Stores parameters used to apply transformation to the data layer's data. More...

Inheritance diagram for MyCaffe.param.TransformationParameter:

Public Types
enum	SCALE_OPERATOR { NONE , MUL , POW }
	Defines the type of scale operator to use (if any). More...

enum	COLOR_ORDER { RGB = 0 , BGR = 1 }
	Defines the color ordering used to tranform the input data. More...

Public Types inherited from MyCaffe.param.LayerParameterBase
enum	LABEL_TYPE { NONE , SINGLE , MULTIPLE , ONLY_ONE }
	Defines the label type. More...

Public Member Functions
	TransformationParameter ()
	The constructor. More...

override object	Load (System.IO.BinaryReader br, bool bNewInstance=true)
	Load the parameter from a binary reader. More...

override void	Copy (LayerParameterBase src)
	Copy on parameter to another. More...

override LayerParameterBase	Clone ()
	Creates a new copy of this instance of the parameter. More...

override RawProto	ToProto (string strName)
	Convert the parameter into a RawProto. More...

Public Member Functions inherited from MyCaffe.param.LayerParameterBase
	LayerParameterBase ()
	Constructor for the parameter. More...

virtual string	PrepareRunModelInputs ()
	This method gives derivative classes a chance specify model inputs required by the run model. More...

virtual void	PrepareRunModel (LayerParameter p)
	This method gives derivative classes a chance to prepare the layer for a run-model. More...

void	Save (BinaryWriter bw)
	Save this parameter to a binary writer. More...

abstract object	Load (BinaryReader br, bool bNewInstance=true)
	Load the parameter from a binary reader. More...

Public Member Functions inherited from MyCaffe.basecode.BaseParameter
	BaseParameter ()
	Constructor for the parameter. More...

virtual bool	Compare (BaseParameter p)
	Compare this parameter to another parameter. More...

Static Public Member Functions
static TransformationParameter	FromProto (RawProto rp)
	Parses the parameter from a RawProto. More...

Static Public Member Functions inherited from MyCaffe.basecode.BaseParameter
static double	ParseDouble (string strVal)
	Parse double values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static bool	TryParse (string strVal, out double df)
	Parse double values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static float	ParseFloat (string strVal)
	Parse float values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static bool	TryParse (string strVal, out float f)
	Parse doufloatble values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

Properties
double	forced_positive_range_max `[getset]`
	Specifies whether or not to fit the data into a forced range of [0, forced_positive_range_max]. More...

double	scale `[getset]`
	For data pre-processing, we can do simple scaling and subtracting the data mean, if provided. Note that the mean subtraction is always carried out before scaling. More...

SCALE_OPERATOR?	scale_operator `[getset]`
	Get/set the scale operator used to apply the scale value to the data-mean or data result. More...

bool	mirror `[getset]`
	Specify if we want to randomly mirror the data. More...

uint	crop_size `[getset]`
	Specify if we would like to randomly crop an image. More...

bool	use_imagedb_mean `[getset]`
	Specifies whether to subtract the mean image from the image database, subtract the mean values, or neither and do no mean subtraction. More...

List< double >	mean_value `[getset]`
	If specified can be repeated once (would subtract it from all the channels or can be repeated the same number of times as channels (would subtract them from the corresponding channel). More...

bool	force_color `[getset]`
	Force the decoded image to have 3 color channels. More...

bool	force_gray `[getset]`
	Force the decoded image to have 1 color channel. More...

int?	random_seed `[getset]`
	Only used during testing. More...

string	mean_file `[getset]`
	Specifies the path to file containing the image mean in the proto buffer format of a BlobProto. More...

COLOR_ORDER	color_order `[getset]`
	Specifies the color ordering to use. Native Caffe models often uses COLOR_ORDER.BGR, whereas MyCaffe datasets often uses the COLOR_ORDER.RGB ordering. More...

ResizeParameter	resize_param `[getset]`
	Optionally, specifies the resize policy, otherwise this is null. More...

NoiseParameter	noise_param `[getset]`
	Optionally, specifies the noise policy, otherwise this is null. More...

DistortionParameter	distortion_param `[getset]`
	Optionally, specifies the distortion policy, otherwise this is null. More...

ExpansionParameter	expansion_param `[getset]`
	Optionally, specifies the expansion policy, otherwise this is null. More...

EmitConstraint	emit_constraint `[getset]`
	Optionally, specifies the emit constraint on emitting annotation after transformation, otherwise this is null. More...

MaskParameter	mask_param `[getset]`
	Optionally, specifies the image mask which defines the boundary area that is set to black on the image thus masking that area out. More...

