An eVision.EasyDeepLearning.EDataAugmentation object is responsible for storing the data augmentation parameters and generating new transformed images from existing ones. More...

Public Member Functions
None	__init__ (self)
	Creates an eVision.EasyDeepLearning.EDataAugmentation object.
None	__init__ (self, eVision.EasyDeepLearning.EDataAugmentation other)
	Creates a copy of the eVision.EasyDeepLearning.EDataAugmentation object other.
None	CopyTo (self, eVision.EasyDeepLearning.EDataAugmentation other)
	Copies itself to the eVision.EasyDeepLearning.EDataAugmentation object other.
None	Load (self, str path)
	Loads an eVision.EasyDeepLearning.EDataAugmentation object.
None	Load (self, eVision.ESerializer\|None serializer)
	Loads an eVision.EasyDeepLearning.EDataAugmentation object.
None	Save (self, str path)
	Saves an eVision.EasyDeepLearning.EDataAugmentation object.
None	Save (self, eVision.ESerializer\|None serializer)
	Saves an eVision.EasyDeepLearning.EDataAugmentation object.
bool	HasDataAugmentations (self)
	Whether the eVision.EasyDeepLearning.EDataAugmentation object contains augmentations.
eVision.EBaseROI\|None	Generate (self, eVision.EBaseROI\|None img, eVision.EasyDeepLearning.EDLDataAugmentationType type)
	Generates a new image from a generic eVision.EBaseROI image.
eVision.EBaseROI\|None	Generate (self, eVision.EBaseROI\|None img)
	Generates a new image from a generic eVision.EBaseROI image.
None	Generate (self, eVision.EROIBW8 source, eVision.EROIBW8 dest, eVision.EasyDeepLearning.EDLDataAugmentationType type)
	Generates a new image.
None	Generate (self, eVision.EROIBW8 source, eVision.EROIBW8 dest)
	Generates a new image.
None	Generate (self, eVision.EROIBW16 source, eVision.EROIBW16 dest, eVision.EasyDeepLearning.EDLDataAugmentationType type)
	Generates a new image.
None	Generate (self, eVision.EROIBW16 source, eVision.EROIBW16 dest)
	Generates a new image.
None	Generate (self, eVision.EROIC24 source, eVision.EROIC24 dest, eVision.EasyDeepLearning.EDLDataAugmentationType type)
	Generates a new image.
None	Generate (self, eVision.EROIC24 source, eVision.EROIC24 dest)
	Generates a new image.

Protected Member Functions
int	_MaxHorizontalShift__getter (self)
	\cond
	_MaxHorizontalShift__setter (self, int value)
	Return the maximum horizontal shift allowed.
int	_MaxVerticalShift__getter (self)
	\cond
	_MaxVerticalShift__setter (self, int value)
	Return the maximum vertical shift allowed.
float	_MaxRotationAngle__getter (self)
	\cond
	_MaxRotationAngle__setter (self, float value)
	Returns the maximum rotation angle allowed.
bool	_EnableVerticalFlip__getter (self)
	\cond
	_EnableVerticalFlip__setter (self, bool value)
	Gets whether to use vertically flipped versions of input images.
bool	_EnableHorizontalFlip__getter (self)
	\cond
	_EnableHorizontalFlip__setter (self, bool value)
	Gets whether to use horizontally flipped versions of input images.
float	_MinScale__getter (self)
	\cond
	_MinScale__setter (self, float value)
	Gets the minimum scaling allowed.
float	_MaxScale__getter (self)
	\cond
	_MaxScale__setter (self, float value)
	Gets the maximum scaling allowed.
float	_MaxHorizontalShear__getter (self)
	\cond
	_MaxHorizontalShear__setter (self, float value)
	Gets the maximum absolute horizontal shear, represented as an angle from the vertical direction.
float	_MaxVerticalShear__getter (self)
	\cond
	_MaxVerticalShear__setter (self, float value)
	Gets the maximum absolute vertical shear, represented as an angle from the horizontal direction.
float	_MaxBrightnessOffset__getter (self)
	\cond
	_MaxBrightnessOffset__setter (self, float value)
	Gets the maximum absolute brightness offset.
float	_MaxContrastGain__getter (self)
	\cond
	_MaxContrastGain__setter (self, float value)
	Gets the maximum contrast gain.
float	_MinContrastGain__getter (self)
	\cond
	_MinContrastGain__setter (self, float value)
	Gets the minimum contrast gain.
float	_MinGamma__getter (self)
	\cond
	_MinGamma__setter (self, float value)
	Gets the minimum gamma for gamma correction.
float	_MaxGamma__getter (self)
	\cond
	_MaxGamma__setter (self, float value)
	Gets the maximum gamma for gamma correction.
float	_MaxHueOffset__getter (self)
	\cond
	_MaxHueOffset__setter (self, float value)
	Gets the maximum absolute hue offset.
float	_MinSaturationGain__getter (self)
	\cond
	_MinSaturationGain__setter (self, float value)
	Gets the minimum saturation gain.
float	_MaxSaturationGain__getter (self)
	\cond
	_MaxSaturationGain__setter (self, float value)
	Gets the maximum saturation gain.
float	_GaussianNoiseMaximumStandardDeviation__getter (self)
	\cond
	_GaussianNoiseMaximumStandardDeviation__setter (self, float value)
	The Gaussian noise maximum standard deviation.
float	_GaussianNoiseMinimumStandardDeviation__getter (self)
	\cond
	_GaussianNoiseMinimumStandardDeviation__setter (self, float value)
	The Gaussian noise minimum standard deviation.
float	_SpeckleNoiseMaximumStandardDeviation__getter (self)
	\cond
	_SpeckleNoiseMaximumStandardDeviation__setter (self, float value)
	The speckle noise maximum standard deviation.
float	_SpeckleNoiseMinimumStandardDeviation__getter (self)
	\cond
	_SpeckleNoiseMinimumStandardDeviation__setter (self, float value)
	The speckle noise minimum standard deviation.
float	_SaltAndPepperNoiseMaximumDensity__getter (self)
	\cond
	_SaltAndPepperNoiseMaximumDensity__setter (self, float value)
	The maximum density of the salt and pepper noise.
float	_SaltAndPepperNoiseMinimumDensity__getter (self)
	\cond
	_SaltAndPepperNoiseMinimumDensity__setter (self, float value)
	The minimum density of the salt and pepper noise.
int	_StainDisruptionMaxAnchorPoints__getter (self)
	\cond
	_StainDisruptionMaxAnchorPoints__setter (self, int value)
	The maximum number of anchor points to use while disrupting the ellipse.
float	_StainDisruptionMaxIntensity__getter (self)
	\cond
	_StainDisruptionMaxIntensity__setter (self, float value)
	The maximum offset applied to the coordinates (x,y) of a pixel from the ellipse contour.
int	_StainEllipseMinRadius__getter (self)
	\cond
	_StainEllipseMinRadius__setter (self, int value)
	The minimum radius of the ellipse used to produce the stain.
int	_StainEllipseMaxRadius__getter (self)
	\cond
	_StainEllipseMaxRadius__setter (self, int value)
	The maximum radius of the ellipse used to produce the stain.
int	_MinStainColor__getter (self)
	\cond
	_MinStainColor__setter (self, int value)
	The minimum color value from which to draw a color to fill in the stain (we use a gaussian distribution of with a mean between eVision.EasyDeepLearning.EDataAugmentation.MinStainColor and eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor).
int	_MaxStainColor__getter (self)
	\cond
	_MaxStainColor__setter (self, int value)
	The maximum color value from which to draw a color to fill in the stain (we use a gaussian distribution of with a mean between eVision.EasyDeepLearning.EDataAugmentation.MinStainColor and eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor).
int	_StainColorVariation__getter (self)
	\cond
	_StainColorVariation__setter (self, int value)
	The variation of the color used to fill in the ellipse (We use an gaussian distribution of standard mean deviation stainColorVariation).
float	_StainInterpolationSiteFactor__getter (self)
	\cond
	_StainInterpolationSiteFactor__setter (self, float value)
	The factor to compute the number of interpolation sites to use from the number of anchor points.
float	_StainProbability__getter (self)
	\cond
	_StainProbability__setter (self, float value)
	Probability of applying the stain data augmentation (default value: 0, i.e.
int	_StainBlur__getter (self)
	\cond
	_StainBlur__setter (self, int value)
	Stain blur.

