#include <NeuralNetwork.hpp>

Inheritance diagram for fast::NeuralNetwork:

Collaboration diagram for fast::NeuralNetwork:

Public Member Functions
void	load (std::string filename)

void	load (std::vector< uint8_t > model, std::vector< uint8_t > weights)

void	setInferenceEngine (InferenceEngine::pointer engine)

void	setInferenceEngine (std::string engine)

InferenceEngine::pointer	getInferenceEngine () const

void	setInputNode (uint portID, std::string name, NodeType type=NodeType::IMAGE, TensorShape shape={})

void	setOutputNode (uint portID, std::string name, NodeType type=NodeType::IMAGE, TensorShape shape={})

void	setScaleFactor (float scale)

void	setMeanAndStandardDeviation (float mean, float std)

void	setMinAndMaxIntensity (float min, float max)

void	setSignedInputNormalization (bool signedInputNormalization)

void	setPreserveAspectRatio (bool preserve)

void	setHorizontalFlipping (bool flip)

void	setTemporalWindow (uint window)

virtual void	setInputSize (std::string name, std::vector< int > size)

void	loadAttributes ()

virtual	~NeuralNetwork ()

Public Member Functions inherited from fast::ProcessObject
virtual	~ProcessObject ()

void	update (int executeToken=-1)

RuntimeMeasurement::pointer	getRuntime ()

RuntimeMeasurement::pointer	getRuntime (std::string name)

RuntimeMeasurementsManager::pointer	getAllRuntimes ()

void	enableRuntimeMeasurements ()

void	disableRuntimeMeasurements ()

void	setMainDevice (ExecutionDevice::pointer device)

void	setMainDeviceCriteria (const DeviceCriteria &citeria)

ExecutionDevice::pointer	getMainDevice () const

void	setDevice (uint deviceNumber, ExecutionDevice::pointer device)

void	setDeviceCriteria (uint deviceNumber, const DeviceCriteria &criteria)

ExecutionDevice::pointer	getDevice (uint deviceNumber) const

virtual DataChannel::pointer	getOutputPort (uint portID=0)

virtual DataChannel::pointer	getInputPort (uint portID=0)

virtual void	setInputConnection (DataChannel::pointer port)

virtual void	setInputConnection (uint portID, DataChannel::pointer port)

virtual void	setInputData (DataObject::pointer data)

virtual void	setInputData (uint portID, DataObject::pointer data)

int	getNrOfInputConnections () const

int	getNrOfOutputPorts () const

virtual std::string	getNameOfClass () const =0

std::shared_ptr< Attribute >	getAttribute (std::string id)

std::unordered_map< std::string, std::shared_ptr< Attribute > >	getAttributes ()

void	setAttributes (std::vector< std::shared_ptr< Attribute >> attributes)

void	stopPipeline ()

void	setModified (bool modified)

template<class DataType >
std::shared_ptr< DataType >	updateAndGetOutputData (uint portID=0)

Public Member Functions inherited from fast::Object
	Object ()

virtual	~Object ()

Reporter &	getReporter ()

Protected Member Functions
	NeuralNetwork ()

virtual void	run ()

std::unordered_map< std::string, Tensor::pointer >	processInputData ()

std::vector< std::shared_ptr< Image > >	resizeImages (const std::vector< std::shared_ptr< Image >> &images, int width, int height, int depth)

Tensor::pointer	convertImagesToTensor (std::vector< std::shared_ptr< Image >> image, const TensorShape &shape, bool temporal)

Tensor::pointer	standardizeOutputTensorData (Tensor::pointer tensor, int sample=0)

