eVision.EasyDeepLearning.EDeepOCRTool Class Reference

Trains the EasyDeepOCR Deep Learning models. More...

Inheritance diagram for eVision.EasyDeepLearning.EDeepOCRTool:

Collaboration diagram for eVision.EasyDeepLearning.EDeepOCRTool:

Public Member Functions
None	__init__ (self)
	Constructs a eVision.EasyDeepLearning.EDeepOCRTool.
None	__init__ (self, eVision.EasyDeepLearning.EDeepOCRModel model)
	Constructs a eVision.EasyDeepLearning.EDeepOCRTool.
None	__init__ (self, eVision.EasyDeepLearning.EDeepOCRTool other)
	Copy constructor of a eVision.EasyDeepLearning.EDeepOCRTool object.
None	SerializeSettings (self, eVision.ESerializer|None serializer)
	Serializes the eVision.EasyDeepLearning.EDeepOCRTool settings.
None	Train (self, eVision.EasyDeepLearning.EDataset dataset)
	Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.
None	Train (self, eVision.EasyDeepLearning.EDataset dataset, eVision.EasyDeepLearning.EDataAugmentation dataAugmentation)
	Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.
None	Train (self, eVision.EasyDeepLearning.EDataset trainingDataset, eVision.EasyDeepLearning.EDataset validationDataset)
	Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.
None	Train (self, eVision.EasyDeepLearning.EDataset trainingDataset, eVision.EasyDeepLearning.EDataset validationDataset, eVision.EasyDeepLearning.EDataAugmentation dataAugmentation)
	Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.
None	Train (self, eVision.EasyDeepLearning.EDataset dataset, int iterations)
	Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.
None	Train (self, eVision.EasyDeepLearning.EDataset dataset, eVision.EasyDeepLearning.EDataAugmentation dataAugmentation, int iterations)
	Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.
None	Train (self, eVision.EasyDeepLearning.EDataset trainingDataset, eVision.EasyDeepLearning.EDataset validationDataset, int iterations)
	Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.
None	Train (self, eVision.EasyDeepLearning.EDataset trainingDataset, eVision.EasyDeepLearning.EDataset validationDataset, eVision.EasyDeepLearning.EDataAugmentation dataAugmentation, int iterations)
	Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.
eVision.EasyDeepLearning.EDeepOCRToolMetrics	GetTrainingMetrics (self, int i)
	Metrics on the training dataset at the specified iteration of the training.
eVision.EasyDeepLearning.EDeepOCRToolMetrics	GetValidationMetrics (self, int i)
	Metrics on the validation dataset at the specified iteration of the training.
Public Member Functions inherited from eVision.EasyDeepLearning.EDeepLearningTool
None	Load (self, str filePath)
	Loads a deep learning tool.
None	Load (self, eVision.ESerializer|None serializer)
	Loads a deep learning tool.
eVision.EasyDeepLearning.EDeepLearningTool|None	Clone (self)
	Clones this tool.
None	Save (self, str filePath, bool includeTrainingModel)
	Saves the settings, inference and training model of the deep learning tool.
None	Save (self, str filePath)
	Saves the settings, inference and training model of the deep learning tool.
None	Save (self, eVision.ESerializer|None serializer, bool includeTrainingModel)
	Saves the settings, inference and training model of the deep learning tool.
None	Save (self, eVision.ESerializer|None serializer)
	Saves the settings, inference and training model of the deep learning tool.
None	SerializeInferenceModel (self, eVision.ESerializer|None serializer)
	Serializes the inference model of the tool.
None	SerializeTrainingModel (self, eVision.ESerializer|None serializer)
	Serializes the training model of the tool.
None	SaveSettings (self, str filePath)
	Saves the settings of the tool to a file.
None	SaveInferenceModel (self, str filePath)
	Saves the tool's inference model to a file.
None	SaveTrainingModel (self, str filePath)
	Saves the tool's training model to a file.
None	LoadSettings (self, str filePath)
	Loads the settings of a tool.
None	LoadInferenceModel (self, str filePath)