Properties
	MaxHorizontalShift = property(_MaxHorizontalShift__getter, _MaxHorizontalShift__setter)
	\endcond
	MaxVerticalShift = property(_MaxVerticalShift__getter, _MaxVerticalShift__setter)
	\endcond
	MaxRotationAngle = property(_MaxRotationAngle__getter, _MaxRotationAngle__setter)
	\endcond
	EnableVerticalFlip = property(_EnableVerticalFlip__getter, _EnableVerticalFlip__setter)
	\endcond
	EnableHorizontalFlip = property(_EnableHorizontalFlip__getter, _EnableHorizontalFlip__setter)
	\endcond
	MinScale = property(_MinScale__getter, _MinScale__setter)
	\endcond
	MaxScale = property(_MaxScale__getter, _MaxScale__setter)
	\endcond
	MaxHorizontalShear = property(_MaxHorizontalShear__getter, _MaxHorizontalShear__setter)
	\endcond
	MaxVerticalShear = property(_MaxVerticalShear__getter, _MaxVerticalShear__setter)
	\endcond
	MaxBrightnessOffset = property(_MaxBrightnessOffset__getter, _MaxBrightnessOffset__setter)
	\endcond
	MaxContrastGain = property(_MaxContrastGain__getter, _MaxContrastGain__setter)
	\endcond
	MinContrastGain = property(_MinContrastGain__getter, _MinContrastGain__setter)
	\endcond
	MinGamma = property(_MinGamma__getter, _MinGamma__setter)
	\endcond
	MaxGamma = property(_MaxGamma__getter, _MaxGamma__setter)
	\endcond
	MaxHueOffset = property(_MaxHueOffset__getter, _MaxHueOffset__setter)
	\endcond
	MinSaturationGain = property(_MinSaturationGain__getter, _MinSaturationGain__setter)
	\endcond
	MaxSaturationGain = property(_MaxSaturationGain__getter, _MaxSaturationGain__setter)
	\endcond
	GaussianNoiseMaximumStandardDeviation = property(_GaussianNoiseMaximumStandardDeviation__getter, _GaussianNoiseMaximumStandardDeviation__setter)
	\endcond
	GaussianNoiseMinimumStandardDeviation = property(_GaussianNoiseMinimumStandardDeviation__getter, _GaussianNoiseMinimumStandardDeviation__setter)
	\endcond
	SpeckleNoiseMaximumStandardDeviation = property(_SpeckleNoiseMaximumStandardDeviation__getter, _SpeckleNoiseMaximumStandardDeviation__setter)
	\endcond
	SpeckleNoiseMinimumStandardDeviation = property(_SpeckleNoiseMinimumStandardDeviation__getter, _SpeckleNoiseMinimumStandardDeviation__setter)
	\endcond
	SaltAndPepperNoiseMaximumDensity = property(_SaltAndPepperNoiseMaximumDensity__getter, _SaltAndPepperNoiseMaximumDensity__setter)
	\endcond
	SaltAndPepperNoiseMinimumDensity = property(_SaltAndPepperNoiseMinimumDensity__getter, _SaltAndPepperNoiseMinimumDensity__setter)
	\endcond
	StainDisruptionMaxAnchorPoints = property(_StainDisruptionMaxAnchorPoints__getter, _StainDisruptionMaxAnchorPoints__setter)
	\endcond
	StainDisruptionMaxIntensity = property(_StainDisruptionMaxIntensity__getter, _StainDisruptionMaxIntensity__setter)
	\endcond
	StainEllipseMinRadius = property(_StainEllipseMinRadius__getter, _StainEllipseMinRadius__setter)
	\endcond
	StainEllipseMaxRadius = property(_StainEllipseMaxRadius__getter, _StainEllipseMaxRadius__setter)
	\endcond
	MinStainColor = property(_MinStainColor__getter, _MinStainColor__setter)
	\endcond
	MaxStainColor = property(_MaxStainColor__getter, _MaxStainColor__setter)
	\endcond
	StainColorVariation = property(_StainColorVariation__getter, _StainColorVariation__setter)
	\endcond
	StainInterpolationSiteFactor = property(_StainInterpolationSiteFactor__getter, _StainInterpolationSiteFactor__setter)
	\endcond
	StainProbability = property(_StainProbability__getter, _StainProbability__setter)
	\endcond
	StainBlur = property(_StainBlur__getter, _StainBlur__setter)
	\endcond

Detailed Description

An eVision.EasyDeepLearning.EDataAugmentation object is responsible for storing the data augmentation parameters and generating new transformed images from existing ones.

Deep learning algorithms are not invariant to the location, scale, or rotation of the elements of interest in the image. Thus, if the final application requires the deep learning algorithm to be invariant to those characteristics, the dataset must contain images covering the spectrum of those characteristics.

Data augmentation can be used to avoid capturing in the original dataset the whole spectrum of those characteristics by automatically generating new versions of the images in the dataset that are shifted, scaled or rotated to cover this spectrum.

When generating a new image, the eVision.EasyDeepLearning.EDataAugmentation will randomly pick transformation value within the specified limits.

When using data augmentation, one must carefully chose the spectrum of transformations such that the element of interest are still visible in the image.

