The class implements Histogram of Oriented Gradients ([17]) object detector. More...

#include "cudaobjdetect.hpp"

Inheritance diagram for cv::cuda::HOG:

Collaboration diagram for cv::cuda::HOG:

Public Types
enum	{ DESCR_FORMAT_ROW_BY_ROW, DESCR_FORMAT_COL_BY_COL }

Public Member Functions
virtual void	clear ()
	Clears the algorithm state. More...

virtual void	compute (InputArray img, OutputArray descriptors, Stream &stream=Stream::Null())=0
	Returns block descriptors computed for the whole image. More...

virtual void	detect (InputArray img, std::vector< Point > &found_locations, std::vector< double > *confidences=NULL)=0
	Performs object detection without a multi-scale window. More...

virtual void	detectMultiScale (InputArray img, std::vector< Rect > &found_locations, std::vector< double > *confidences=NULL)=0
	Performs object detection with a multi-scale window. More...

virtual bool	empty () const
	Returns true if the Algorithm is empty (e.g. More...

virtual size_t	getBlockHistogramSize () const =0
	Returns the block histogram size. More...

virtual String	getDefaultName () const
	Returns the algorithm string identifier. More...

virtual Mat	getDefaultPeopleDetector () const =0
	Returns coefficients of the classifier trained for people detection. More...

virtual int	getDescriptorFormat () const =0

virtual size_t	getDescriptorSize () const =0
	Returns the number of coefficients required for the classification. More...

virtual bool	getGammaCorrection () const =0

virtual int	getGroupThreshold () const =0

virtual double	getHitThreshold () const =0

virtual double	getL2HysThreshold () const =0

virtual int	getNumLevels () const =0

virtual double	getScaleFactor () const =0

virtual double	getWinSigma () const =0

virtual Size	getWinStride () const =0

virtual void	read (const FileNode &fn)
	Reads algorithm parameters from a file storage. More...

virtual void	save (const String &filename) const
	Saves the algorithm to a file. More...

virtual void	setDescriptorFormat (int descr_format)=0
	Descriptor storage format: More...

virtual void	setGammaCorrection (bool gamma_correction)=0
	Flag to specify whether the gamma correction preprocessing is required or not. More...

virtual void	setGroupThreshold (int group_threshold)=0
	Coefficient to regulate the similarity threshold. More...

virtual void	setHitThreshold (double hit_threshold)=0
	Threshold for the distance between features and SVM classifying plane. More...

virtual void	setL2HysThreshold (double threshold_L2hys)=0
	L2-Hys normalization method shrinkage. More...

virtual void	setNumLevels (int nlevels)=0
	Maximum number of detection window increases. More...

virtual void	setScaleFactor (double scale0)=0
	Coefficient of the detection window increase. More...

virtual void	setSVMDetector (InputArray detector)=0
	Sets coefficients for the linear SVM classifier. More...

virtual void	setWinSigma (double win_sigma)=0
	Gaussian smoothing window parameter. More...

virtual void	setWinStride (Size win_stride)=0
	Window stride. It must be a multiple of block stride. More...

virtual void	write (FileStorage &fs) const
	Stores algorithm parameters in a file storage. More...

Static Public Member Functions
static Ptr< HOG >	create (Size win_size=Size(64, 128), Size block_size=Size(16, 16), Size block_stride=Size(8, 8), Size cell_size=Size(8, 8), int nbins=9)
	Creates the HOG descriptor and detector. More...

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

Detailed Description

The class implements Histogram of Oriented Gradients ([17]) object detector.

Note

An example applying the HOG descriptor for people detection can be found at opencv_source_code/samples/cpp/peopledetect.cpp
A CUDA example applying the HOG descriptor for people detection can be found at opencv_source_code/samples/gpu/hog.cpp
(Python) An example applying the HOG descriptor for people detection can be found at opencv_source_code/samples/python/peopledetect.py

Member Enumeration Documentation

anonymous enum

Enumerator
DESCR_FORMAT_ROW_BY_ROW
DESCR_FORMAT_COL_BY_COL

Member Function Documentation

virtual void cv::Algorithm::clear ( )

inlinevirtualinherited

Clears the algorithm state.

Reimplemented in cv::FlannBasedMatcher, cv::DescriptorMatcher, and cv::cuda::DescriptorMatcher.

virtual void cv::cuda::HOG::compute	(	InputArray	img,
		OutputArray	descriptors,
		Stream &	stream = `Stream::Null()`
	)

pure virtual

Returns block descriptors computed for the whole image.

Parameters

img	Source image. See cuda::HOGDescriptor::detect for type limitations.
descriptors	2D array of descriptors.
stream	CUDA stream.

static Ptr<HOG> cv::cuda::HOG::create	(	Size	win_size = `Size(64, 128)`,
		Size	block_size = `Size(16, 16)`,
		Size	block_stride = `Size(8, 8)`,
		Size	cell_size = `Size(8, 8)`,
		int	nbins = `9`
	)

static

Creates the HOG descriptor and detector.

