OpenCV  3.1.0
Open Source Computer Vision
Public Member Functions | Static Public 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 "core.hpp"

Inheritance diagram for cv::Algorithm:
cv::AlignExposures cv::BackgroundSubtractor cv::BaseCascadeClassifier cv::bioinspired::Retina cv::bioinspired::RetinaFastToneMapping cv::bioinspired::TransientAreasSegmentationModule cv::CalibrateCRF cv::ccalib::CustomPattern cv::CLAHE cv::cuda::CannyEdgeDetector cv::cuda::CascadeClassifier cv::cuda::Convolution cv::cuda::CornernessCriteria cv::cuda::CornersDetector cv::cuda::DenseOpticalFlow cv::cuda::DescriptorMatcher cv::cuda::DisparityBilateralFilter cv::cuda::Filter cv::cuda::HOG cv::cuda::HoughCirclesDetector cv::cuda::HoughLinesDetector cv::cuda::HoughSegmentDetector cv::cuda::ImagePyramid cv::cuda::LookUpTable cv::cuda::SparseOpticalFlow cv::cuda::TemplateMatching cv::DenseOpticalFlow cv::DescriptorMatcher cv::face::FaceRecognizer cv::Feature2D cv::GeneralizedHough cv::HistogramCostExtractor cv::line_descriptor::BinaryDescriptor cv::line_descriptor::BinaryDescriptorMatcher cv::line_descriptor::LSDDetector cv::LineSegmentDetector cv::MergeExposures cv::MinProblemSolver cv::ml::StatModel cv::ml::SVM::Kernel cv::plot::Plot2d cv::rgbd::DepthCleaner cv::rgbd::Odometry cv::rgbd::RgbdNormals cv::rgbd::RgbdPlane cv::saliency::Saliency cv::ShapeDistanceExtractor cv::ShapeTransformer cv::stereo::StereoMatcher cv::StereoMatcher cv::structured_light::StructuredLightPattern cv::superres::DenseOpticalFlowExt cv::superres::SuperResolution cv::text::ERFilter cv::Tonemap cv::Tracker cv::ximgproc::AdaptiveManifoldFilter cv::ximgproc::DisparityFilter cv::ximgproc::DTFilter cv::ximgproc::FastGlobalSmootherFilter cv::ximgproc::GuidedFilter cv::ximgproc::RFFeatureGetter cv::ximgproc::segmentation::GraphSegmentation cv::ximgproc::SparseMatchInterpolator cv::ximgproc::StructuredEdgeDetection cv::ximgproc::SuperpixelLSC cv::ximgproc::SuperpixelSEEDS cv::ximgproc::SuperpixelSLIC

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...
 

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 SIFT use in your application via Algorithm interface:

#include "opencv2/opencv.hpp"
using namespace cv::xfeatures2d;
Ptr<Feature2D> sift = SIFT::create();
FileStorage fs("sift_params.xml", FileStorage::READ);
if( fs.isOpened() ) // if we have file with parameters, read them
{
sift->read(fs["sift_params"]);
fs.release();
}
else // else modify the parameters and store them; user can later edit the file to use different parameters
{
sift->setContrastThreshold(0.01f); // lower the contrast threshold, compared to the default value
{
WriteStructContext ws(fs, "sift_params", CV_NODE_MAP);
sift->write(fs);
}
}
Mat image = imread("myimage.png", 0), descriptors;
vector<KeyPoint> keypoints;
sift->detectAndCompute(image, noArray(), keypoints, descriptors);

Constructor & Destructor Documentation

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

Member Function Documentation

virtual void cv::Algorithm::clear ( )
inlinevirtual
virtual bool cv::Algorithm::empty ( ) const
inlinevirtual

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.

virtual String cv::Algorithm::getDefaultName ( ) const
virtual

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.

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).

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);
virtual void cv::Algorithm::read ( const FileNode fn)
inlinevirtual
template<typename _Tp >
static Ptr<_Tp> cv::Algorithm::read ( const FileNode fn)
inlinestatic

Reads algorithm from the file node.

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

Ptr<SVM> svm = Algorithm::read<SVM>(fn);

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)

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

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.

virtual void cv::Algorithm::write ( FileStorage fs) const
inlinevirtual

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