Remarks:

License(s): EasyClassify or EasySegment or EasyLocate

Constructor & Destructor Documentation

◆ init() [1/2]

None eVision.EasyDeepLearning.EDataAugmentation.__init__ ( self )

Creates an eVision.EasyDeepLearning.EDataAugmentation object.

◆ init() [2/2]

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

Creates a copy of the eVision.EasyDeepLearning.EDataAugmentation object other.

Parameters

other The other eVision.EasyDeepLearning.EDataAugmentation that we will copy into this one.

Member Function Documentation

◆ _EnableHorizontalFlip__getter()

bool eVision.EasyDeepLearning.EDataAugmentation._EnableHorizontalFlip__getter ( self )

protected

\cond

Gets whether to use horizontally flipped versions of input images.

◆ _EnableHorizontalFlip__setter()

eVision.EasyDeepLearning.EDataAugmentation._EnableHorizontalFlip__setter	(		self,
		bool	value )

protected

Gets whether to use horizontally flipped versions of input images.

◆ _EnableVerticalFlip__getter()

bool eVision.EasyDeepLearning.EDataAugmentation._EnableVerticalFlip__getter ( self )

protected

\cond

Gets whether to use vertically flipped versions of input images.

◆ _EnableVerticalFlip__setter()

eVision.EasyDeepLearning.EDataAugmentation._EnableVerticalFlip__setter	(		self,
		bool	value )

protected

Gets whether to use vertically flipped versions of input images.

◆ _GaussianNoiseMaximumStandardDeviation__getter()

float eVision.EasyDeepLearning.EDataAugmentation._GaussianNoiseMaximumStandardDeviation__getter ( self )

protected

\cond

The Gaussian noise maximum standard deviation.

The Gaussian noise is an additive noise sampled from a Gaussian distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMaximumStandardDeviation.(also called the normal distribution).

Its value must be superior or equal to eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMinimumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ _GaussianNoiseMaximumStandardDeviation__setter()

eVision.EasyDeepLearning.EDataAugmentation._GaussianNoiseMaximumStandardDeviation__setter	(		self,
		float	value )

protected

The Gaussian noise maximum standard deviation.

The Gaussian noise is an additive noise sampled from a Gaussian distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMaximumStandardDeviation.(also called the normal distribution).

Its value must be superior or equal to eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMinimumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ _GaussianNoiseMinimumStandardDeviation__getter()

float eVision.EasyDeepLearning.EDataAugmentation._GaussianNoiseMinimumStandardDeviation__getter ( self )

protected

\cond

The Gaussian noise minimum standard deviation.

The Gaussian noise is an additive noise sampled from a Gaussian distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMaximumStandardDeviation.(also called the normal distribution).

Its value must be between 0 and eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMaximumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ _GaussianNoiseMinimumStandardDeviation__setter()

eVision.EasyDeepLearning.EDataAugmentation._GaussianNoiseMinimumStandardDeviation__setter	(		self,
		float	value )

protected

The Gaussian noise minimum standard deviation.

The Gaussian noise is an additive noise sampled from a Gaussian distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMaximumStandardDeviation.(also called the normal distribution).

Its value must be between 0 and eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMaximumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ _MaxBrightnessOffset__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MaxBrightnessOffset__getter ( self )

protected

\cond

Gets the maximum absolute brightness offset.

◆ _MaxBrightnessOffset__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxBrightnessOffset__setter	(		self,
		float	value )

protected

Gets the maximum absolute brightness offset.

◆ _MaxContrastGain__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MaxContrastGain__getter ( self )

protected

\cond

Gets the maximum contrast gain.

Remarks:

Contrast transformation is performed by multiplying each mean-centered pixel value by a gain value taken between eVision.EasyDeepLearning.EDataAugmentation.MinContrastGain and eVision.EasyDeepLearning.EDataAugmentation.MaxContrastGain. A contrast transformation does not change the overall brightness of an image.

◆ _MaxContrastGain__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxContrastGain__setter	(		self,
		float	value )

protected

Gets the maximum contrast gain.

Remarks:

Contrast transformation is performed by multiplying each mean-centered pixel value by a gain value taken between eVision.EasyDeepLearning.EDataAugmentation.MinContrastGain and eVision.EasyDeepLearning.EDataAugmentation.MaxContrastGain. A contrast transformation does not change the overall brightness of an image.

◆ _MaxGamma__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MaxGamma__getter ( self )

protected

\cond

Gets the maximum gamma for gamma correction.

Remarks:

Gamma correction transformation is performed by raising each normalized pixel value to the power of gamma with gamma taken between eVision.EasyDeepLearning.EDataAugmentation.MinGamma and eVision.EasyDeepLearning.EDataAugmentation.MaxGamma.

◆ _MaxGamma__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxGamma__setter	(		self,
		float	value )

protected

Gets the maximum gamma for gamma correction.

Remarks:

Gamma correction transformation is performed by raising each normalized pixel value to the power of gamma with gamma taken between eVision.EasyDeepLearning.EDataAugmentation.MinGamma and eVision.EasyDeepLearning.EDataAugmentation.MaxGamma.

◆ _MaxHorizontalShear__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MaxHorizontalShear__getter ( self )

protected

\cond

Gets the maximum absolute horizontal shear, represented as an angle from the vertical direction.

◆ _MaxHorizontalShear__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxHorizontalShear__setter	(		self,
		float	value )

protected

Gets the maximum absolute horizontal shear, represented as an angle from the vertical direction.

◆ _MaxHorizontalShift__getter()

int eVision.EasyDeepLearning.EDataAugmentation._MaxHorizontalShift__getter ( self )

protected

\cond

Return the maximum horizontal shift allowed.

◆ _MaxHorizontalShift__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxHorizontalShift__setter	(		self,
		int	value )

protected

Return the maximum horizontal shift allowed.

◆ _MaxHueOffset__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MaxHueOffset__getter ( self )

protected

\cond

Gets the maximum absolute hue offset.

◆ _MaxHueOffset__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxHueOffset__setter	(		self,
		float	value )

protected

Gets the maximum absolute hue offset.

◆ _MaxRotationAngle__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MaxRotationAngle__getter ( self )

protected

\cond

Returns the maximum rotation angle allowed. The unit of the returned angle is in the current angle unit (see eVision.Easy.SetAngleUnit).

◆ _MaxRotationAngle__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxRotationAngle__setter	(		self,
		float	value )

protected

Returns the maximum rotation angle allowed.

The unit of the returned angle is in the current angle unit (see eVision.Easy.SetAngleUnit).

◆ _MaxSaturationGain__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MaxSaturationGain__getter ( self )

protected

\cond

Gets the maximum saturation gain.

◆ _MaxSaturationGain__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxSaturationGain__setter	(		self,
		float	value )

protected

Gets the maximum saturation gain.