Parameters

win_size	Detection window size. Align to block size and block stride.
block_size	Block size in pixels. Align to cell size. Only (16,16) is supported for now.
block_stride	Block stride. It must be a multiple of cell size.
cell_size	Cell size. Only (8, 8) is supported for now.
nbins	Number of bins. Only 9 bins per cell are supported for now.

virtual void cv::cuda::HOG::detect	(	InputArray	img,
		std::vector< Point > &	found_locations,
		std::vector< double > *	confidences = `NULL`
	)

pure virtual

Performs object detection without a multi-scale window.

Parameters

img	Source image. CV_8UC1 and CV_8UC4 types are supported for now.
found_locations	Left-top corner points of detected objects boundaries.
confidences	Optional output array for confidences.

virtual void cv::cuda::HOG::detectMultiScale	(	InputArray	img,
		std::vector< Rect > &	found_locations,
		std::vector< double > *	confidences = `NULL`
	)

pure virtual

Performs object detection with a multi-scale window.

Parameters

img	Source image. See cuda::HOGDescriptor::detect for type limitations.
found_locations	Detected objects boundaries.
confidences	Optional output array for confidences.

virtual bool cv::Algorithm::empty ( ) const

inlinevirtualinherited

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 size_t cv::cuda::HOG::getBlockHistogramSize ( ) const

pure virtual

Returns the block histogram size.

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

virtualinherited

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.

virtual Mat cv::cuda::HOG::getDefaultPeopleDetector ( ) const

pure virtual

Returns coefficients of the classifier trained for people detection.

virtual int cv::cuda::HOG::getDescriptorFormat ( ) const

pure virtual

virtual size_t cv::cuda::HOG::getDescriptorSize ( ) const

pure virtual

Returns the number of coefficients required for the classification.

virtual bool cv::cuda::HOG::getGammaCorrection ( ) const

pure virtual

virtual int cv::cuda::HOG::getGroupThreshold ( ) const

pure virtual

virtual double cv::cuda::HOG::getHitThreshold ( ) const

pure virtual

virtual double cv::cuda::HOG::getL2HysThreshold ( ) const

pure virtual

virtual int cv::cuda::HOG::getNumLevels ( ) const

pure virtual

virtual double cv::cuda::HOG::getScaleFactor ( ) const

pure virtual

virtual double cv::cuda::HOG::getWinSigma ( ) const

pure virtual

virtual Size cv::cuda::HOG::getWinStride ( ) const

pure virtual

template<typename _Tp >

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

inlinestaticinherited

Loads algorithm from the file.

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)

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).

References cv::Ptr< T >::empty(), cv::FileNode::empty(), cv::FileStorage::getFirstTopLevelNode(), and cv::FileStorage::READ.

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template<typename _Tp >

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

inlinestaticinherited

Loads algorithm from a String.

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)

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

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

References CV_WRAP, cv::Ptr< T >::empty(), cv::FileNode::empty(), cv::FileStorage::getFirstTopLevelNode(), cv::FileStorage::MEMORY, and cv::FileStorage::READ.

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

inlinevirtualinherited

Reads algorithm parameters from a file storage.

Reimplemented in cv::FlannBasedMatcher, cv::DescriptorMatcher, and cv::Feature2D.

template<typename _Tp >

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

inlinestaticinherited

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)

References cv::Ptr< T >::empty().

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

virtualinherited

Saves the algorithm to a file.

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

virtual void cv::cuda::HOG::setDescriptorFormat ( int descr_format )

pure virtual

Descriptor storage format:

DESCR_FORMAT_ROW_BY_ROW - Row-major order.
DESCR_FORMAT_COL_BY_COL - Column-major order.

virtual void cv::cuda::HOG::setGammaCorrection ( bool gamma_correction )

pure virtual

Flag to specify whether the gamma correction preprocessing is required or not.

virtual void cv::cuda::HOG::setGroupThreshold ( int group_threshold )

pure virtual

Coefficient to regulate the similarity threshold.

When detected, some objects can be covered by many rectangles. 0 means not to perform grouping. See groupRectangles.

virtual void cv::cuda::HOG::setHitThreshold ( double hit_threshold )

pure virtual

Threshold for the distance between features and SVM classifying plane.

Usually it is 0 and should be specfied in the detector coefficients (as the last free coefficient). But if the free coefficient is omitted (which is allowed), you can specify it manually here.

virtual void cv::cuda::HOG::setL2HysThreshold ( double threshold_L2hys )

pure virtual

L2-Hys normalization method shrinkage.

virtual void cv::cuda::HOG::setNumLevels ( int nlevels )

pure virtual

Maximum number of detection window increases.

virtual void cv::cuda::HOG::setScaleFactor ( double scale0 )

pure virtual

Coefficient of the detection window increase.

virtual void cv::cuda::HOG::setSVMDetector ( InputArray detector )

pure virtual

Sets coefficients for the linear SVM classifier.

virtual void cv::cuda::HOG::setWinSigma ( double win_sigma )

pure virtual

Gaussian smoothing window parameter.

virtual void cv::cuda::HOG::setWinStride ( Size win_stride )

pure virtual

Window stride. It must be a multiple of block stride.

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

inlinevirtualinherited

Stores algorithm parameters in a file storage.

Reimplemented in cv::FlannBasedMatcher, cv::DescriptorMatcher, and cv::Feature2D.

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

protectedinherited

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

cudaobjdetect/include/opencv2/cudaobjdetect.hpp

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Detailed Description

Member Enumeration Documentation

Member Function Documentation