This class allows to create and manipulate comprehensive artificial neural networks. More...

Public Member Functions
	Net ()

void	connect (string outPin, string inpPin)
	Connects output of the first layer to input of the second layer.

string	dump ()
	Dump net to String.

void	dumpToFile (string path)
	Dump net structure, hyperparameters, backend, target and fusion to dot file.

void	dumpToPbtxt (string path)
	Dump net structure, hyperparameters, backend, target and fusion to pbtxt file.

bool	empty ()

void	enableFusion (bool fusion)
	Enables or disables layer fusion in the network.

void	enableWinograd (bool useWinograd)
	Enables or disables the Winograd compute branch. The Winograd compute branch can speed up 3x3 Convolution at a small loss of accuracy.

Mat	forward ()
	Runs forward pass to compute output of layer with name `outputName`.

void	forward (List< Mat > outputBlobs)
	Runs forward pass to compute output of layer with name `outputName`.

void	forward (List< Mat > outputBlobs, List< string > outBlobNames)
	Runs forward pass to compute outputs of layers listed in `outBlobNames`.

void	forward (List< Mat > outputBlobs, string outputName)
	Runs forward pass to compute output of layer with name `outputName`.

Mat	forward (string outputName)
	Runs forward pass to compute output of layer with name `outputName`.

long	getFLOPS (int layerId, List< MatOfInt > netInputShapes)

long	getFLOPS (int layerId, MatOfInt netInputShape)

long	getFLOPS (List< MatOfInt > netInputShapes)
	Computes FLOP for whole loaded model with specified input shapes.

long	getFLOPS (MatOfInt netInputShape)

void	getInputDetails (MatOfFloat scales, MatOfInt zeropoints)
	Returns input scale and zeropoint for a quantized Net.

Layer	getLayer (DictValue layerId)

Layer	getLayer (int layerId)
	Returns pointer to layer with specified id or name which the network use.

Layer	getLayer (string layerName)

int	getLayerId (string layer)
	Converts string name of the layer to the integer identifier.

List< string >	getLayerNames ()

int	getLayersCount (string layerType)
	Returns count of layers of specified type.

void	getLayerTypes (List< string > layersTypes)
	Returns list of types for layer used in model.

void	getMemoryConsumption (int layerId, List< MatOfInt > netInputShapes, long[] weights, long[] blobs)

void	getMemoryConsumption (int layerId, MatOfInt netInputShape, long[] weights, long[] blobs)

void	getMemoryConsumption (MatOfInt netInputShape, long[] weights, long[] blobs)

IntPtr	getNativeObjAddr ()

void	getOutputDetails (MatOfFloat scales, MatOfInt zeropoints)
	Returns output scale and zeropoint for a quantized Net.

Mat	getParam (int layer)
	Returns parameter blob of the layer.

Mat	getParam (int layer, int numParam)
	Returns parameter blob of the layer.

Mat	getParam (string layerName)

Mat	getParam (string layerName, int numParam)

long	getPerfProfile (MatOfDouble timings)
	Returns overall time for inference and timings (in ticks) for layers.

MatOfInt	getUnconnectedOutLayers ()
	Returns indexes of layers with unconnected outputs.

List< string >	getUnconnectedOutLayersNames ()
	Returns names of layers with unconnected outputs.

Net	quantize (List< Mat > calibData, int inputsDtype, int outputsDtype)
	Returns a quantized Net from a floating-point Net.

Net	quantize (List< Mat > calibData, int inputsDtype, int outputsDtype, bool perChannel)
	Returns a quantized Net from a floating-point Net.

void	setHalideScheduler (string scheduler)
	Compile Halide layers.

void	setInput (Mat blob)
	Sets the new input value for the network.

void	setInput (Mat blob, string name)
	Sets the new input value for the network.

void	setInput (Mat blob, string name, double scalefactor)
	Sets the new input value for the network.

void	setInput (Mat blob, string name, double scalefactor, in Vec4d mean)
	Sets the new input value for the network.

void	setInput (Mat blob, string name, double scalefactor, in(double v0, double v1, double v2, double v3) mean)
	Sets the new input value for the network.

void	setInput (Mat blob, string name, double scalefactor, Scalar mean)
	Sets the new input value for the network.

void	setInputShape (string inputName, MatOfInt shape)
	Specify shape of network input.

void	setInputsNames (List< string > inputBlobNames)
	Sets outputs names of the network input pseudo layer.

void	setParam (int layer, int numParam, Mat blob)
	Sets the new value for the learned param of the layer.

void	setParam (string layerName, int numParam, Mat blob)

void	setPreferableBackend (int backendId)
	Ask network to use specific computation backend where it supported.

void	setPreferableTarget (int targetId)
	Ask network to make computations on specific target device.