◆ _MaxScale__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MaxScale__getter ( self )

protected

\cond

Gets the maximum scaling allowed.

◆ _MaxScale__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxScale__setter	(		self,
		float	value )

protected

Gets the maximum scaling allowed.

◆ _MaxStainColor__getter()

int eVision.EasyDeepLearning.EDataAugmentation._MaxStainColor__getter ( self )

protected

\cond

The maximum color value from which to draw a color to fill in the stain (we use a gaussian distribution of with a mean between eVision.EasyDeepLearning.EDataAugmentation.MinStainColor and eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor)

Its value must be bigger than eVision.EasyDeepLearning.EDataAugmentation.MinStainColor.

◆ _MaxStainColor__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxStainColor__setter	(		self,
		int	value )

protected

The maximum color value from which to draw a color to fill in the stain (we use a gaussian distribution of with a mean between eVision.EasyDeepLearning.EDataAugmentation.MinStainColor and eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor).

Its value must be bigger than eVision.EasyDeepLearning.EDataAugmentation.MinStainColor.

◆ _MaxVerticalShear__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MaxVerticalShear__getter ( self )

protected

\cond

Gets the maximum absolute vertical shear, represented as an angle from the horizontal direction.

◆ _MaxVerticalShear__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxVerticalShear__setter	(		self,
		float	value )

protected

Gets the maximum absolute vertical shear, represented as an angle from the horizontal direction.

◆ _MaxVerticalShift__getter()

int eVision.EasyDeepLearning.EDataAugmentation._MaxVerticalShift__getter ( self )

protected

\cond

Return the maximum vertical shift allowed.

◆ _MaxVerticalShift__setter()

eVision.EasyDeepLearning.EDataAugmentation._MaxVerticalShift__setter	(		self,
		int	value )

protected

Return the maximum vertical shift allowed.

◆ _MinContrastGain__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MinContrastGain__getter ( self )

protected

\cond

Gets the minimum contrast gain.

Remarks:

Contrast transformation is performed by multiplying each mean-centered pixel value by a gain value taken between eVision.EasyDeepLearning.EDataAugmentation.MinContrastGain and eVision.EasyDeepLearning.EDataAugmentation.MaxContrastGain. A contrast transformation does not change the overall brightness of an image.

◆ _MinContrastGain__setter()

eVision.EasyDeepLearning.EDataAugmentation._MinContrastGain__setter	(		self,
		float	value )

protected

Gets the minimum contrast gain.

Remarks:

Contrast transformation is performed by multiplying each mean-centered pixel value by a gain value taken between eVision.EasyDeepLearning.EDataAugmentation.MinContrastGain and eVision.EasyDeepLearning.EDataAugmentation.MaxContrastGain. A contrast transformation does not change the overall brightness of an image.

◆ _MinGamma__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MinGamma__getter ( self )

protected

\cond

Gets the minimum gamma for gamma correction.

Remarks:

Gamma correction transformation is performed by raising each normalized pixel value to the power of gamma with gamma taken between eVision.EasyDeepLearning.EDataAugmentation.MinGamma and eVision.EasyDeepLearning.EDataAugmentation.MaxGamma.

◆ _MinGamma__setter()

eVision.EasyDeepLearning.EDataAugmentation._MinGamma__setter	(		self,
		float	value )

protected

Gets the minimum gamma for gamma correction.

Remarks:

Gamma correction transformation is performed by raising each normalized pixel value to the power of gamma with gamma taken between eVision.EasyDeepLearning.EDataAugmentation.MinGamma and eVision.EasyDeepLearning.EDataAugmentation.MaxGamma.

◆ _MinSaturationGain__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MinSaturationGain__getter ( self )

protected

\cond

Gets the minimum saturation gain.

◆ _MinSaturationGain__setter()

eVision.EasyDeepLearning.EDataAugmentation._MinSaturationGain__setter	(		self,
		float	value )

protected

Gets the minimum saturation gain.

◆ _MinScale__getter()

float eVision.EasyDeepLearning.EDataAugmentation._MinScale__getter ( self )

protected

\cond

Gets the minimum scaling allowed.

◆ _MinScale__setter()

eVision.EasyDeepLearning.EDataAugmentation._MinScale__setter	(		self,
		float	value )

protected

Gets the minimum scaling allowed.

◆ _MinStainColor__getter()

int eVision.EasyDeepLearning.EDataAugmentation._MinStainColor__getter ( self )

protected

\cond

The minimum color value from which to draw a color to fill in the stain (we use a gaussian distribution of with a mean between eVision.EasyDeepLearning.EDataAugmentation.MinStainColor and eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor)

Its value must be inferior to 255 and eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor.

◆ _MinStainColor__setter()

eVision.EasyDeepLearning.EDataAugmentation._MinStainColor__setter	(		self,
		int	value )

protected

The minimum color value from which to draw a color to fill in the stain (we use a gaussian distribution of with a mean between eVision.EasyDeepLearning.EDataAugmentation.MinStainColor and eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor).

Its value must be inferior to 255 and eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor.

◆ _SaltAndPepperNoiseMaximumDensity__getter()

float eVision.EasyDeepLearning.EDataAugmentation._SaltAndPepperNoiseMaximumDensity__getter ( self )

protected

\cond

The maximum density of the salt and pepper noise.

The salt and pepper noise sets the value of a number of randomly selected (between eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity and eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMaximumDensity) pixels to its minimum or maximum value.

Its value must be between eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity and 1.

Remarks:

This noise is computed after all the other noises.

◆ _SaltAndPepperNoiseMaximumDensity__setter()

eVision.EasyDeepLearning.EDataAugmentation._SaltAndPepperNoiseMaximumDensity__setter	(		self,
		float	value )

protected

The maximum density of the salt and pepper noise.

The salt and pepper noise sets the value of a number of randomly selected (between eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity and eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMaximumDensity) pixels to its minimum or maximum value.

Its value must be between eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity and 1.

Remarks:

This noise is computed after all the other noises.

◆ _SaltAndPepperNoiseMinimumDensity__getter()

float eVision.EasyDeepLearning.EDataAugmentation._SaltAndPepperNoiseMinimumDensity__getter ( self )

protected

\cond

The minimum density of the salt and pepper noise.

The salt and pepper noise sets the value of a number of randomly selected (between eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity and eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMaximumDensity) pixels to its minimum or maximum value.

Its value must be between 0 and eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity.

Remarks:

This noise is computed after all the other noises.

◆ _SaltAndPepperNoiseMinimumDensity__setter()

eVision.EasyDeepLearning.EDataAugmentation._SaltAndPepperNoiseMinimumDensity__setter	(		self,
		float	value )

protected

The minimum density of the salt and pepper noise.

