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.
eVision.EasyDeepLearning.EDeepLearningToolType	ToolType (self)
	Type of the deep learning tool.
eVision.EasyDeepLearning.EDeepOCRModel	Model (self)
	Type of Deep OCR model to train and evaluate.
	Model (self, eVision.EasyDeepLearning.EDeepOCRModel value)
	Type of Deep OCR model to train and evaluate.
eVision.EasyDeepLearning.EDeepOCRModelParameters|None	Parameters (self)
	Parameters of the model.
	Parameters (self, eVision.EasyDeepLearning.EDeepOCRModelParameters|None value)
	Parameters of the model.
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.
bool	EnableGPU (self)
	Enable the use of a GPU for training and inference of the deep learning tool.
	EnableGPU (self, bool value)
	Enable the use of a GPU for training and inference of the deep learning tool.
list[int]	GPUIndexes (self)
	Indexes of the GPUs to use for computations.
	GPUIndexes (self, list[int] value)
	Indexes of the GPUs to use for computations.
int	NumGPUs (self)
	Number of detected NVIDIA GPU.
str	Engine (self)
	Sets the engine with which to execute or train the neural network.
	Engine (self, str value)
	Sets the engine with which to execute or train the neural network.
eVision.EasyDeepLearning.EDeepLearningInferencePrecision	InferencePrecision (self)
	Inference precision.
	InferencePrecision (self, eVision.EasyDeepLearning.EDeepLearningInferencePrecision value)
	Inference precision.
int	NumAvailableDevices (self)
	Available devices for the current eVision.EasyDeepLearning.EDeepLearningTool.Engine.
list[eVision._eVision.EasyDeepLearning.EDeepLearningDevice]	AvailableDevices (self)
	Get all available device for the current engine.
int	NumActiveDevices (self)
	Gets the number of devices with which to run or train the model.
list[eVision._eVision.EasyDeepLearning.EDeepLearningDevice]	ActiveDevices (self)
	Devices with which to run or train the model.
	ActiveDevices (self, list[eVision._eVision.EasyDeepLearning.EDeepLearningDevice] value)
	Devices with which to run or train the model.
eVision.EasyDeepLearning.EDeepLearningExecutionSettings	ExecutionSettings (self)
	Execution settings of the tool (engine, device(s), inference precision, batch size settings).
	ExecutionSettings (self, eVision.EasyDeepLearning.EDeepLearningExecutionSettings value)
	Execution settings of the tool (engine, device(s), inference precision, batch size settings).
eVision.EasyDeepLearning.EDeepLearningDevice	EngineSetupDataDevice (self)
	Device corresponding to the engine data contained in the tool.
eVision.EasyDeepLearning.EDeepLearningInferencePrecision	EngineSetupDataInferencePrecision (self)
	Inference precision corresponding to the engine data contained in the tool.
int	EngineSetupDataBatchSize (self)
	Batch size corresponding to the engine data contained in the tool.
bool	OptimizeBatchSize (self)
	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.
	OptimizeBatchSize (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 (self)
	Computes the batch size that will maximize the inference speed on NVIDIA GPU.
int	BatchSize (self)
	Batch size.
	BatchSize (self, int value)
	Batch size.
float	CurrentTrainingProgression (self)
	Current training progression as a percentage (between 0 and 1).
int	CurrentTrainingFinishedIterations (self)
	Number of iterations that are already finished in the current training.
int	CurrentTrainingNumIterations (self)
	Total number of training iterations that will be performed during the current training of the deep learning tool.
int	NumTrainedIterations (self)
	Number of iterations that were performed to train this deep learning tool.
int	BestIteration (self)
	Iteration at which the minimum validation error was reached.
int	ImageCacheSize (self)
	Size in byte of the image cache.
	ImageCacheSize (self, int value)
	Size in byte of the image cache.
str	Path (self)
	Path of the tool when loaded or saved using eVision.EasyDeepLearning.EDeepLearningTool.Save or eVision.EasyDeepLearning.EDeepLearningTool.Load.
str	InferenceModelPath (self)
	Path of the inference model when loaded or saved using eVision.EasyDeepLearning.EDeepLearningTool.SaveInferenceModel, eVision.EasyDeepLearning.EDeepLearningTool.LoadInferenceModel or eVision.EasyDeepLearning.EDeepLearningTool.SerializeInferenceModel.
str	TrainingModelPath (self)
	Path of the training model when loaded or saved using eVision.EasyDeepLearning.EDeepLearningTool.SaveTrainingModel, eVision.EasyDeepLearning.EDeepLearningTool.LoadTrainingModel or eVision.EasyDeepLearning.EDeepLearningTool.SerializeTrainingModel.
str	SettingsPath (self)
	Path of the settings when loaded or saved using eVision.EasyDeepLearning.EDeepLearningTool.SaveSettings, eVision.EasyDeepLearning.EDeepLearningTool.LoadSettings or eVision.EasyDeepLearning.EDeepLearningTool.SerializeSettings.
int	AutoSavePeriod (self)
	Auto-save period.
	AutoSavePeriod (self, int value)
	Auto-save period.
eVision.EasyDeepLearning.EDeepLearningLearningRateType	LearningRateType (self)
	Learning rate type.
list[float]	LearningRateParameters (self)
	Parameters of the learning rate.
bool	EnableDeterministicTraining (self)
	Whether to use deterministic training algorithm that allows to repeatable training results.
	EnableDeterministicTraining (self, bool value)
	Whether to use deterministic training algorithm that allows to repeatable training results.
int	DeterministicTrainingRandomSeed (self)
	Random seed to use when eVision.EasyDeepLearning.EDeepLearningTool.EnableDeterministicTraining is set to true.
	DeterministicTrainingRandomSeed (self, int value)
	Random seed to use when eVision.EasyDeepLearning.EDeepLearningTool.EnableDeterministicTraining is set to true.
int	NumLabels (self)
	Number of labels of this tool.

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.
Protected Member Functions inherited from eVision.EasyDeepLearning.EDeepLearningTool
	_ActiveDeviceByName__setter (self, str value)
	Sets the device with which to run the model using its name.
	_ActiveDeviceById__setter (self, int value)
	Sets the device with which to run the model using its index in the list returned by eVision.EasyDeepLearning.EDeepLearningTool.AvailableDevices.
	_ActiveDevicesById__setter (self, list[int] value)
	Sets the devices with which to run the model using their index in the list returned by eVision.EasyDeepLearning.EDeepLearningTool.AvailableDevices.
Properties inherited from eVision.EasyDeepLearning.EDeepLearningTool
	ActiveDeviceByName
	ActiveDeviceById
	ActiveDevicesById

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

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

Model() [1/2]

eVision.EasyDeepLearning.EDeepOCRModel eVision.EasyDeepLearning.EDeepOCRTool.Model

(

self

)

Type of Deep OCR model to train and evaluate.

Throws an exception if the tool is already trained.

Model() [2/2]

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

Type of Deep OCR model to train and evaluate.

Throws an exception if the tool is already trained.

Parameters() [1/2]

eVision.EasyDeepLearning.EDeepOCRModelParameters | None eVision.EasyDeepLearning.EDeepOCRTool.Parameters

(

self

)

Parameters of the model.

Parameters() [2/2]

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

Parameters of the model.

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.

ToolType()

eVision.EasyDeepLearning.EDeepLearningToolType eVision.EasyDeepLearning.EDeepOCRTool.ToolType

(

self

)

Type of the deep learning tool.

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.