Public Member Functions inherited from OpenCVForUnity.DisposableObject
void	Dispose ()

void	ThrowIfDisposed ()

Static Public Member Functions
static Net	__fromPtr__ (IntPtr addr)

static Net	readFromModelOptimizer (MatOfByte bufferModelConfig, MatOfByte bufferWeights)
	Create a network from Intel's Model Optimizer in-memory buffers with intermediate representation (IR).

static Net	readFromModelOptimizer (string xml, string bin)
	Create a network from Intel's Model Optimizer intermediate representation (IR).

Static Public Member Functions inherited from OpenCVForUnity.DisposableObject
static IntPtr	ThrowIfNullIntPtr (IntPtr ptr)

Protected Member Functions
override void	Dispose (bool disposing)

Protected Member Functions inherited from OpenCVForUnity.DisposableOpenCVObject
	DisposableOpenCVObject ()

	DisposableOpenCVObject (bool isEnabledDispose)

	DisposableOpenCVObject (IntPtr ptr)

	DisposableOpenCVObject (IntPtr ptr, bool isEnabledDispose)

Protected Member Functions inherited from OpenCVForUnity.DisposableObject
	DisposableObject ()

	DisposableObject (bool isEnabledDispose)

Additional Inherited Members
Package Attributes inherited from OpenCVForUnity.DisposableOpenCVObject
Properties inherited from OpenCVForUnity.DisposableObject
bool	IsDisposed `[get, protected set]`

bool	IsEnabledDispose `[get, set]`

Detailed Description

This class allows to create and manipulate comprehensive artificial neural networks.

Neural network is presented as directed acyclic graph (DAG), where vertices are Layer instances, and edges specify relationships between layers inputs and outputs.

Each network layer has unique integer id and unique string name inside its network. LayerId can store either layer name or layer id.

This class supports reference counting of its instances, i. e. copies point to the same instance.

Constructor & Destructor Documentation

◆ Net()

OpenCVForUnity.DnnModule.Net.Net ( )

Member Function Documentation

◆ fromPtr()

static Net OpenCVForUnity.DnnModule.Net.__fromPtr__ ( IntPtr addr )

static

◆ connect()

void OpenCVForUnity.DnnModule.Net.connect	(	string	outPin,
		string	inpPin )

Connects output of the first layer to input of the second layer.

Parameters

outPin	descriptor of the first layer output.
inpPin	descriptor of the second layer input.

Descriptors have the following template <DFN><layer_name>[.input_number]</DFN>:

the first part of the template <DFN>layer_name</DFN> is string name of the added layer. If this part is empty then the network input pseudo layer will be used;
the second optional part of the template <DFN>input_number</DFN> is either number of the layer input, either label one. If this part is omitted then the first layer input will be used.

See also
setNetInputs(), Layer::inputNameToIndex(), Layer.outputNameToIndex()

◆ Dispose()

override void OpenCVForUnity.DnnModule.Net.Dispose ( bool disposing )

protectedvirtual

Reimplemented from OpenCVForUnity.DisposableOpenCVObject.

◆ dump()

string OpenCVForUnity.DnnModule.Net.dump ( )

Dump net to String.

Returns: String with structure, hyperparameters, backend, target and fusion Call method after setInput(). To see correct backend, target and fusion run after forward().

◆ dumpToFile()

void OpenCVForUnity.DnnModule.Net.dumpToFile ( string path )

Dump net structure, hyperparameters, backend, target and fusion to dot file.

Parameters

path	path to output file with .dot extension

dump()

◆ dumpToPbtxt()

void OpenCVForUnity.DnnModule.Net.dumpToPbtxt ( string path )

Dump net structure, hyperparameters, backend, target and fusion to pbtxt file.

Parameters

path	path to output file with .pbtxt extension

Use Netron (https://netron.app) to open the target file to visualize the model. Call method after setInput(). To see correct backend, target and fusion run after forward().