The salt and pepper noise sets the value of a number of randomly selected (between eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity and eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMaximumDensity) pixels to its minimum or maximum value.

Its value must be between 0 and eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity.

Remarks:

This noise is computed after all the other noises.

◆ _SpeckleNoiseMaximumStandardDeviation__getter()

float eVision.EasyDeepLearning.EDataAugmentation._SpeckleNoiseMaximumStandardDeviation__getter ( self )

protected

\cond

The speckle noise maximum standard deviation.

The speckle noise is a multiplicative noise sampled from a Gamma distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMaximumStandardDeviation.

Its value must be strictly higher than eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMinimumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ _SpeckleNoiseMaximumStandardDeviation__setter()

eVision.EasyDeepLearning.EDataAugmentation._SpeckleNoiseMaximumStandardDeviation__setter	(		self,
		float	value )

protected

The speckle noise maximum standard deviation.

The speckle noise is a multiplicative noise sampled from a Gamma distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMaximumStandardDeviation.

Its value must be strictly higher than eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMinimumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ _SpeckleNoiseMinimumStandardDeviation__getter()

float eVision.EasyDeepLearning.EDataAugmentation._SpeckleNoiseMinimumStandardDeviation__getter ( self )

protected

\cond

The speckle noise minimum standard deviation.

The speckle noise is a multiplicative noise sampled from a Gamma distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMaximumStandardDeviation.

Its value must be strictly positive and lower than eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMaximumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ _SpeckleNoiseMinimumStandardDeviation__setter()

eVision.EasyDeepLearning.EDataAugmentation._SpeckleNoiseMinimumStandardDeviation__setter	(		self,
		float	value )

protected

The speckle noise minimum standard deviation.

The speckle noise is a multiplicative noise sampled from a Gamma distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMaximumStandardDeviation.

Its value must be strictly positive and lower than eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMaximumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ _StainBlur__getter()

int eVision.EasyDeepLearning.EDataAugmentation._StainBlur__getter ( self )

protected

\cond

Stain blur.

The stain blur is the half kernel size of a Gaussian filter that is applied on the stain to smooth its edges and therefore the transition between the original image and the stain.

◆ _StainBlur__setter()

eVision.EasyDeepLearning.EDataAugmentation._StainBlur__setter	(		self,
		int	value )

protected

Stain blur.

The stain blur is the half kernel size of a Gaussian filter that is applied on the stain to smooth its edges and therefore the transition between the original image and the stain.

◆ _StainColorVariation__getter()

int eVision.EasyDeepLearning.EDataAugmentation._StainColorVariation__getter ( self )

protected

\cond

The variation of the color used to fill in the ellipse (We use an gaussian distribution of standard mean deviation stainColorVariation).

◆ _StainColorVariation__setter()

eVision.EasyDeepLearning.EDataAugmentation._StainColorVariation__setter	(		self,
		int	value )

protected

The variation of the color used to fill in the ellipse (We use an gaussian distribution of standard mean deviation stainColorVariation).

◆ _StainDisruptionMaxAnchorPoints__getter()

int eVision.EasyDeepLearning.EDataAugmentation._StainDisruptionMaxAnchorPoints__getter ( self )

protected

\cond

The maximum number of anchor points to use while disrupting the ellipse.

◆ _StainDisruptionMaxAnchorPoints__setter()

eVision.EasyDeepLearning.EDataAugmentation._StainDisruptionMaxAnchorPoints__setter	(		self,
		int	value )

protected

The maximum number of anchor points to use while disrupting the ellipse.

◆ _StainDisruptionMaxIntensity__getter()

float eVision.EasyDeepLearning.EDataAugmentation._StainDisruptionMaxIntensity__getter ( self )

protected

\cond

The maximum offset applied to the coordinates (x,y) of a pixel from the ellipse contour.

◆ _StainDisruptionMaxIntensity__setter()

eVision.EasyDeepLearning.EDataAugmentation._StainDisruptionMaxIntensity__setter	(		self,
		float	value )

protected

The maximum offset applied to the coordinates (x,y) of a pixel from the ellipse contour.

◆ _StainEllipseMaxRadius__getter()

int eVision.EasyDeepLearning.EDataAugmentation._StainEllipseMaxRadius__getter ( self )

protected

\cond

The maximum radius of the ellipse used to produce the stain.

Its value must be superior to eVision.EasyDeepLearning.EDataAugmentation.StainEllipseMinRadius.

◆ _StainEllipseMaxRadius__setter()

eVision.EasyDeepLearning.EDataAugmentation._StainEllipseMaxRadius__setter	(		self,
		int	value )

protected

The maximum radius of the ellipse used to produce the stain.

Its value must be superior to eVision.EasyDeepLearning.EDataAugmentation.StainEllipseMinRadius.

◆ _StainEllipseMinRadius__getter()

int eVision.EasyDeepLearning.EDataAugmentation._StainEllipseMinRadius__getter ( self )

protected

\cond

The minimum radius of the ellipse used to produce the stain.

Its value must be inferior to eVision.EasyDeepLearning.EDataAugmentation.StainEllipseMaxRadius.

◆ _StainEllipseMinRadius__setter()

eVision.EasyDeepLearning.EDataAugmentation._StainEllipseMinRadius__setter	(		self,
		int	value )

protected

The minimum radius of the ellipse used to produce the stain.

Its value must be inferior to eVision.EasyDeepLearning.EDataAugmentation.StainEllipseMaxRadius.

◆ _StainInterpolationSiteFactor__getter()

float eVision.EasyDeepLearning.EDataAugmentation._StainInterpolationSiteFactor__getter ( self )

protected

\cond

The factor to compute the number of interpolation sites to use from the number of anchor points.

◆ _StainInterpolationSiteFactor__setter()

eVision.EasyDeepLearning.EDataAugmentation._StainInterpolationSiteFactor__setter	(		self,
		float	value )

protected

The factor to compute the number of interpolation sites to use from the number of anchor points.

◆ _StainProbability__getter()

float eVision.EasyDeepLearning.EDataAugmentation._StainProbability__getter ( self )

protected

\cond

Probability of applying the stain data augmentation (default value: 0, i.e. no stain).

◆ _StainProbability__setter()

eVision.EasyDeepLearning.EDataAugmentation._StainProbability__setter	(		self,
		float	value )

protected

Probability of applying the stain data augmentation (default value: 0, i.e.

no stain).

◆ CopyTo()

None eVision.EasyDeepLearning.EDataAugmentation.CopyTo	(		self,
		eVision.EasyDeepLearning.EDataAugmentation	other )

Copies itself to the eVision.EasyDeepLearning.EDataAugmentation object other.

Parameters

other The other eVision.EasyDeepLearning.EDataAugmentation that we will copy into this one.

