs, name) -> None

◆ write() [3/3]

void cv::Algorithm::write ( FileStorage fs,
const String name 
) const
Python:
cv.Algorithm.write(fs) -> None
cv.Algorithm.write(fs, name) -> None

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

◆ writeFormat()

void cv::Algorithm::writeFormat ( FileStorage fs) const
protected

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