DataLabelMappingParameter	label_mapping `[getset]`
	Optionally, specifies the label mapping which defines how to map lables when calling the DataTransformer.TransformLabel method. More...

Detailed Description

Stores parameters used to apply transformation to the data layer's data.

Definition at line 18 of file TransformationParameter.cs.

Member Enumeration Documentation

◆ COLOR_ORDER

enum MyCaffe.param.TransformationParameter.COLOR_ORDER

Defines the color ordering used to tranform the input data.

Enumerator
RGB	Orders the channels by 'R'ed, 'G'reen, then 'B'lue.
BGR	Orders the channels by 'B'lue, 'G'reen, then 'R'ed. This ordering is typically used by Native C++ Caffe.

Definition at line 62 of file TransformationParameter.cs.

◆ SCALE_OPERATOR

enum MyCaffe.param.TransformationParameter.SCALE_OPERATOR

Defines the type of scale operator to use (if any).

Enumerator
NONE	Specifies to not scale the data.
MUL	Specifies to use the multiplication operator where the scale is multiplied by the result of the data-mean.
POW	Specifies to use the power operator where the data-mean is raised to the power of the scale value.

Definition at line 43 of file TransformationParameter.cs.

Constructor & Destructor Documentation

◆ TransformationParameter()

MyCaffe.param.TransformationParameter.TransformationParameter ( )

The constructor.

Definition at line 77 of file TransformationParameter.cs.

Member Function Documentation

◆ Clone()

override LayerParameterBase MyCaffe.param.TransformationParameter.Clone ( )

virtual

Creates a new copy of this instance of the parameter.

Returns: A new instance of this parameter is returned.

Implements MyCaffe.param.LayerParameterBase.

Definition at line 352 of file TransformationParameter.cs.

◆ Copy()

override void MyCaffe.param.TransformationParameter.Copy ( LayerParameterBase src )

virtual

Copy on parameter to another.

Parameters

src	Specifies the parameter to copy.

Implements MyCaffe.param.LayerParameterBase.

Definition at line 321 of file TransformationParameter.cs.

◆ FromProto()

static TransformationParameter MyCaffe.param.TransformationParameter.FromProto ( RawProto rp )

static

Parses the parameter from a RawProto.

Parameters

rp	Specifies the RawProto to parse.

Returns: A new instance of the parameter is returned.

Definition at line 428 of file TransformationParameter.cs.

◆ Load()

override object MyCaffe.param.TransformationParameter.Load	(	System.IO.BinaryReader	br,
		bool	bNewInstance = `true`
	)

Load the parameter from a binary reader.

Parameters

br	Specifies the binary reader.
bNewInstance	When true a new instance is created (the default), otherwise the existing instance is loaded from the binary reader.

Returns: Returns an instance of the parameter.

Definition at line 309 of file TransformationParameter.cs.

◆ ToProto()

override RawProto MyCaffe.param.TransformationParameter.ToProto ( string strName )

virtual

Convert the parameter into a RawProto.

Parameters

strName Specifies the name to associate with the RawProto.

Returns: The new RawProto is returned.

Implements MyCaffe.basecode.BaseParameter.

Definition at line 364 of file TransformationParameter.cs.

Property Documentation

◆ color_order

COLOR_ORDER MyCaffe.param.TransformationParameter.color_order

getset

Specifies the color ordering to use. Native Caffe models often uses COLOR_ORDER.BGR, whereas MyCaffe datasets often uses the COLOR_ORDER.RGB ordering.

Definition at line 210 of file TransformationParameter.cs.

◆ crop_size

uint MyCaffe.param.TransformationParameter.crop_size

getset

Specify if we would like to randomly crop an image.

Definition at line 127 of file TransformationParameter.cs.

◆ distortion_param

DistortionParameter MyCaffe.param.TransformationParameter.distortion_param

getset

Optionally, specifies the distortion policy, otherwise this is null.

Currently, this parameter is only used by the AnnotatedDataLayer.

Definition at line 249 of file TransformationParameter.cs.

◆ emit_constraint

EmitConstraint MyCaffe.param.TransformationParameter.emit_constraint

getset

Optionally, specifies the emit constraint on emitting annotation after transformation, otherwise this is null.

Currently, this parameter is only used by the AnnotatedDataLayer.

Definition at line 275 of file TransformationParameter.cs.

◆ expansion_param

ExpansionParameter MyCaffe.param.TransformationParameter.expansion_param

getset

Optionally, specifies the expansion policy, otherwise this is null.

Currently, this parameter is only used by the AnnotatedDataLayer.

Definition at line 262 of file TransformationParameter.cs.