◆ Generate() [1/8]

eVision.EBaseROI \| None eVision.EasyDeepLearning.EDataAugmentation.Generate	(		self,
		eVision.EBaseROI \| None	img )

Generates a new image from a generic eVision.EBaseROI image.

The caller is responsible for calling freeing the memory of the returned image by calling delete on the image.

Remarks:

If the data augmentation fails, the method will throw an exception.

Parameters

img	The image to transform.

◆ Generate() [2/8]

eVision.EBaseROI \| None eVision.EasyDeepLearning.EDataAugmentation.Generate	(		self,
		eVision.EBaseROI \| None	img,
		eVision.EasyDeepLearning.EDLDataAugmentationType	type )

Generates a new image from a generic eVision.EBaseROI image.

The caller is responsible for calling freeing the memory of the returned image by calling delete on the image.

Remarks:

If the data augmentation fails, the method will throw an exception.

Parameters

img	The image to transform.
type	The type of transformation to generate.

◆ Generate() [3/8]

None eVision.EasyDeepLearning.EDataAugmentation.Generate	(		self,
		eVision.EROIBW16	source,
		eVision.EROIBW16	dest )

Generates a new image.

Remarks:

If the data augmentation fails, the method will throw an exception.

Parameters

source	The image to transform.
dest	The transformed image.

◆ Generate() [4/8]

None eVision.EasyDeepLearning.EDataAugmentation.Generate	(		self,
		eVision.EROIBW16	source,
		eVision.EROIBW16	dest,
		eVision.EasyDeepLearning.EDLDataAugmentationType	type )

Generates a new image.

Remarks:

If the data augmentation fails, the method will throw an exception.

Parameters

source	The image to transform.
dest	The transformed image.
type	The type of transformation to generate.

◆ Generate() [5/8]

None eVision.EasyDeepLearning.EDataAugmentation.Generate	(		self,
		eVision.EROIBW8	source,
		eVision.EROIBW8	dest )

Generates a new image.

Remarks:

If the data augmentation fails, the method will throw an exception.

Parameters

source	The image to transform.
dest	The transformed image.

◆ Generate() [6/8]

None eVision.EasyDeepLearning.EDataAugmentation.Generate	(		self,
		eVision.EROIBW8	source,
		eVision.EROIBW8	dest,
		eVision.EasyDeepLearning.EDLDataAugmentationType	type )

Generates a new image.

Remarks:

If the data augmentation fails, the method will throw an exception.

Parameters

source	The image to transform.
dest	The transformed image.
type	The type of transformation to generate.

◆ Generate() [7/8]

None eVision.EasyDeepLearning.EDataAugmentation.Generate	(		self,
		eVision.EROIC24	source,
		eVision.EROIC24	dest )

Generates a new image.

Remarks:

If the data augmentation fails, the method will throw an exception.

Parameters

source	The image to transform.
dest	The transformed image.

◆ Generate() [8/8]

None eVision.EasyDeepLearning.EDataAugmentation.Generate	(		self,
		eVision.EROIC24	source,
		eVision.EROIC24	dest,
		eVision.EasyDeepLearning.EDLDataAugmentationType	type )

Generates a new image.

Remarks:

If the data augmentation fails, the method will throw an exception.

Parameters

source	The image to transform.
dest	The transformed image.
type	The type of transformation to generate.

◆ HasDataAugmentations()

bool eVision.EasyDeepLearning.EDataAugmentation.HasDataAugmentations ( self )

Whether the eVision.EasyDeepLearning.EDataAugmentation object contains augmentations.

◆ Load() [1/2]

None eVision.EasyDeepLearning.EDataAugmentation.Load	(		self,
		eVision.ESerializer \| None	serializer )

Loads an eVision.EasyDeepLearning.EDataAugmentation object.

The given ESerializer must have been created for reading.

Parameters

serializer The serializer.

◆ Load() [2/2]

None eVision.EasyDeepLearning.EDataAugmentation.Load	(		self,
		str	path )

Loads an eVision.EasyDeepLearning.EDataAugmentation object.

The given ESerializer must have been created for reading.

Parameters

path	The file path.

◆ Save() [1/2]

None eVision.EasyDeepLearning.EDataAugmentation.Save	(		self,
		eVision.ESerializer \| None	serializer )

Saves an eVision.EasyDeepLearning.EDataAugmentation object.

The given ESerializer must have been created for writing.

Parameters

serializer The eVision.ESerializer object that is written to.

◆ Save() [2/2]

None eVision.EasyDeepLearning.EDataAugmentation.Save	(		self,
		str	path )

Saves an eVision.EasyDeepLearning.EDataAugmentation object.

The given ESerializer must have been created for writing.

Parameters

path	The file path.

Property Documentation

◆ EnableHorizontalFlip

eVision.EasyDeepLearning.EDataAugmentation.EnableHorizontalFlip = property(_EnableHorizontalFlip__getter, _EnableHorizontalFlip__setter)

static

\endcond

Gets whether to use horizontally flipped versions of input images.

◆ EnableVerticalFlip

eVision.EasyDeepLearning.EDataAugmentation.EnableVerticalFlip = property(_EnableVerticalFlip__getter, _EnableVerticalFlip__setter)

static

\endcond

Gets whether to use vertically flipped versions of input images.

◆ GaussianNoiseMaximumStandardDeviation

eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMaximumStandardDeviation = property(_GaussianNoiseMaximumStandardDeviation__getter, _GaussianNoiseMaximumStandardDeviation__setter)

static

\endcond

The Gaussian noise maximum standard deviation.

The Gaussian noise is an additive noise sampled from a Gaussian distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMaximumStandardDeviation.(also called the normal distribution).

Its value must be superior or equal to eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMinimumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ GaussianNoiseMinimumStandardDeviation

eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMinimumStandardDeviation = property(_GaussianNoiseMinimumStandardDeviation__getter, _GaussianNoiseMinimumStandardDeviation__setter)

static

\endcond

The Gaussian noise minimum standard deviation.

The Gaussian noise is an additive noise sampled from a Gaussian distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMaximumStandardDeviation.(also called the normal distribution).

Its value must be between 0 and eVision.EasyDeepLearning.EDataAugmentation.GaussianNoiseMaximumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ MaxBrightnessOffset

eVision.EasyDeepLearning.EDataAugmentation.MaxBrightnessOffset = property(_MaxBrightnessOffset__getter, _MaxBrightnessOffset__setter)

static

\endcond

Gets the maximum absolute brightness offset.

◆ MaxContrastGain

eVision.EasyDeepLearning.EDataAugmentation.MaxContrastGain = property(_MaxContrastGain__getter, _MaxContrastGain__setter)

static

\endcond

Gets the maximum contrast gain.