	Loads the tool's inference model.
None	LoadTrainingModel (self, str filePath)
	Loads the tool's training model.
None	UnloadInferenceModel (self)
	Unloads the inference model.
None	UnloadTrainingModel (self)
	Unloads the training model.
None	UnloadModels (self)
	Unloads the inference and training model.
bool	HasInferenceModel (self)
	Whether the inference model is loaded or created when the tool is not yet trained.
bool	HasTrainingModel (self)
	Whether the training model is loaded or created when the tool is not yet trained.
bool	IsTrained (self)
	Tells whether the deep learning tool has been trained.
str	GetAvailableDeviceName (self, int i)
	Name of the i-th device of the current engine.
eVision.EasyDeepLearning.EDeepLearningDevice	GetAvailableDevice (self, int i)
	i-th eVision.EasyDeepLearning.EDeepLearningDevice of the current engine.
None	SetActiveDevice (self, eVision.EasyDeepLearning.EDeepLearningDevice device)
	Sets the device with which to run or train the model.
eVision.EasyDeepLearning.EDeepLearningDevice	GetActiveDevice (self, int i)
	Gets the active device.
eVision.EasyDeepLearning.EDeepLearningDevice	GetActiveDevice (self)
	Gets the active device.
bool	HasEngineSetupData (self)
	Whether the inference model has engine setup data.
None	ClearEngineSetupData (self)
	Clears the engine data saved in the inference model.
bool	IsTraining (self)
	Indicates whether the object is currently training.
int	WaitForTrainingCompletion (self, int timeout)
	Waits until the training is complete or the timeout is expired.
int	WaitForTrainingCompletion (self)
	Waits until the training is complete or the timeout is expired.
int	WaitForIterationCompletion (self)
	Waits until an iteration is complete.
int	StopTraining (self, bool wait)
	Stops training and returns the last completed iteration.
None	SetLearningRate (self, eVision.EasyDeepLearning.EDeepLearningLearningRateType type, list[float] parameters)
	Specifies how the value of the learning rate and how it evolves during training.
None	InitializeInference (self, int width, int height, eVision.EImageType imageType, int numImages)
	Initializes the neural network for inference (i.e.
None	InitializeInference (self, eVision.EBaseROI img)
	Initializes the neural network for inference (i.e.
None	InitializeInference (self, list[eVision._eVision.EBaseROI|None] imgList)
	Initializes the neural network for inference (i.e.
str	GetLabel (self, int index)
	Gets the label from its index.
None	SetLabel (self, int index, str label)
	Changes a label predicted by the tool.
None	SetLabelWeight (self, int index, float weight)
	Sets the label weight.
float	GetLabelWeight (self, int index)
	Gets the label weight.
None	SetLabelColor (self, int index, eVision.ERGBColor c)
	Changes a label color.
eVision.ERGBColor	GetLabelColor (self, int index)
	Label color.
None	SetLabelOpacity (self, int index, int opacity)
	Changes a label opacity (between 0 for fully transparent and 255 for opaque color).
int	GetLabelOpacity (self, int index)
	Gets the label opacity (between 0 for fully transparent and 255 for opaque color).
int	GetOptimalNumImagesForBatchSize (self, eVision.EBaseROI sampleImage)
	Optimal number of images to process together for inference given the batch size and eVision.EasyDeepLearning.EDeepLearningTool.GetNumPatchesForImage.
int	GetOptimalNumImagesForBatchSize (self, int imageWidth, int imageHeight)
	Optimal number of images to process together for inference given the batch size and eVision.EasyDeepLearning.EDeepLearningTool.GetNumPatchesForImage.
int	GetNumPatchesForImage (self, eVision.EBaseROI sampleImage)
	Number of patches that will be extracted from an input image to perform inference.
int	GetNumPatchesForImage (self, int imageWidth, int imageHeight)
	Number of patches that will be extracted from an input image to perform inference.
None	Clean (self)
	Reset the engine and clean CPU and GPU memory allocated for running the model.