◆ empty()

bool OpenCVForUnity.DnnModule.Net.empty ( )

Returns true if there are no layers in the network.

◆ enableFusion()

void OpenCVForUnity.DnnModule.Net.enableFusion ( bool fusion )

Enables or disables layer fusion in the network.

Parameters

fusion true to enable the fusion, false to disable. The fusion is enabled by default.

◆ enableWinograd()

void OpenCVForUnity.DnnModule.Net.enableWinograd ( bool useWinograd )

Enables or disables the Winograd compute branch. The Winograd compute branch can speed up 3x3 Convolution at a small loss of accuracy.

Parameters

useWinograd true to enable the Winograd compute branch. The default is true.

◆ forward() [1/5]

Mat OpenCVForUnity.DnnModule.Net.forward ( )

Runs forward pass to compute output of layer with name outputName.

Parameters

outputName name for layer which output is needed to get

Returns

blob for first output of specified layer.

By default runs forward pass for the whole network.

◆ forward() [2/5]

void OpenCVForUnity.DnnModule.Net.forward ( List< Mat > outputBlobs )

Runs forward pass to compute output of layer with name outputName.

Parameters

outputBlobs	contains all output blobs for specified layer.
outputName	name for layer which output is needed to get

If outputName is empty, runs forward pass for the whole network.

◆ forward() [3/5]

void OpenCVForUnity.DnnModule.Net.forward	(	List< Mat >	outputBlobs,
		List< string >	outBlobNames )

Runs forward pass to compute outputs of layers listed in outBlobNames.

Parameters

outputBlobs	contains blobs for first outputs of specified layers.
outBlobNames	names for layers which outputs are needed to get

◆ forward() [4/5]

void OpenCVForUnity.DnnModule.Net.forward	(	List< Mat >	outputBlobs,
		string	outputName )

Runs forward pass to compute output of layer with name outputName.

Parameters

outputBlobs	contains all output blobs for specified layer.
outputName	name for layer which output is needed to get

If outputName is empty, runs forward pass for the whole network.

◆ forward() [5/5]

Mat OpenCVForUnity.DnnModule.Net.forward ( string outputName )

Runs forward pass to compute output of layer with name outputName.

Parameters

outputName name for layer which output is needed to get

Returns

blob for first output of specified layer.

By default runs forward pass for the whole network.

◆ getFLOPS() [1/4]

long OpenCVForUnity.DnnModule.Net.getFLOPS	(	int	layerId,
		List< MatOfInt >	netInputShapes )

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ getFLOPS() [2/4]

long OpenCVForUnity.DnnModule.Net.getFLOPS	(	int	layerId,
		MatOfInt	netInputShape )

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ getFLOPS() [3/4]

long OpenCVForUnity.DnnModule.Net.getFLOPS ( List< MatOfInt > netInputShapes )

Computes FLOP for whole loaded model with specified input shapes.

Parameters

netInputShapes vector of shapes for all net inputs.

Returns: computed FLOP.

◆ getFLOPS() [4/4]

long OpenCVForUnity.DnnModule.Net.getFLOPS ( MatOfInt netInputShape )

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ getInputDetails()

void OpenCVForUnity.DnnModule.Net.getInputDetails	(	MatOfFloat	scales,
		MatOfInt	zeropoints )

Returns input scale and zeropoint for a quantized Net.

Parameters

scales	output parameter for returning input scales.
zeropoints	output parameter for returning input zeropoints.

◆ getLayer() [1/3]

Layer OpenCVForUnity.DnnModule.Net.getLayer ( DictValue layerId )

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Deprecated: to be removed

◆ getLayer() [2/3]

Layer OpenCVForUnity.DnnModule.Net.getLayer ( int layerId )

Returns pointer to layer with specified id or name which the network use.

◆ getLayer() [3/3]

Layer OpenCVForUnity.DnnModule.Net.getLayer ( string layerName )

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Deprecated: Use int getLayerId(const String &layer)

◆ getLayerId()

int OpenCVForUnity.DnnModule.Net.getLayerId ( string layer )

Converts string name of the layer to the integer identifier.

Returns: id of the layer, or -1 if the layer wasn't found.

◆ getLayerNames()

List< string > OpenCVForUnity.DnnModule.Net.getLayerNames ( )

◆ getLayersCount()

int OpenCVForUnity.DnnModule.Net.getLayersCount ( string layerType )

Returns count of layers of specified type.