◆ force_color

bool MyCaffe.param.TransformationParameter.force_color

getset

Force the decoded image to have 3 color channels.

Definition at line 165 of file TransformationParameter.cs.

◆ force_gray

bool MyCaffe.param.TransformationParameter.force_gray

getset

Force the decoded image to have 1 color channel.

Definition at line 175 of file TransformationParameter.cs.

◆ forced_positive_range_max

double MyCaffe.param.TransformationParameter.forced_positive_range_max

getset

Specifies whether or not to fit the data into a forced range of [0, forced_positive_range_max].

Definition at line 86 of file TransformationParameter.cs.

◆ label_mapping

DataLabelMappingParameter MyCaffe.param.TransformationParameter.label_mapping

getset

Optionally, specifies the label mapping which defines how to map lables when calling the DataTransformer.TransformLabel method.

Currently, this parameter is only used by the DataLayer.

Definition at line 302 of file TransformationParameter.cs.

◆ mask_param

MaskParameter MyCaffe.param.TransformationParameter.mask_param

getset

Optionally, specifies the image mask which defines the boundary area that is set to black on the image thus masking that area out.

The mask is applied last, after all other alterations are made.

Currently, this parameter is only used by the DataLayer.

Definition at line 290 of file TransformationParameter.cs.

◆ mean_file

string MyCaffe.param.TransformationParameter.mean_file

getset

Specifies the path to file containing the image mean in the proto buffer format of a BlobProto.

The mean file is used when specified and the 'use_imagedb_mean' = true. If the 'use_imagedb_mean' = true and the mean file is not set, the Caffe Image Database is queried for the calculated mean image.

Definition at line 199 of file TransformationParameter.cs.

◆ mean_value

List<double> MyCaffe.param.TransformationParameter.mean_value

getset

If specified can be repeated once (would subtract it from all the channels or can be repeated the same number of times as channels (would subtract them from the corresponding channel).

So for example if there are 3 channels, mean_value could have 3 values, one for each channel – or just one value which would be applied to all channels.

Definition at line 155 of file TransformationParameter.cs.

◆ mirror

bool MyCaffe.param.TransformationParameter.mirror

getset

Specify if we want to randomly mirror the data.

Definition at line 117 of file TransformationParameter.cs.

◆ noise_param

NoiseParameter MyCaffe.param.TransformationParameter.noise_param

getset

Optionally, specifies the noise policy, otherwise this is null.

Currently, this parameter is only used by the DataLayer.

Definition at line 236 of file TransformationParameter.cs.

◆ random_seed

int? MyCaffe.param.TransformationParameter.random_seed

getset

Only used during testing.

Definition at line 185 of file TransformationParameter.cs.

◆ resize_param

ResizeParameter MyCaffe.param.TransformationParameter.resize_param

getset

Optionally, specifies the resize policy, otherwise this is null.

Currently, this parameter is only used by the AnnotatedDataLayer.

Definition at line 223 of file TransformationParameter.cs.

◆ scale

double MyCaffe.param.TransformationParameter.scale

getset

For data pre-processing, we can do simple scaling and subtracting the data mean, if provided. Note that the mean subtraction is always carried out before scaling.

Definition at line 98 of file TransformationParameter.cs.

◆ scale_operator

SCALE_OPERATOR? MyCaffe.param.TransformationParameter.scale_operator

getset

Get/set the scale operator used to apply the scale value to the data-mean or data result.

Definition at line 107 of file TransformationParameter.cs.

◆ use_imagedb_mean

bool MyCaffe.param.TransformationParameter.use_imagedb_mean

getset

Specifies whether to subtract the mean image from the image database, subtract the mean values, or neither and do no mean subtraction.

Definition at line 138 of file TransformationParameter.cs.

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

C:/Data/Data/SS_Projects/Intelligence/GitHub/MyCaffe/MyCaffe/param/TransformationParameter.cs

Public Types

Public Member Functions

Static Public Member Functions

Properties

Detailed Description

Member Enumeration Documentation

◆ COLOR_ORDER

◆ SCALE_OPERATOR

Constructor & Destructor Documentation

◆ TransformationParameter()

Member Function Documentation

◆ Clone()

◆ Copy()

◆ FromProto()

◆ Load()

◆ ToProto()

Property Documentation

◆ color_order

◆ crop_size

◆ distortion_param

◆ emit_constraint

◆ expansion_param

◆ force_color

◆ force_gray

◆ forced_positive_range_max

◆ label_mapping

◆ mask_param

◆ mean_file

◆ mean_value

◆ mirror

◆ noise_param

◆ random_seed

◆ resize_param

◆ scale

◆ scale_operator

◆ use_imagedb_mean