Protected Member Functions
eVision.EasyDeepLearning.EDeepLearningToolType	_ToolType__getter (self)
	\cond
eVision.EasyDeepLearning.EDeepOCRModel	_Model__getter (self)
	\cond
	_Model__setter (self, eVision.EasyDeepLearning.EDeepOCRModel value)
	Type of Deep OCR model to train and evaluate.
eVision.EasyDeepLearning.EDeepOCRModelParameters|None	_Parameters__getter (self)
	\cond
	_Parameters__setter (self, eVision.EasyDeepLearning.EDeepOCRModelParameters|None value)
	Parameters of the model.
Protected Member Functions inherited from eVision.EasyDeepLearning.EDeepLearningTool
bool	_EnableGPU__getter (self)
	\cond
	_EnableGPU__setter (self, bool value)
	Enable the use of a GPU for training and inference of the deep learning tool.
list[int]	_GPUIndexes__getter (self)
	\cond
	_GPUIndexes__setter (self, list[int] value)
	Indexes of the GPUs to use for computations.
int	_NumGPUs__getter (self)
	\cond
str	_Engine__getter (self)
	\cond
	_Engine__setter (self, str value)
	Sets the engine with which to execute or train the neural network.
eVision.EasyDeepLearning.EDeepLearningInferencePrecision	_InferencePrecision__getter (self)
	\cond
	_InferencePrecision__setter (self, eVision.EasyDeepLearning.EDeepLearningInferencePrecision value)
	Inference precision.
int	_NumAvailableDevices__getter (self)
	\cond
list[eVision._eVision.EasyDeepLearning.EDeepLearningDevice]	_AvailableDevices__getter (self)
	\cond
int	_NumActiveDevices__getter (self)
	\cond
	_ActiveDeviceByName__setter (self, str value)
	\cond
	_ActiveDeviceById__setter (self, int value)
	\cond
list[eVision._eVision.EasyDeepLearning.EDeepLearningDevice]	_ActiveDevices__getter (self)
	\cond
	_ActiveDevices__setter (self, list[eVision._eVision.EasyDeepLearning.EDeepLearningDevice] value)
	Devices with which to run or train the model.
	_ActiveDevicesById__setter (self, list[int] value)
	\cond
eVision.EasyDeepLearning.EDeepLearningExecutionSettings	_ExecutionSettings__getter (self)
	\cond
	_ExecutionSettings__setter (self, eVision.EasyDeepLearning.EDeepLearningExecutionSettings value)
	Execution settings of the tool (engine, device(s), inference precision, batch size settings).
eVision.EasyDeepLearning.EDeepLearningDevice	_EngineSetupDataDevice__getter (self)
	\cond
eVision.EasyDeepLearning.EDeepLearningInferencePrecision	_EngineSetupDataInferencePrecision__getter (self)
	\cond
int	_EngineSetupDataBatchSize__getter (self)
	\cond
bool	_OptimizeBatchSize__getter (self)
	\cond
	_OptimizeBatchSize__setter (self, bool value)
	Indicates whether to optimize the batch size (see eVision.EasyDeepLearning.EDeepLearningTool.BatchSize) to maximize the training and inference speed according to the engine, the device and the available memory.
int	_BatchSizeForMaximumInferenceSpeed__getter (self)
	\cond
int	_BatchSize__getter (self)
	\cond
	_BatchSize__setter (self, int value)
	Batch size.
float	_CurrentTrainingProgression__getter (self)
	\cond
int	_CurrentTrainingFinishedIterations__getter (self)
	\cond
int	_CurrentTrainingNumIterations__getter (self)
	\cond
int	_NumTrainedIterations__getter (self)
	\cond
int	_BestIteration__getter (self)
	\cond
int	_ImageCacheSize__getter (self)
	\cond
	_ImageCacheSize__setter (self, int value)
	Size in byte of the image cache.
str	_Path__getter (self)
	\cond
str	_InferenceModelPath__getter (self)
	\cond
str	_TrainingModelPath__getter (self)
	\cond
str	_SettingsPath__getter (self)
	\cond
int	_AutoSavePeriod__getter (self)
	\cond
	_AutoSavePeriod__setter (self, int value)
	Auto-save period.
eVision.EasyDeepLearning.EDeepLearningLearningRateType	_LearningRateType__getter (self)
	\cond
list[float]	_LearningRateParameters__getter (self)
	\cond
bool	_EnableDeterministicTraining__getter (self)
	\cond
	_EnableDeterministicTraining__setter (self, bool value)
	Whether to use deterministic training algorithm that allows to repeatable training results.
int	_DeterministicTrainingRandomSeed__getter (self)
	\cond
	_DeterministicTrainingRandomSeed__setter (self, int value)
	Random seed to use when eVision.EasyDeepLearning.EDeepLearningTool.EnableDeterministicTraining is set to true.
int	_NumLabels__getter (self)
	\cond