Parameters

layerType type.

Returns: count of layers

◆ getLayerTypes()

void OpenCVForUnity.DnnModule.Net.getLayerTypes ( List< string > layersTypes )

Returns list of types for layer used in model.

Parameters

layersTypes output parameter for returning types.

◆ getMemoryConsumption() [1/3]

void OpenCVForUnity.DnnModule.Net.getMemoryConsumption	(	int	layerId,
		List< MatOfInt >	netInputShapes,
		long[]	weights,
		long[]	blobs )

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ getMemoryConsumption() [2/3]

void OpenCVForUnity.DnnModule.Net.getMemoryConsumption	(	int	layerId,
		MatOfInt	netInputShape,
		long[]	weights,
		long[]	blobs )

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ getMemoryConsumption() [3/3]

void OpenCVForUnity.DnnModule.Net.getMemoryConsumption	(	MatOfInt	netInputShape,
		long[]	weights,
		long[]	blobs )

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ getNativeObjAddr()

IntPtr OpenCVForUnity.DnnModule.Net.getNativeObjAddr ( )

◆ getOutputDetails()

void OpenCVForUnity.DnnModule.Net.getOutputDetails	(	MatOfFloat	scales,
		MatOfInt	zeropoints )

Returns output scale and zeropoint for a quantized Net.

Parameters

scales	output parameter for returning output scales.
zeropoints	output parameter for returning output zeropoints.

◆ getParam() [1/4]

Mat OpenCVForUnity.DnnModule.Net.getParam ( int layer )

Returns parameter blob of the layer.

Parameters

layer	name or id of the layer.
numParam	index of the layer parameter in the Layer::blobs array.

Layer::blobs

◆ getParam() [2/4]

Mat OpenCVForUnity.DnnModule.Net.getParam	(	int	layer,
		int	numParam )

Returns parameter blob of the layer.

Parameters

layer	name or id of the layer.
numParam	index of the layer parameter in the Layer::blobs array.

Layer::blobs

◆ getParam() [3/4]

Mat OpenCVForUnity.DnnModule.Net.getParam ( string layerName )

◆ getParam() [4/4]

Mat OpenCVForUnity.DnnModule.Net.getParam	(	string	layerName,
		int	numParam )

◆ getPerfProfile()

long OpenCVForUnity.DnnModule.Net.getPerfProfile ( MatOfDouble timings )

Returns overall time for inference and timings (in ticks) for layers.

Indexes in returned vector correspond to layers ids. Some layers can be fused with others, in this case zero ticks count will be return for that skipped layers. Supported by DNN_BACKEND_OPENCV on DNN_TARGET_CPU only.

Returns: overall ticks for model inference.

◆ getUnconnectedOutLayers()

MatOfInt OpenCVForUnity.DnnModule.Net.getUnconnectedOutLayers ( )

Returns indexes of layers with unconnected outputs.

FIXIT: Rework API to registerOutput() approach, deprecate this call

◆ getUnconnectedOutLayersNames()

List< string > OpenCVForUnity.DnnModule.Net.getUnconnectedOutLayersNames ( )

Returns names of layers with unconnected outputs.

FIXIT: Rework API to registerOutput() approach, deprecate this call

◆ quantize() [1/2]

Net OpenCVForUnity.DnnModule.Net.quantize	(	List< Mat >	calibData,
		int	inputsDtype,
		int	outputsDtype )

Returns a quantized Net from a floating-point Net.

Parameters

calibData	Calibration data to compute the quantization parameters.
inputsDtype	Datatype of quantized net's inputs. Can be CV_32F or CV_8S.
outputsDtype	Datatype of quantized net's outputs. Can be CV_32F or CV_8S.
perChannel	Quantization granularity of quantized Net. The default is true, that means quantize model in per-channel way (channel-wise). Set it false to quantize model in per-tensor way (or tensor-wise).

◆ quantize() [2/2]

Net OpenCVForUnity.DnnModule.Net.quantize	(	List< Mat >	calibData,
		int	inputsDtype,
		int	outputsDtype,
		bool	perChannel )

Returns a quantized Net from a floating-point Net.

Parameters

calibData	Calibration data to compute the quantization parameters.
inputsDtype	Datatype of quantized net's inputs. Can be CV_32F or CV_8S.
outputsDtype	Datatype of quantized net's outputs. Can be CV_32F or CV_8S.
perChannel	Quantization granularity of quantized Net. The default is true, that means quantize model in per-channel way (channel-wise). Set it false to quantize model in per-tensor way (or tensor-wise).