Protected Member Functions inherited from fast::ProcessObject
	ProcessObject ()

virtual void	preExecute ()

virtual void	postExecute ()

template<class DataType >
void	createInputPort (uint portID, bool required=true)

template<class DataType >
void	createOutputPort (uint portID)

template<class DataType >
std::shared_ptr< DataType >	getInputData (uint portID=0)

template<class DataType >
std::shared_ptr< DataType >	getOutputData (uint portID=0)

void	addOutputData (uint portID, DataObject::pointer data)

bool	hasNewInputData (uint portID)

virtual void	waitToFinish ()

void	createOpenCLProgram (std::string sourceFilename, std::string name="")

cl::Program	getOpenCLProgram (std::shared_ptr< OpenCLDevice > device, std::string name="", std::string buildOptions="")

void	createFloatAttribute (std::string id, std::string name, std::string description, float initialValue)

void	createIntegerAttribute (std::string id, std::string name, std::string description, int initialValue)

void	createBooleanAttribute (std::string id, std::string name, std::string description, bool initialValue)

void	createStringAttribute (std::string id, std::string name, std::string description, std::string initialValue)

float	getFloatAttribute (std::string id)

int	getIntegerAttribute (std::string id)

bool	getBooleanAttribute (std::string id)

std::string	getStringAttribute (std::string id)

std::vector< float >	getFloatListAttribute (std::string id)

std::vector< int >	getIntegerListAttribute (std::string id)

std::vector< bool >	getBooleanListAttribute (std::string id)

std::vector< std::string >	getStringListAttribute (std::string id)

void	changeDeviceOnInputs (uint deviceNumber, ExecutionDevice::pointer device)

void	validateInputPortExists (uint portID)

void	validateOutputPortExists (uint portID)

Protected Member Functions inherited from fast::Object
Reporter &	reportError ()

Reporter &	reportWarning ()

Reporter &	reportInfo ()

ReporterEnd	reportEnd () const

Protected Attributes
bool	mPreserveAspectRatio

bool	mHorizontalImageFlipping = false

bool	mSignedInputNormalization = false

int	mTemporalWindow = 0

int	m_batchSize

float	mScaleFactor

float	mMean

float	mStd

float	mMinIntensity

float	mMaxIntensity

bool	mMinAndMaxIntensitySet = false

Vector3f	mNewInputSpacing

std::unordered_map< std::string, std::vector< int > >	mInputSizes

std::unordered_map< int, DataObject::pointer >	m_processedOutputData

std::shared_ptr< InferenceEngine >	m_engine

std::unordered_map< std::string, std::vector< std::shared_ptr< Image > > >	mInputImages

std::unordered_map< std::string, std::vector< std::shared_ptr< Tensor > > >	mInputTensors

Protected Attributes inherited from fast::ProcessObject
bool	mIsModified

int	m_lastExecuteToken = -1

RuntimeMeasurementsManager::pointer	mRuntimeManager

std::unordered_map< uint, bool >	mRequiredInputs

std::unordered_map< uint, std::vector< uint > >	mInputDevices

std::unordered_map< uint, ExecutionDevice::pointer >	mDevices

std::unordered_map< uint, DeviceCriteria >	mDeviceCriteria

std::unordered_map< uint, DataChannel::pointer >	mInputConnections

std::unordered_map< uint, std::vector< std::weak_ptr< DataChannel > > >	mOutputConnections

std::unordered_map< uint, bool >	mInputPorts

std::unordered_set< uint >	mOutputPorts

std::unordered_map< uint, std::pair< DataObject::pointer, uint64_t > >	mLastProcessed

std::unordered_map< std::string, std::shared_ptr< OpenCLProgram > >	mOpenCLPrograms

std::unordered_map< std::string, std::shared_ptr< Attribute > >	mAttributes

std::unordered_map< std::string, std::string >	m_frameData

std::unordered_set< std::string >	m_lastFrame

int	m_maximumNrOfFrames = -1

Protected Attributes inherited from fast::Object
std::weak_ptr< Object >	mPtr

Additional Inherited Members
Public Types inherited from fast::ProcessObject
typedef std::shared_ptr< ProcessObject >	pointer

Public Types inherited from fast::Object
typedef std::shared_ptr< Object >	pointer

Static Public Member Functions inherited from fast::ProcessObject
static std::string	getStaticNameOfClass ()