Properties
	ToolType = property(_ToolType__getter, None)
	\endcond
	Model = property(_Model__getter, _Model__setter)
	\endcond
	Parameters = property(_Parameters__getter, _Parameters__setter)
	\endcond
Properties inherited from eVision.EasyDeepLearning.EDeepLearningTool
	ToolType = property(_ToolType__getter, None)
	\endcond
	EnableGPU = property(_EnableGPU__getter, _EnableGPU__setter)
	\endcond
	GPUIndexes = property(_GPUIndexes__getter, _GPUIndexes__setter)
	\endcond
	NumGPUs = property(_NumGPUs__getter, None)
	\endcond
	Engine = property(_Engine__getter, _Engine__setter)
	\endcond
	InferencePrecision = property(_InferencePrecision__getter, _InferencePrecision__setter)
	\endcond
	NumAvailableDevices = property(_NumAvailableDevices__getter, None)
	\endcond
	AvailableDevices = property(_AvailableDevices__getter, None)
	\endcond
	NumActiveDevices = property(_NumActiveDevices__getter, None)
	\endcond
	ActiveDeviceByName = property(None, _ActiveDeviceByName__setter)
	\endcond
	ActiveDeviceById = property(None, _ActiveDeviceById__setter)
	\endcond
	ActiveDevices = property(_ActiveDevices__getter, _ActiveDevices__setter)
	\endcond
	ActiveDevicesById = property(None, _ActiveDevicesById__setter)
	\endcond
	ExecutionSettings = property(_ExecutionSettings__getter, _ExecutionSettings__setter)
	\endcond
	EngineSetupDataDevice = property(_EngineSetupDataDevice__getter, None)
	\endcond
	EngineSetupDataInferencePrecision = property(_EngineSetupDataInferencePrecision__getter, None)
	\endcond
	EngineSetupDataBatchSize = property(_EngineSetupDataBatchSize__getter, None)
	\endcond
	OptimizeBatchSize = property(_OptimizeBatchSize__getter, _OptimizeBatchSize__setter)
	\endcond
	BatchSizeForMaximumInferenceSpeed = property(_BatchSizeForMaximumInferenceSpeed__getter, None)
	\endcond
	BatchSize = property(_BatchSize__getter, _BatchSize__setter)
	\endcond
	CurrentTrainingProgression = property(_CurrentTrainingProgression__getter, None)
	\endcond
	CurrentTrainingFinishedIterations = property(_CurrentTrainingFinishedIterations__getter, None)
	\endcond
	CurrentTrainingNumIterations = property(_CurrentTrainingNumIterations__getter, None)
	\endcond
	NumTrainedIterations = property(_NumTrainedIterations__getter, None)
	\endcond
	BestIteration = property(_BestIteration__getter, None)
	\endcond
	ImageCacheSize = property(_ImageCacheSize__getter, _ImageCacheSize__setter)
	\endcond
	Path = property(_Path__getter, None)
	\endcond
	InferenceModelPath = property(_InferenceModelPath__getter, None)
	\endcond
	TrainingModelPath = property(_TrainingModelPath__getter, None)
	\endcond
	SettingsPath = property(_SettingsPath__getter, None)
	\endcond
	AutoSavePeriod = property(_AutoSavePeriod__getter, _AutoSavePeriod__setter)
	\endcond
	LearningRateType = property(_LearningRateType__getter, None)
	\endcond
	LearningRateParameters = property(_LearningRateParameters__getter, None)
	\endcond
	EnableDeterministicTraining = property(_EnableDeterministicTraining__getter, _EnableDeterministicTraining__setter)
	\endcond
	DeterministicTrainingRandomSeed = property(_DeterministicTrainingRandomSeed__getter, _DeterministicTrainingRandomSeed__setter)
	\endcond
	NumLabels = property(_NumLabels__getter, None)
	\endcond