◆ readFromModelOptimizer() [1/2]

static Net OpenCVForUnity.DnnModule.Net.readFromModelOptimizer	(	MatOfByte	bufferModelConfig,
		MatOfByte	bufferWeights )

static

Create a network from Intel's Model Optimizer in-memory buffers with intermediate representation (IR).

Returns: Net object.

◆ readFromModelOptimizer() [2/2]

static Net OpenCVForUnity.DnnModule.Net.readFromModelOptimizer	(	string	xml,
		string	bin )

static

Create a network from Intel's Model Optimizer intermediate representation (IR).

◆ setHalideScheduler()

void OpenCVForUnity.DnnModule.Net.setHalideScheduler ( string scheduler )

Compile Halide layers.

Schedule layers that support Halide backend. Then compile them for specific target. For layers that not represented in scheduling file or if no manual scheduling used at all, automatic scheduling will be applied.

◆ setInput() [1/6]

void OpenCVForUnity.DnnModule.Net.setInput ( Mat blob )

Sets the new input value for the network.

Parameters

blob	A new blob. Should have CV_32F or CV_8U depth.
name	A name of input layer.
scalefactor	An optional normalization scale.
mean	An optional mean subtraction values.

connect(String, String) to know format of the descriptor.

If scale or mean values are specified, a final input blob is computed as:

\[input(n,c,h,w) = scalefactor \times (blob(n,c,h,w) - mean_c)\]

◆ setInput() [2/6]

void OpenCVForUnity.DnnModule.Net.setInput	(	Mat	blob,
		string	name )

Sets the new input value for the network.

Parameters

blob	A new blob. Should have CV_32F or CV_8U depth.
name	A name of input layer.
scalefactor	An optional normalization scale.
mean	An optional mean subtraction values.

connect(String, String) to know format of the descriptor.

If scale or mean values are specified, a final input blob is computed as:

\[input(n,c,h,w) = scalefactor \times (blob(n,c,h,w) - mean_c)\]

◆ setInput() [3/6]

void OpenCVForUnity.DnnModule.Net.setInput	(	Mat	blob,
		string	name,
		double	scalefactor )

Sets the new input value for the network.

Parameters

blob	A new blob. Should have CV_32F or CV_8U depth.
name	A name of input layer.
scalefactor	An optional normalization scale.
mean	An optional mean subtraction values.

connect(String, String) to know format of the descriptor.

If scale or mean values are specified, a final input blob is computed as:

\[input(n,c,h,w) = scalefactor \times (blob(n,c,h,w) - mean_c)\]

◆ setInput() [4/6]

void OpenCVForUnity.DnnModule.Net.setInput	(	Mat	blob,
		string	name,
		double	scalefactor,
		in Vec4d	mean )

Sets the new input value for the network.

Parameters

blob	A new blob. Should have CV_32F or CV_8U depth.
name	A name of input layer.
scalefactor	An optional normalization scale.
mean	An optional mean subtraction values.

connect(String, String) to know format of the descriptor.

If scale or mean values are specified, a final input blob is computed as:

\[input(n,c,h,w) = scalefactor \times (blob(n,c,h,w) - mean_c)\]

◆ setInput() [5/6]

void OpenCVForUnity.DnnModule.Net.setInput	(	Mat	blob,
		string	name,
		double	scalefactor,
		in(double v0, double v1, double v2, double v3)	mean )

Sets the new input value for the network.

Parameters

blob	A new blob. Should have CV_32F or CV_8U depth.
name	A name of input layer.
scalefactor	An optional normalization scale.
mean	An optional mean subtraction values.

connect(String, String) to know format of the descriptor.

If scale or mean values are specified, a final input blob is computed as:

\[input(n,c,h,w) = scalefactor \times (blob(n,c,h,w) - mean_c)\]

◆ setInput() [6/6]

void OpenCVForUnity.DnnModule.Net.setInput	(	Mat	blob,
		string	name,
		double	scalefactor,
		Scalar	mean )

Sets the new input value for the network.

Parameters

blob	A new blob. Should have CV_32F or CV_8U depth.
name	A name of input layer.
scalefactor	An optional normalization scale.
mean	An optional mean subtraction values.

connect(String, String) to know format of the descriptor.