Static Public Member Functions inherited from fast::Object
static std::string	getStaticNameOfClass ()

Constructor & Destructor Documentation

◆ ~NeuralNetwork()

virtual fast::NeuralNetwork::~NeuralNetwork ( )

virtual

◆ NeuralNetwork()

fast::NeuralNetwork::NeuralNetwork ( )

protected

Member Function Documentation

◆ convertImagesToTensor()

Tensor::pointer fast::NeuralNetwork::convertImagesToTensor	(	std::vector< std::shared_ptr< Image >>	image,
		const TensorShape &	shape,
		bool	temporal
	)

protected

◆ getInferenceEngine()

InferenceEngine::pointer fast::NeuralNetwork::getInferenceEngine ( ) const

Retrieve current inference engine

Returns

◆ load() [1/2]

void fast::NeuralNetwork::load ( std::string filename )

Load a given netowrk file. This takes time.

Parameters

filename

◆ load() [2/2]

void fast::NeuralNetwork::load	(	std::vector< uint8_t >	model,
		std::vector< uint8_t >	weights
	)

Load a network from memory provided as byte two byte vectors: model and weights

Parameters

model
weights

◆ loadAttributes()

void fast::NeuralNetwork::loadAttributes ( )

virtual

Reimplemented from fast::ProcessObject.

Reimplemented in fast::SegmentationNetwork.

◆ processInputData()

std::unordered_map<std::string, Tensor::pointer> fast::NeuralNetwork::processInputData ( )

protected

◆ resizeImages()

std::vector<std::shared_ptr<Image> > fast::NeuralNetwork::resizeImages	(	const std::vector< std::shared_ptr< Image >> &	images,
		int	width,
		int	height,
		int	depth
	)

protected

◆ run()

virtual void fast::NeuralNetwork::run ( )

protectedvirtual

◆ setHorizontalFlipping()

void fast::NeuralNetwork::setHorizontalFlipping ( bool flip )

Setting this parameter to true will flip the input image horizontally. For pixel classification the output image will be flipped back.

Parameters

flip

◆ setInferenceEngine() [1/2]

void fast::NeuralNetwork::setInferenceEngine ( InferenceEngine::pointer engine )

Specify which inference engine to use

Parameters

engine

◆ setInferenceEngine() [2/2]

void fast::NeuralNetwork::setInferenceEngine ( std::string engine )

Specify which inference engine to use

Parameters

engine

◆ setInputNode()

void fast::NeuralNetwork::setInputNode	(	uint	portID,
		std::string	name,
		NodeType	type = `NodeType::IMAGE`,
		TensorShape	shape = `{}`
	)

◆ setInputSize()

virtual void fast::NeuralNetwork::setInputSize	(	std::string	name,
		std::vector< int >	size
	)

virtual

◆ setMeanAndStandardDeviation()

void fast::NeuralNetwork::setMeanAndStandardDeviation	(	float	mean,
		float	std
	)

For each input value i: new_i = (i - mean)/std, this is applied after the scale factor

Parameters

mean
std

◆ setMinAndMaxIntensity()

void fast::NeuralNetwork::setMinAndMaxIntensity	(	float	min,
		float	max
	)

Intensities of input image will be clipped at these values

Parameters

min
max

◆ setOutputNode()

void fast::NeuralNetwork::setOutputNode	(	uint	portID,
		std::string	name,
		NodeType	type = `NodeType::IMAGE`,
		TensorShape	shape = `{}`
	)

◆ setPreserveAspectRatio()

void fast::NeuralNetwork::setPreserveAspectRatio ( bool preserve )

◆ setScaleFactor()

void fast::NeuralNetwork::setScaleFactor ( float scale )

For each input value i: new_i = i*scale

Parameters

scale

◆ setSignedInputNormalization()

void fast::NeuralNetwork::setSignedInputNormalization ( bool signedInputNormalization )

◆ setTemporalWindow()

void fast::NeuralNetwork::setTemporalWindow ( uint window )

Set the temporal window for dynamic mode. If window > 1, assume the second dimension of the input tensor is the number of timesteps. If the window is set to 4, the frames t-3, t-2, t-1 and t, where t is the current timestep, will be given as input to the network.