Additional Inherited Members
Static Public Member Functions inherited from eVision.EasyDeepLearning.EDeepLearningTool
eVision.EasyDeepLearning.EDeepLearningTool|None	Create (str path)
	Factory method to open a deep learning tool.
eVision.EasyDeepLearning.EDeepLearningTool|None	Create (eVision.ESerializer|None serializer)
	Factory method to open a deep learning tool.
eVision.EasyDeepLearning.EDeepLearningTool|None	Create (eVision.EasyDeepLearning.EDeepLearningToolType type)
	Factory method to open a deep learning tool.
int	GetNumAvailableEngines ()
	Number of available engines.
str	GetAvailableEngineName (int id)
	Gets the name of the engine given its id.
list[str]	GetAvailableEngines ()
	Available engines.
list[eVision._eVision.EasyDeepLearning.EDeepLearningDevice]	GetAvailableDevicesForEngine (str engine)
	Available devices for the specified engine.

Detailed Description

Trains the EasyDeepOCR Deep Learning models.

Remarks:

License(s): EasyDeepOCR

Constructor & Destructor Documentation

__init__() [1/3]

None eVision.EasyDeepLearning.EDeepOCRTool.__init__

(

self

)

Constructs a eVision.EasyDeepLearning.EDeepOCRTool.

__init__() [2/3]

None eVision.EasyDeepLearning.EDeepOCRTool.__init__	(		self,
		eVision.EasyDeepLearning.EDeepOCRModel	model )

Constructs a eVision.EasyDeepLearning.EDeepOCRTool.

Parameters

model

The type of model to train.

__init__() [3/3]

None eVision.EasyDeepLearning.EDeepOCRTool.__init__	(		self,
		eVision.EasyDeepLearning.EDeepOCRTool	other )

Copy constructor of a eVision.EasyDeepLearning.EDeepOCRTool object.

Parameters

other

Reference to the eVision.EasyDeepLearning.EDeepOCRTool object that should be copied.

Member Function Documentation

_Model__getter()

eVision.EasyDeepLearning.EDeepOCRModel eVision.EasyDeepLearning.EDeepOCRTool._Model__getter ( self )

protected

\cond

Type of Deep OCR model to train and evaluate.

Throws an exception if the tool is already trained.

_Model__setter()

eVision.EasyDeepLearning.EDeepOCRTool._Model__setter ( self, eVision.EasyDeepLearning.EDeepOCRModel value )

protected

Type of Deep OCR model to train and evaluate.

Throws an exception if the tool is already trained.

_Parameters__getter()

eVision.EasyDeepLearning.EDeepOCRModelParameters | None eVision.EasyDeepLearning.EDeepOCRTool._Parameters__getter ( self )

protected

\cond

Parameters of the model.

_Parameters__setter()

eVision.EasyDeepLearning.EDeepOCRTool._Parameters__setter ( self, eVision.EasyDeepLearning.EDeepOCRModelParameters | None value )

protected

Parameters of the model.