Remarks:

Contrast transformation is performed by multiplying each mean-centered pixel value by a gain value taken between eVision.EasyDeepLearning.EDataAugmentation.MinContrastGain and eVision.EasyDeepLearning.EDataAugmentation.MaxContrastGain. A contrast transformation does not change the overall brightness of an image.

◆ MaxGamma

eVision.EasyDeepLearning.EDataAugmentation.MaxGamma = property(_MaxGamma__getter, _MaxGamma__setter)

static

\endcond

Gets the maximum gamma for gamma correction.

Remarks:

Gamma correction transformation is performed by raising each normalized pixel value to the power of gamma with gamma taken between eVision.EasyDeepLearning.EDataAugmentation.MinGamma and eVision.EasyDeepLearning.EDataAugmentation.MaxGamma.

◆ MaxHorizontalShear

eVision.EasyDeepLearning.EDataAugmentation.MaxHorizontalShear = property(_MaxHorizontalShear__getter, _MaxHorizontalShear__setter)

static

\endcond

Gets the maximum absolute horizontal shear, represented as an angle from the vertical direction.

◆ MaxHorizontalShift

eVision.EasyDeepLearning.EDataAugmentation.MaxHorizontalShift = property(_MaxHorizontalShift__getter, _MaxHorizontalShift__setter)

static

\endcond

Return the maximum horizontal shift allowed.

◆ MaxHueOffset

eVision.EasyDeepLearning.EDataAugmentation.MaxHueOffset = property(_MaxHueOffset__getter, _MaxHueOffset__setter)

static

\endcond

Gets the maximum absolute hue offset.

◆ MaxRotationAngle

eVision.EasyDeepLearning.EDataAugmentation.MaxRotationAngle = property(_MaxRotationAngle__getter, _MaxRotationAngle__setter)

static

\endcond

Returns the maximum rotation angle allowed. The unit of the returned angle is in the current angle unit (see eVision.Easy.SetAngleUnit).

◆ MaxSaturationGain

eVision.EasyDeepLearning.EDataAugmentation.MaxSaturationGain = property(_MaxSaturationGain__getter, _MaxSaturationGain__setter)

static

\endcond

Gets the maximum saturation gain.

◆ MaxScale

eVision.EasyDeepLearning.EDataAugmentation.MaxScale = property(_MaxScale__getter, _MaxScale__setter)

static

\endcond

Gets the maximum scaling allowed.

◆ MaxStainColor

eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor = property(_MaxStainColor__getter, _MaxStainColor__setter)

static

\endcond

The maximum color value from which to draw a color to fill in the stain (we use a gaussian distribution of with a mean between eVision.EasyDeepLearning.EDataAugmentation.MinStainColor and eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor)

Its value must be bigger than eVision.EasyDeepLearning.EDataAugmentation.MinStainColor.

◆ MaxVerticalShear

eVision.EasyDeepLearning.EDataAugmentation.MaxVerticalShear = property(_MaxVerticalShear__getter, _MaxVerticalShear__setter)

static

\endcond

Gets the maximum absolute vertical shear, represented as an angle from the horizontal direction.

◆ MaxVerticalShift

eVision.EasyDeepLearning.EDataAugmentation.MaxVerticalShift = property(_MaxVerticalShift__getter, _MaxVerticalShift__setter)

static

\endcond

Return the maximum vertical shift allowed.

◆ MinContrastGain

eVision.EasyDeepLearning.EDataAugmentation.MinContrastGain = property(_MinContrastGain__getter, _MinContrastGain__setter)

static

\endcond

Gets the minimum contrast gain.

Remarks:

Contrast transformation is performed by multiplying each mean-centered pixel value by a gain value taken between eVision.EasyDeepLearning.EDataAugmentation.MinContrastGain and eVision.EasyDeepLearning.EDataAugmentation.MaxContrastGain. A contrast transformation does not change the overall brightness of an image.

◆ MinGamma

eVision.EasyDeepLearning.EDataAugmentation.MinGamma = property(_MinGamma__getter, _MinGamma__setter)

static

\endcond

Gets the minimum gamma for gamma correction.

Remarks:

Gamma correction transformation is performed by raising each normalized pixel value to the power of gamma with gamma taken between eVision.EasyDeepLearning.EDataAugmentation.MinGamma and eVision.EasyDeepLearning.EDataAugmentation.MaxGamma.

◆ MinSaturationGain

eVision.EasyDeepLearning.EDataAugmentation.MinSaturationGain = property(_MinSaturationGain__getter, _MinSaturationGain__setter)

static

\endcond

Gets the minimum saturation gain.

◆ MinScale

eVision.EasyDeepLearning.EDataAugmentation.MinScale = property(_MinScale__getter, _MinScale__setter)

static

\endcond

Gets the minimum scaling allowed.

◆ MinStainColor

eVision.EasyDeepLearning.EDataAugmentation.MinStainColor = property(_MinStainColor__getter, _MinStainColor__setter)

static

\endcond

The minimum color value from which to draw a color to fill in the stain (we use a gaussian distribution of with a mean between eVision.EasyDeepLearning.EDataAugmentation.MinStainColor and eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor)

Its value must be inferior to 255 and eVision.EasyDeepLearning.EDataAugmentation.MaxStainColor.

◆ SaltAndPepperNoiseMaximumDensity

eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMaximumDensity = property(_SaltAndPepperNoiseMaximumDensity__getter, _SaltAndPepperNoiseMaximumDensity__setter)

static

\endcond

The maximum density of the salt and pepper noise.

The salt and pepper noise sets the value of a number of randomly selected (between eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity and eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMaximumDensity) pixels to its minimum or maximum value.

Its value must be between eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity and 1.

Remarks:

This noise is computed after all the other noises.

◆ SaltAndPepperNoiseMinimumDensity

eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity = property(_SaltAndPepperNoiseMinimumDensity__getter, _SaltAndPepperNoiseMinimumDensity__setter)

static

\endcond

The minimum density of the salt and pepper noise.

The salt and pepper noise sets the value of a number of randomly selected (between eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity and eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMaximumDensity) pixels to its minimum or maximum value.

Its value must be between 0 and eVision.EasyDeepLearning.EDataAugmentation.SaltAndPepperNoiseMinimumDensity.

Remarks:

This noise is computed after all the other noises.

◆ SpeckleNoiseMaximumStandardDeviation

eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMaximumStandardDeviation = property(_SpeckleNoiseMaximumStandardDeviation__getter, _SpeckleNoiseMaximumStandardDeviation__setter)

static

\endcond

The speckle noise maximum standard deviation.

The speckle noise is a multiplicative noise sampled from a Gamma distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMaximumStandardDeviation.

Its value must be strictly higher than eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMinimumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ SpeckleNoiseMinimumStandardDeviation

eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMinimumStandardDeviation = property(_SpeckleNoiseMinimumStandardDeviation__getter, _SpeckleNoiseMinimumStandardDeviation__setter)

static

\endcond

The speckle noise minimum standard deviation.