Parameters

window

◆ standardizeOutputTensorData()

Tensor::pointer fast::NeuralNetwork::standardizeOutputTensorData	(	Tensor::pointer	tensor,
		int	sample = `0`
	)

protected

Converts a tensor to channel last image ordering and takes care of frame data and spacing

Parameters

tensor

Returns

Member Data Documentation

◆ m_batchSize

int fast::NeuralNetwork::m_batchSize

protected

◆ m_engine

std::shared_ptr<InferenceEngine> fast::NeuralNetwork::m_engine

protected

◆ m_processedOutputData

std::unordered_map<int, DataObject::pointer> fast::NeuralNetwork::m_processedOutputData

protected

◆ mHorizontalImageFlipping

bool fast::NeuralNetwork::mHorizontalImageFlipping = false

protected

◆ mInputImages

std::unordered_map<std::string, std::vector<std::shared_ptr<Image> > > fast::NeuralNetwork::mInputImages

protected

◆ mInputSizes

std::unordered_map<std::string, std::vector<int> > fast::NeuralNetwork::mInputSizes

protected

◆ mInputTensors

std::unordered_map<std::string, std::vector<std::shared_ptr<Tensor> > > fast::NeuralNetwork::mInputTensors

protected

◆ mMaxIntensity

float fast::NeuralNetwork::mMaxIntensity

protected

◆ mMean

float fast::NeuralNetwork::mMean

protected

◆ mMinAndMaxIntensitySet

bool fast::NeuralNetwork::mMinAndMaxIntensitySet = false

protected

◆ mMinIntensity

float fast::NeuralNetwork::mMinIntensity

protected

◆ mNewInputSpacing

Vector3f fast::NeuralNetwork::mNewInputSpacing

protected

◆ mPreserveAspectRatio

bool fast::NeuralNetwork::mPreserveAspectRatio

protected

◆ mScaleFactor

float fast::NeuralNetwork::mScaleFactor

protected

◆ mSignedInputNormalization

bool fast::NeuralNetwork::mSignedInputNormalization = false

protected

◆ mStd

float fast::NeuralNetwork::mStd

protected

◆ mTemporalWindow

int fast::NeuralNetwork::mTemporalWindow = 0

protected

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

Algorithms/NeuralNetwork/NeuralNetwork.hpp

Public Member Functions

Protected Member Functions

Protected Attributes

Additional Inherited Members

Constructor & Destructor Documentation

◆ ~NeuralNetwork()

◆ NeuralNetwork()

Member Function Documentation

◆ convertImagesToTensor()

◆ getInferenceEngine()

◆ load() [1/2]

◆ load() [2/2]

◆ loadAttributes()

◆ processInputData()

◆ resizeImages()

◆ run()

◆ setHorizontalFlipping()

◆ setInferenceEngine() [1/2]

◆ setInferenceEngine() [2/2]

◆ setInputNode()

◆ setInputSize()

◆ setMeanAndStandardDeviation()

◆ setMinAndMaxIntensity()

◆ setOutputNode()

◆ setPreserveAspectRatio()

◆ setScaleFactor()

◆ setSignedInputNormalization()

◆ setTemporalWindow()

◆ standardizeOutputTensorData()

Member Data Documentation

◆ m_batchSize

◆ m_engine

◆ m_processedOutputData

◆ mHorizontalImageFlipping

◆ mInputImages

◆ mInputSizes

◆ mInputTensors

◆ mMaxIntensity

◆ mMean

◆ mMinAndMaxIntensitySet

◆ mMinIntensity

◆ mNewInputSpacing

◆ mPreserveAspectRatio

◆ mScaleFactor

◆ mSignedInputNormalization

◆ mStd

◆ mTemporalWindow