Class cv::Algorithm#

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

#include <opencv2/core.hpp>

Collaboration diagram for cv::Algorithm:

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:

    Ptr<Feature2D> sbd = SimpleBlobDetector::create();
    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);

Constructor & Destructor Documentation#

Algorithm()#

cv::Algorithm::Algorithm()

~Algorithm()#

cv::Algorithm::~Algorithm()

Member Function Documentation#

clear()#

void cv::Algorithm::clear()

Python:

cv.Algorithm.clear()

Clears the algorithm state.

empty()#

bool cv::Algorithm::empty()

Python:

cv.Algorithm.empty() -> retval

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read.

getDefaultName()#

String cv::Algorithm::getDefaultName()

Python:

cv.Algorithm.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.

read()#

void cv::Algorithm::read(const FileNode & fn)

Python:

cv.Algorithm.read(fn)

Reads algorithm parameters from a file storage.

save()#

void cv::Algorithm::save(const String & filename)

Python:

cv.Algorithm.save(filename)

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

write()#

void cv::Algorithm::write(
const Ptr< FileStorage > & fs,
const String & name = String() )

Python:

cv.Algorithm.write(fs)

cv.Algorithm.write(fs, name)

write()#

void cv::Algorithm::write(FileStorage & fs)

Python:

cv.Algorithm.write(fs)

cv.Algorithm.write(fs, name)

Stores algorithm parameters in a file storage.

write()#

void cv::Algorithm::write(
FileStorage & fs,
const String & name )

Python:

cv.Algorithm.write(fs)

cv.Algorithm.write(fs, name)

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

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load()#

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

Loads algorithm from the file.

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).

Parameters

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)

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loadFromString()#

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

Loads algorithm from a String.

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

Ptr<SVM> svm = Algorithm::loadFromString<SVM>(myStringModel);

Parameters

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)

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read()#

template<typename _Tp>
static Ptr< _Tp > cv::Algorithm::read(const FileNode & fn)

Python:

cv.Algorithm.read(fn)

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)

writeFormat()#

void cv::Algorithm::writeFormat(FileStorage & fs)

Source file#

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

opencv2/core.hpp