\( L_p \) - normalization layer. More...

#include "all_layers.hpp"

Inheritance diagram for cv::dnn::NormalizeBBoxLayer:

Static Public Member Functions
static Ptr< NormalizeBBoxLayer >	create (const LayerParams &params)

Static Public Member Functions inherited from cv::Algorithm
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...

Public Attributes
bool	acrossSpatial

float	epsilon

float	pnorm

Public Attributes inherited from cv::dnn::Layer
std::vector< Mat >	blobs
	List of learned parameters must be stored here to allow read them by using Net::getParam(). More...

String	name
	Name of the layer instance, can be used for logging or other internal purposes. More...

int	preferableTarget
	prefer target for layer forwarding More...

String	type
	Type name which was used for creating layer by layer factory. More...

Additional Inherited Members
Public Member Functions inherited from cv::dnn::Layer
	Layer ()

	Layer (const LayerParams &params)
	Initializes only name, type and blobs fields. More...

virtual	~Layer ()

virtual void	applyHalideScheduler (Ptr< BackendNode > &node, const std::vector< Mat *> &inputs, const std::vector< Mat > &outputs, int targetId) const
	Automatic Halide scheduling based on layer hyper-parameters. More...

virtual void	finalize (const std::vector< Mat *> &input, std::vector< Mat > &output)
	Computes and sets internal parameters according to inputs, outputs and blobs. More...

void	finalize (const std::vector< Mat > &inputs, std::vector< Mat > &outputs)

std::vector< Mat >	finalize (const std::vector< Mat > &inputs)

virtual void	forward (std::vector< Mat *> &input, std::vector< Mat > &output, std::vector< Mat > &internals)=0
	Given the `input` blobs, computes the output `blobs`. More...

void	forward (const std::vector< Mat > &inputs, std::vector< Mat > &outputs, std::vector< Mat > &internals)

virtual int64	getFLOPS (const std::vector< MatShape > &inputs, const std::vector< MatShape > &outputs) const

virtual bool	getMemoryShapes (const std::vector< MatShape > &inputs, const int requiredOutputs, std::vector< MatShape > &outputs, std::vector< MatShape > &internals) const

virtual Ptr< BackendNode >	initHalide (const std::vector< Ptr< BackendWrapper > > &inputs)
	Returns Halide backend node. More...

virtual int	inputNameToIndex (String inputName)
	Returns index of input blob into the input array. More...

virtual int	outputNameToIndex (String outputName)
	Returns index of output blob in output array. More...

void	run (const std::vector< Mat > &inputs, std::vector< Mat > &outputs, std::vector< Mat > &internals)
	Allocates layer and computes output. More...

virtual bool	setActivation (const Ptr< ActivationLayer > &layer)
	Tries to attach to the layer the subsequent activation layer, i.e. do the layer fusion in a partial case. More...

virtual bool	setBatchNorm (const Ptr< BatchNormLayer > &layer)
	Tries to attach to the layer the subsequent batch normalization layer, i.e. do the layer fusion in a partial case. More...

void	setParamsFrom (const LayerParams &params)
	Initializes only name, type and blobs fields. More...

virtual bool	setScale (const Ptr< ScaleLayer > &layer)
	Tries to attach to the layer the subsequent scaling layer, i.e. do the layer fusion in a partial case. More...

virtual bool	supportBackend (int backendId)
	Ask layer if it support specific backend for doing computations. More...

virtual Ptr< BackendNode >	tryAttach (const Ptr< BackendNode > &node)
	Implement layers fusing. More...

virtual void	unsetAttached ()
	"Deattaches" all the layers, attached to particular layer. More...

Public Member Functions inherited from cv::Algorithm
	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...

Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const

Detailed Description

\( L_p \) - normalization layer.

Parameters

p	Normalization factor. The most common `p = 1` for \( L_1 \) - normalization or `p = 2` for \( L_2 \) - normalization or a custom one.
eps	Parameter \( \epsilon \) to prevent a division by zero.
across_spatial	If true, normalize an input across all non-batch dimensions. Otherwise normalize an every channel separately.

Across spatial:

\[ norm = \sqrt[p]{\epsilon + \sum_{x, y, c} |src(x, y, c)|^p } \\ dst(x, y, c) = \frac{ src(x, y, c) }{norm} \]

Channel wise normalization:

\[ norm(c) = \sqrt[p]{\epsilon + \sum_{x, y} |src(x, y, c)|^p } \\ dst(x, y, c) = \frac{ src(x, y, c) }{norm(c)} \]

Where x, y - spatial cooridnates, c - channel.

An every sample in the batch is normalized separately. Optionally, output is scaled by the trained parameters.

Member Function Documentation

§ create()

static Ptr<NormalizeBBoxLayer> cv::dnn::NormalizeBBoxLayer::create ( const LayerParams & params )

static

Member Data Documentation

§ acrossSpatial

bool cv::dnn::NormalizeBBoxLayer::acrossSpatial

§ epsilon

float cv::dnn::NormalizeBBoxLayer::epsilon

§ pnorm

float cv::dnn::NormalizeBBoxLayer::pnorm

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

dnn/include/opencv2/dnn/all_layers.hpp

Static Public Member Functions

Public Attributes