If scale or mean values are specified, a final input blob is computed as:

\[input(n,c,h,w) = scalefactor \times (blob(n,c,h,w) - mean_c)\]

◆ setInputShape()

void OpenCVForUnity.DnnModule.Net.setInputShape	(	string	inputName,
		MatOfInt	shape )

Specify shape of network input.

◆ setInputsNames()

void OpenCVForUnity.DnnModule.Net.setInputsNames ( List< string > inputBlobNames )

Sets outputs names of the network input pseudo layer.

Each net always has special own the network input pseudo layer with id=0. This layer stores the user blobs only and don't make any computations. In fact, this layer provides the only way to pass user data into the network. As any other layer, this layer can label its outputs and this function provides an easy way to do this.

◆ setParam() [1/2]

void OpenCVForUnity.DnnModule.Net.setParam	(	int	layer,
		int	numParam,
		Mat	blob )

Sets the new value for the learned param of the layer.

Parameters

layer	name or id of the layer.
numParam	index of the layer parameter in the Layer::blobs array.
blob	the new value.

Layer::blobs

Note: If shape of the new blob differs from the previous shape, then the following forward pass may fail.

◆ setParam() [2/2]

void OpenCVForUnity.DnnModule.Net.setParam	(	string	layerName,
		int	numParam,
		Mat	blob )

◆ setPreferableBackend()

void OpenCVForUnity.DnnModule.Net.setPreferableBackend ( int backendId )

Ask network to use specific computation backend where it supported.

◆ setPreferableTarget()

void OpenCVForUnity.DnnModule.Net.setPreferableTarget ( int targetId )

Ask network to make computations on specific target device.

List of supported combinations backend / target:

	DNN_BACKEND_OPENCV	DNN_BACKEND_INFERENCE_ENGINE	DNN_BACKEND_HALIDE	DNN_BACKEND_CUDA
DNN_TARGET_CPU	+	+	+
DNN_TARGET_OPENCL	+	+	+
DNN_TARGET_OPENCL_FP16	+	+
DNN_TARGET_MYRIAD		+
DNN_TARGET_FPGA		+
DNN_TARGET_CUDA				+
DNN_TARGET_CUDA_FP16				+
DNN_TARGET_HDDL		+

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

OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/dnn/Net.cs
OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/dnn/Net_Struct.cs
OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/dnn/Net_ValueTuple.cs

Public Member Functions

Static Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ Net()

Member Function Documentation

◆ __fromPtr__()

◆ connect()

◆ Dispose()

◆ dump()

◆ dumpToFile()

◆ dumpToPbtxt()

◆ empty()

◆ enableFusion()

◆ enableWinograd()

◆ forward() [1/5]

◆ forward() [2/5]

◆ forward() [3/5]

◆ forward() [4/5]

◆ forward() [5/5]

◆ getFLOPS() [1/4]

◆ getFLOPS() [2/4]

◆ getFLOPS() [3/4]

◆ getFLOPS() [4/4]

◆ getInputDetails()

◆ getLayer() [1/3]

◆ getLayer() [2/3]

◆ getLayer() [3/3]

◆ getLayerId()

◆ getLayerNames()

◆ getLayersCount()

◆ getLayerTypes()

◆ getMemoryConsumption() [1/3]

◆ getMemoryConsumption() [2/3]

◆ getMemoryConsumption() [3/3]

◆ getNativeObjAddr()

◆ getOutputDetails()

◆ getParam() [1/4]

◆ getParam() [2/4]

◆ getParam() [3/4]

◆ getParam() [4/4]

◆ getPerfProfile()

◆ getUnconnectedOutLayers()

◆ getUnconnectedOutLayersNames()

◆ quantize() [1/2]

◆ quantize() [2/2]

◆ readFromModelOptimizer() [1/2]

◆ readFromModelOptimizer() [2/2]

◆ setHalideScheduler()

◆ setInput() [1/6]

◆ setInput() [2/6]

◆ setInput() [3/6]

◆ setInput() [4/6]

◆ setInput() [5/6]

◆ setInput() [6/6]

◆ setInputShape()

◆ setInputsNames()

◆ setParam() [1/2]

◆ setParam() [2/2]

◆ setPreferableBackend()

◆ setPreferableTarget()

◆ fromPtr()