_ToolType__getter()

eVision.EasyDeepLearning.EDeepLearningToolType eVision.EasyDeepLearning.EDeepOCRTool._ToolType__getter ( self )

protected

\cond

Type of the deep learning tool.

Reimplemented from eVision.EasyDeepLearning.EDeepLearningTool.

GetTrainingMetrics()

eVision.EasyDeepLearning.EDeepOCRToolMetrics eVision.EasyDeepLearning.EDeepOCRTool.GetTrainingMetrics	(		self,
		int	i )

Metrics on the training dataset at the specified iteration of the training.

Parameters

i	Iteration of the training

GetValidationMetrics()

eVision.EasyDeepLearning.EDeepOCRToolMetrics eVision.EasyDeepLearning.EDeepOCRTool.GetValidationMetrics	(		self,
		int	i )

Metrics on the validation dataset at the specified iteration of the training.

Parameters

i	Iteration of the training

SerializeSettings()

None eVision.EasyDeepLearning.EDeepOCRTool.SerializeSettings	(		self,
		eVision.ESerializer | None	serializer )

Serializes the eVision.EasyDeepLearning.EDeepOCRTool settings.

Parameters

serializer

Pointer to eVision.ESerializer.

Reimplemented from eVision.EasyDeepLearning.EDeepLearningTool.

Train() [1/8]

None eVision.EasyDeepLearning.EDeepOCRTool.Train	(		self,
		eVision.EasyDeepLearning.EDataset	dataset )

Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.

At the end of the training, the deep learning tool is in the state it was at the iteration that gave the minimum validation error. See eVision.EasyDeepLearning.EDeepLearningTool.BestIteration.

If no iterations is given, the training will stop automatically.

Remarks:

License(s): EasyDeepOCR

Parameters

dataset

eVision.EasyDeepLearning.EDataset with which to train and validate the deep learning tool

Train() [2/8]

None eVision.EasyDeepLearning.EDeepOCRTool.Train	(		self,
		eVision.EasyDeepLearning.EDataset	dataset,
		eVision.EasyDeepLearning.EDataAugmentation	dataAugmentation )

Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.

At the end of the training, the deep learning tool is in the state it was at the iteration that gave the minimum validation error. See eVision.EasyDeepLearning.EDeepLearningTool.BestIteration.

If no iterations is given, the training will stop automatically.

Remarks:

License(s): EasyDeepOCR

Parameters

dataset	eVision.EasyDeepLearning.EDataset with which to train and validate the deep learning tool
dataAugmentation	Data augmentation to use during training

Train() [3/8]

None eVision.EasyDeepLearning.EDeepOCRTool.Train	(		self,
		eVision.EasyDeepLearning.EDataset	dataset,
		eVision.EasyDeepLearning.EDataAugmentation	dataAugmentation,
		int	iterations )

Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.

At the end of the training, the deep learning tool is in the state it was at the iteration that gave the minimum validation error. See eVision.EasyDeepLearning.EDeepLearningTool.BestIteration.

If no iterations is given, the training will stop automatically.

Remarks:

License(s): EasyDeepOCR

Parameters

dataset	eVision.EasyDeepLearning.EDataset with which to train and validate the deep learning tool
dataAugmentation	Data augmentation to use during training
iterations	Number of iterations for training.

Train() [4/8]

None eVision.EasyDeepLearning.EDeepOCRTool.Train	(		self,
		eVision.EasyDeepLearning.EDataset	dataset,
		int	iterations )

Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.

At the end of the training, the deep learning tool is in the state it was at the iteration that gave the minimum validation error. See eVision.EasyDeepLearning.EDeepLearningTool.BestIteration.

If no iterations is given, the training will stop automatically.

Remarks:

License(s): EasyDeepOCR

Parameters

dataset	eVision.EasyDeepLearning.EDataset with which to train and validate the deep learning tool
iterations	Number of iterations for training.

