cv::dnn::SliceLayer Class Reference

#include <opencv2/dnn/all_layers.hpp>

Inheritance diagram for cv::dnn::SliceLayer:

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

Public Attributes
int	axis
std::vector< std::vector< Range > >	sliceRanges
	Vector of slice ranges.
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().
String	name
	Name of the layer instance, can be used for logging or other internal purposes.
int	preferableTarget
	prefer target for layer forwarding
String	type
	Type name which was used for creating layer by layer factory.

Additional Inherited Members
Public Member Functions inherited from cv::dnn::Layer
	Layer ()
	Layer (const LayerParams &params)
	Initializes only name, type and blobs fields.
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.
virtual void	finalize (const std::vector< Mat * > &input, std::vector< Mat > &output)
	Computes and sets internal parameters according to inputs, outputs and blobs.
virtual void	finalize (InputArrayOfArrays inputs, OutputArrayOfArrays outputs)
	Computes and sets internal parameters according to inputs, outputs and blobs.
void	finalize (const std::vector< Mat > &inputs, std::vector< Mat > &outputs)
	This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
std::vector< Mat >	finalize (const std::vector< Mat > &inputs)
	This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
virtual void	forward (std::vector< Mat * > &input, std::vector< Mat > &output, std::vector< Mat > &internals)
	Given the input blobs, computes the output blobs.
virtual void	forward (InputArrayOfArrays inputs, OutputArrayOfArrays outputs, OutputArrayOfArrays internals)
	Given the input blobs, computes the output blobs.
void	forward_fallback (InputArrayOfArrays inputs, OutputArrayOfArrays outputs, OutputArrayOfArrays internals)
	Given the input blobs, computes the output blobs.
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 void	getScaleShift (Mat &scale, Mat &shift) const
	Returns parameters of layers with channel-wise multiplication and addition.
virtual Ptr< BackendNode >	initHalide (const std::vector< Ptr< BackendWrapper > > &inputs)
	Returns Halide backend node.
virtual Ptr< BackendNode >	initInfEngine (const std::vector< Ptr< BackendWrapper > > &inputs)
virtual Ptr< BackendNode >	initVkCom (const std::vector< Ptr< BackendWrapper > > &inputs)
virtual int	inputNameToIndex (String inputName)
	Returns index of input blob into the input array.
virtual int	outputNameToIndex (const String &outputName)
	Returns index of output blob in output array.
void	run (const std::vector< Mat > &inputs, std::vector< Mat > &outputs, std::vector< Mat > &internals)
	Allocates layer and computes output.
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.
void	setParamsFrom (const LayerParams &params)
	Initializes only name, type and blobs fields.
virtual bool	supportBackend (int backendId)
	Ask layer if it support specific backend for doing computations.
virtual Ptr< BackendNode >	tryAttach (const Ptr< BackendNode > &node)
	Implement layers fusing.
virtual bool	tryFuse (Ptr< Layer > &top)
	Try to fuse current layer with a next one.
virtual void	unsetAttached ()
	"Deattaches" all the layers, attached to particular layer.
Protected Member Functions inherited from cv::Algorithm
void	writeFormat (FileStorage &fs) const

Detailed Description

Slice layer has several modes:

1. Caffe mode

   Parameters

   [in]	axis	Axis of split operation
   [in]	slice_point	Array of split points

   Number of output blobs equals to number of split points plus one. The first blob is a slice on input from 0 to slice_point[0] - 1 by axis, the second output blob is a slice of input from slice_point[0] to slice_point[1] - 1 by axis and the last output blob is a slice of input from slice_point[-1] up to the end of axis size.

1. TensorFlow mode

   Parameters

   begin	Vector of start indices
   size	Vector of sizes

   More convenient numpy-like slice. One and only output blob is a slice input[begin[0]:begin[0]+size[0], begin[1]:begin[1]+size[1], ...]

1. Torch mode

   Parameters

   axis	Axis of split operation

   Split input blob on the equal parts by axis.

Member Function Documentation

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

static

Member Data Documentation

int cv::dnn::SliceLayer::axis

std::vector<std::vector<Range> > cv::dnn::SliceLayer::sliceRanges

Vector of slice ranges.

The first dimension equals number of output blobs. Inner vector has slice ranges for the first number of input dimensions.

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

• all_layers.hpp