The speckle noise is a multiplicative noise sampled from a Gamma distribution of deviation between eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMinimumStandardDeviation and eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMaximumStandardDeviation.

Its value must be strictly positive and lower than eVision.EasyDeepLearning.EDataAugmentation.SpeckleNoiseMaximumStandardDeviation.

Remarks:

This noise is computed before the salt and paper noise.

◆ StainBlur

eVision.EasyDeepLearning.EDataAugmentation.StainBlur = property(_StainBlur__getter, _StainBlur__setter)

static

\endcond

Stain blur.

The stain blur is the half kernel size of a Gaussian filter that is applied on the stain to smooth its edges and therefore the transition between the original image and the stain.

◆ StainColorVariation

eVision.EasyDeepLearning.EDataAugmentation.StainColorVariation = property(_StainColorVariation__getter, _StainColorVariation__setter)

static

\endcond

The variation of the color used to fill in the ellipse (We use an gaussian distribution of standard mean deviation stainColorVariation).

◆ StainDisruptionMaxAnchorPoints

eVision.EasyDeepLearning.EDataAugmentation.StainDisruptionMaxAnchorPoints = property(_StainDisruptionMaxAnchorPoints__getter, _StainDisruptionMaxAnchorPoints__setter)

static

\endcond

The maximum number of anchor points to use while disrupting the ellipse.

◆ StainDisruptionMaxIntensity

eVision.EasyDeepLearning.EDataAugmentation.StainDisruptionMaxIntensity = property(_StainDisruptionMaxIntensity__getter, _StainDisruptionMaxIntensity__setter)

static

\endcond

The maximum offset applied to the coordinates (x,y) of a pixel from the ellipse contour.

◆ StainEllipseMaxRadius

eVision.EasyDeepLearning.EDataAugmentation.StainEllipseMaxRadius = property(_StainEllipseMaxRadius__getter, _StainEllipseMaxRadius__setter)

static

\endcond

The maximum radius of the ellipse used to produce the stain.

Its value must be superior to eVision.EasyDeepLearning.EDataAugmentation.StainEllipseMinRadius.

◆ StainEllipseMinRadius

eVision.EasyDeepLearning.EDataAugmentation.StainEllipseMinRadius = property(_StainEllipseMinRadius__getter, _StainEllipseMinRadius__setter)

static

\endcond

The minimum radius of the ellipse used to produce the stain.

Its value must be inferior to eVision.EasyDeepLearning.EDataAugmentation.StainEllipseMaxRadius.

◆ StainInterpolationSiteFactor

eVision.EasyDeepLearning.EDataAugmentation.StainInterpolationSiteFactor = property(_StainInterpolationSiteFactor__getter, _StainInterpolationSiteFactor__setter)

static

\endcond

The factor to compute the number of interpolation sites to use from the number of anchor points.

◆ StainProbability

eVision.EasyDeepLearning.EDataAugmentation.StainProbability = property(_StainProbability__getter, _StainProbability__setter)

static

\endcond

Probability of applying the stain data augmentation (default value: 0, i.e. no stain).

Public Member Functions

Protected Member Functions

Properties

Detailed Description

Constructor & Destructor Documentation

◆ __init__() [1/2]

◆ __init__() [2/2]

Member Function Documentation

◆ _EnableHorizontalFlip__getter()

◆ _EnableHorizontalFlip__setter()

◆ _EnableVerticalFlip__getter()

◆ _EnableVerticalFlip__setter()

◆ _GaussianNoiseMaximumStandardDeviation__getter()

◆ _GaussianNoiseMaximumStandardDeviation__setter()

◆ _GaussianNoiseMinimumStandardDeviation__getter()

◆ _GaussianNoiseMinimumStandardDeviation__setter()

◆ _MaxBrightnessOffset__getter()

◆ _MaxBrightnessOffset__setter()

◆ _MaxContrastGain__getter()

◆ _MaxContrastGain__setter()

◆ _MaxGamma__getter()

◆ _MaxGamma__setter()

◆ _MaxHorizontalShear__getter()

◆ _MaxHorizontalShear__setter()

◆ _MaxHorizontalShift__getter()

◆ _MaxHorizontalShift__setter()

◆ _MaxHueOffset__getter()

◆ _MaxHueOffset__setter()

◆ _MaxRotationAngle__getter()

◆ _MaxRotationAngle__setter()

◆ _MaxSaturationGain__getter()

◆ _MaxSaturationGain__setter()

◆ _MaxScale__getter()

◆ _MaxScale__setter()

◆ _MaxStainColor__getter()

◆ _MaxStainColor__setter()

◆ _MaxVerticalShear__getter()

◆ _MaxVerticalShear__setter()

◆ _MaxVerticalShift__getter()

◆ _MaxVerticalShift__setter()

◆ _MinContrastGain__getter()

◆ _MinContrastGain__setter()

◆ _MinGamma__getter()

◆ _MinGamma__setter()

◆ _MinSaturationGain__getter()

◆ _MinSaturationGain__setter()

◆ _MinScale__getter()

◆ _MinScale__setter()

◆ _MinStainColor__getter()

◆ _MinStainColor__setter()

◆ _SaltAndPepperNoiseMaximumDensity__getter()

◆ _SaltAndPepperNoiseMaximumDensity__setter()

◆ _SaltAndPepperNoiseMinimumDensity__getter()

◆ _SaltAndPepperNoiseMinimumDensity__setter()

◆ _SpeckleNoiseMaximumStandardDeviation__getter()

◆ _SpeckleNoiseMaximumStandardDeviation__setter()

◆ _SpeckleNoiseMinimumStandardDeviation__getter()

◆ _SpeckleNoiseMinimumStandardDeviation__setter()

◆ _StainBlur__getter()

◆ _StainBlur__setter()

◆ _StainColorVariation__getter()

◆ _StainColorVariation__setter()

◆ _StainDisruptionMaxAnchorPoints__getter()

◆ _StainDisruptionMaxAnchorPoints__setter()

◆ _StainDisruptionMaxIntensity__getter()

◆ _StainDisruptionMaxIntensity__setter()

◆ _StainEllipseMaxRadius__getter()

◆ _StainEllipseMaxRadius__setter()

◆ _StainEllipseMinRadius__getter()

◆ _StainEllipseMinRadius__setter()

◆ _StainInterpolationSiteFactor__getter()

◆ _StainInterpolationSiteFactor__setter()

◆ _StainProbability__getter()

◆ _StainProbability__setter()

◆ CopyTo()

◆ Generate() [1/8]

◆ Generate() [2/8]

◆ Generate() [3/8]

◆ Generate() [4/8]

◆ Generate() [5/8]

◆ init() [1/2]

◆ init() [2/2]