Train() [5/8]

None eVision.EasyDeepLearning.EDeepOCRTool.Train	(		self,
		eVision.EasyDeepLearning.EDataset	trainingDataset,
		eVision.EasyDeepLearning.EDataset	validationDataset )

Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.

At the end of the training, the deep learning tool is in the state it was at the iteration that gave the minimum validation error. See eVision.EasyDeepLearning.EDeepLearningTool.BestIteration.

If no iterations is given, the training will stop automatically.

Remarks:

License(s): EasyDeepOCR

Parameters

trainingDataset	eVision.EasyDeepLearning.EDataset with which to train the deep learning tool
validationDataset	eVision.EasyDeepLearning.EDataset with which to validate the deep learning tool

Train() [6/8]

None eVision.EasyDeepLearning.EDeepOCRTool.Train	(		self,
		eVision.EasyDeepLearning.EDataset	trainingDataset,
		eVision.EasyDeepLearning.EDataset	validationDataset,
		eVision.EasyDeepLearning.EDataAugmentation	dataAugmentation )

Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.

At the end of the training, the deep learning tool is in the state it was at the iteration that gave the minimum validation error. See eVision.EasyDeepLearning.EDeepLearningTool.BestIteration.

If no iterations is given, the training will stop automatically.

Remarks:

License(s): EasyDeepOCR

Parameters

trainingDataset	eVision.EasyDeepLearning.EDataset with which to train the deep learning tool
validationDataset	eVision.EasyDeepLearning.EDataset with which to validate the deep learning tool
dataAugmentation	Data augmentation to use during training

Train() [7/8]

None eVision.EasyDeepLearning.EDeepOCRTool.Train	(		self,
		eVision.EasyDeepLearning.EDataset	trainingDataset,
		eVision.EasyDeepLearning.EDataset	validationDataset,
		eVision.EasyDeepLearning.EDataAugmentation	dataAugmentation,
		int	iterations )

Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.

At the end of the training, the deep learning tool is in the state it was at the iteration that gave the minimum validation error. See eVision.EasyDeepLearning.EDeepLearningTool.BestIteration.

If no iterations is given, the training will stop automatically.

Remarks:

License(s): EasyDeepOCR

Parameters

trainingDataset	eVision.EasyDeepLearning.EDataset with which to train the deep learning tool
validationDataset	eVision.EasyDeepLearning.EDataset with which to validate the deep learning tool
dataAugmentation	Data augmentation to use during training
iterations	Number of iterations for training.

Train() [8/8]

None eVision.EasyDeepLearning.EDeepOCRTool.Train	(		self,
		eVision.EasyDeepLearning.EDataset	trainingDataset,
		eVision.EasyDeepLearning.EDataset	validationDataset,
		int	iterations )

Trains the eVision.EasyDeepLearning.EDeepOCRTool with the given dataset for the specified number of iterations.

At the end of the training, the deep learning tool is in the state it was at the iteration that gave the minimum validation error. See eVision.EasyDeepLearning.EDeepLearningTool.BestIteration.

If no iterations is given, the training will stop automatically.

Remarks:

License(s): EasyDeepOCR

Parameters

trainingDataset	eVision.EasyDeepLearning.EDataset with which to train the deep learning tool
validationDataset	eVision.EasyDeepLearning.EDataset with which to validate the deep learning tool
iterations	Number of iterations for training.

Property Documentation

Model

eVision.EasyDeepLearning.EDeepOCRTool.Model = property(_Model__getter, _Model__setter)

static

\endcond

Type of Deep OCR model to train and evaluate.

Throws an exception if the tool is already trained.

Parameters

eVision.EasyDeepLearning.EDeepOCRTool.Parameters = property(_Parameters__getter, _Parameters__setter)

static

\endcond

Parameters of the model.

ToolType

eVision.EasyDeepLearning.EDeepOCRTool.ToolType = property(_ToolType__getter, None)

static

\endcond

Type of the deep learning tool.