cv::saliency::ObjectnessBING クラス

Objectness algorithms based on [3] [3] Cheng, Ming-Ming, et al. "BING: Binarized normed gradients for objectness estimation at 300fps." IEEE CVPR. 2014. [詳解]

#include <saliencySpecializedClasses.hpp>

cv::saliency::Objectnessを継承しています。

公開メンバ関数
CV_WRAP bool	computeSaliency (InputArray image, OutputArray saliencyMap)
CV_WRAP void	read ()
CV_WRAP void	write () const
CV_WRAP std::vector< float >	getobjectnessValues ()
	Return the list of the rectangles' objectness value, [詳解]
CV_WRAP void	setTrainingPath (const String &trainingPath)
	This is a utility function that allows to set the correct path from which the algorithm will load the trained model. [詳解]
CV_WRAP void	setBBResDir (const String &resultsDir)
	This is a utility function that allows to set an arbitrary path in which the algorithm will save the optional results [詳解]
CV_WRAP double	getBase () const
CV_WRAP void	setBase (double val)
CV_WRAP int	getNSS () const
CV_WRAP void	setNSS (int val)
CV_WRAP int	getW () const
CV_WRAP void	setW (int val)
基底クラス cv::saliency::Saliency に属する継承公開メンバ関数
virtual	~Saliency ()
	Destructor
CV_WRAP bool	computeSaliency (InputArray image, OutputArray saliencyMap)
	Compute the saliency [詳解]
基底クラス cv::Algorithm に属する継承公開メンバ関数
virtual CV_WRAP void	clear ()
	Clears the algorithm state [詳解]
virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage [詳解]
CV_WRAP void	write (const Ptr< FileStorage > &fs, const String &name=String()) const
	simplified API for language bindings これはオーバーロードされたメンバ関数です。利便性のために用意されています。元の関数との違いは引き数のみです。
virtual CV_WRAP void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage [詳解]
virtual CV_WRAP bool	empty () const
	Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read [詳解]
virtual CV_WRAP void	save (const String &filename) const
virtual CV_WRAP String	getDefaultName () const

静的公開メンバ関数
static CV_WRAP Ptr< ObjectnessBING >	create ()
基底クラス cv::Algorithm に属する継承静的公開メンバ関数
template<typename _Tp >
static Ptr< _Tp >	read (const FileNode &fn)
	Reads algorithm from the file node [詳解]
template<typename _Tp >
static Ptr< _Tp >	load (const String &filename, const String &objname=String())
	Loads algorithm from the file [詳解]
template<typename _Tp >
static Ptr< _Tp >	loadFromString (const String &strModel, const String &objname=String())
	Loads algorithm from a String [詳解]

限定公開メンバ関数
bool	computeSaliencyImpl (InputArray image, OutputArray objectnessBoundingBox) CV_OVERRIDE
	Performs all the operations and calls all internal functions necessary for the accomplishment of the Binarized normed gradients algorithm. [詳解]
基底クラス cv::Algorithm に属する継承限定公開メンバ関数
void	writeFormat (FileStorage &fs) const

その他の継承メンバ
基底クラス cv::saliency::Saliency に属する継承限定公開変数類
String	className

詳解

Objectness algorithms based on [3] [3] Cheng, Ming-Ming, et al. "BING: Binarized normed gradients for objectness estimation at 300fps." IEEE CVPR. 2014.

the Binarized normed gradients algorithm from [BING]

関数詳解

computeSaliencyImpl()

bool cv::saliency::ObjectnessBING::computeSaliencyImpl ( InputArray  image, OutputArray  objectnessBoundingBox  )

protectedvirtual

Performs all the operations and calls all internal functions necessary for the accomplishment of the Binarized normed gradients algorithm.

引数

image	input image. According to the needs of this specialized algorithm, the param image is a single Mat
objectnessBoundingBox	objectness Bounding Box vector. According to the result given by this specialized algorithm, the objectnessBoundingBox is a vector<Vec4i>. Each bounding box is represented by a Vec4i for (minX, minY, maxX, maxY).

cv::saliency::Objectnessを実装しています。

getobjectnessValues()

CV_WRAP std::vector< float > cv::saliency::ObjectnessBING::getobjectnessValues

(

)

Return the list of the rectangles' objectness value,

in the same order as the vector<Vec4i> objectnessBoundingBox returned by the algorithm (in computeSaliencyImpl function). The bigger value these scores are, it is more likely to be an object window.

setBBResDir()

CV_WRAP void cv::saliency::ObjectnessBING::setBBResDir

(

const String &

resultsDir

)

This is a utility function that allows to set an arbitrary path in which the algorithm will save the optional results

(ie writing on file the total number and the list of rectangles returned by objectess, one for each row).

引数

resultsDir

results' folder path

setTrainingPath()

CV_WRAP void cv::saliency::ObjectnessBING::setTrainingPath

(

const String &

trainingPath

)

This is a utility function that allows to set the correct path from which the algorithm will load the trained model.

引数

trainingPath

trained model path

---

このクラス詳解は次のファイルから抽出されました:

• saliencySpecializedClasses.hpp