Detailed Description

template<typename imf_img_typeT, typename AlphaT = Scalar<float>, typename BetaT = Scalar<float>>
class ImFusion::ImageMath::Noise< imf_img_typeT, AlphaT, BetaT >

ImageMath leaf for generating noise in ImageMath expressions.

As C++ does not deduce constructor template arguments until C++17, the makeNoise convenience functions are also included in this file. Different types of noise are implemented and the meaning of the parameters alpha and beta depends on the type of noise Gaussian: random normal distribution with mean = alpha and variance = beta Uniform: random uniform distribution on [alpha, beta] Shot: Shot noise approximated using a Normal distribution. The value at each pixel is alpha + beta*sqrt(alpha)*randn(). Alpha is the original value of the image and the expected value, beta quantifies the amount of noise. This type of noise preserves zeros.

Public Types
using	expr_type = float
	The expr_type value gives the result of each component of this expression.

using	var_type = void

using	imf_img_type = imf_img_typeT

Public Member Functions
	Noise (std::vector< ImageDescriptor > descriptors, NoiseType noiseType, const AlphaT &alpha, const BetaT &beta, int seed=0)
	Create a Noise constructor using vector of ImageDescriptor objects.

ImageDescriptor	imgDesc () const override
	Return ImageDescriptor of this expression. This reference is expected to remain the same while the class exists.

template<typename ImgT>
auto	convertToMemImgExpr () const noexcept

auto	convertToSharedImgExpr (std::size_t index) const

IMFUSION_STRONG_INLINE expr_type	eval (const std::size_t i, const vec4i &coord) const
	CPU implementation.

int	numImgs () const override
	Return number of images of this expression.

ImageMath::DeviceStrategy	deviceStrategy () const override
	Return DeviceStrategy of this expression.

Public Member Functions inherited from ExprBaseTpl< ImplType >
const auto &	get () const
	get a const reference to this with the actual type

auto &	get ()
	get a reference to this with the actual type

auto	polyWrapper () const

auto	uniquePolyWrapper () const

auto	sharedPolyWrapper () const

template<typename Op, typename RhsT>
auto	binaryOp (const ExprBaseTpl< RhsT > &rhs, const Op &func=Op()) const

template<typename Op, typename RhsT>
auto	binaryOp (RhsT rhs, const Op &func=Op(), typename std::enable_if< std::is_arithmetic_v< RhsT > >::type *=nullptr) const

template<typename Op, typename RhsT, int Dim, int Options, int MaxRows, int MaxCols>
auto	binaryOp (Eigen::Matrix< RhsT, Dim, 1, Options, MaxRows, MaxCols > rhs, const Op &func=Op(), typename std::enable_if< std::is_arithmetic_v< RhsT > >::type *=nullptr) const

template<typename Op, typename StringOp, typename RhsT>
auto	binaryOp (const ExprBaseTpl< RhsT > &rhs, const Op &func, const StringOp &stringFunc) const

template<typename Op, typename StringOp, typename RhsT>
auto	binaryOp (RhsT rhs, const Op &func, const StringOp &stringFunc, typename std::enable_if< std::is_arithmetic_v< RhsT > >::type *=nullptr) const

template<typename Op, typename StringOp, typename RhsT, int Dim, int Options, int MaxRows, int MaxCols>
auto	binaryOp (Eigen::Matrix< RhsT, Dim, 1, Options, MaxRows, MaxCols > rhs, const Op &func, const StringOp &stringFunc, typename std::enable_if< std::is_arithmetic_v< RhsT > >::type *=nullptr) const

template<typename Op>
auto	unaryOp (const Op &func=Op()) const

template<typename Op, typename StringOp>
auto	unaryOp (const Op &func, const StringOp &stringFunc) const

template<typename Op>
reduction_type	reduce (std::vector< vec4i > *arg=nullptr) const

auto	forceCPU () const
	Forces CPU execution.

auto	forceGPU () const
	Forces GPU execution.

auto	channelSwizzle (const std::vector< std::size_t > &indices) const

template<size_t i>
auto	head ()

	ADD_SPECIAL_SWIZZLE (x, {0})

	ADD_SPECIAL_SWIZZLE (y, {1})

	ADD_SPECIAL_SWIZZLE (z, {2})

	ADD_SPECIAL_SWIZZLE (w, {3})

	ADD_SPECIAL_SWIZZLE (r, {0})

	ADD_SPECIAL_SWIZZLE (g, {1})

	ADD_SPECIAL_SWIZZLE (b, {2})

	ADD_SPECIAL_SWIZZLE (a, {3})

	ADD_SPECIAL_SWIZZLE (xy, std::vector< size_t >({0, 1}))

	ADD_SPECIAL_SWIZZLE (rg, std::vector< size_t >({0, 1}))

	ADD_SPECIAL_SWIZZLE (xyz, std::vector< size_t >({0, 1, 2}))

	ADD_SPECIAL_SWIZZLE (xyzw, std::vector< size_t >({0, 1, 2, 3}))

	ADD_SPECIAL_SWIZZLE (rgb, std::vector< size_t >({0, 1, 2}))

	ADD_SPECIAL_SWIZZLE (rgba, std::vector< size_t >({0, 1, 2, 3}))

auto	streamChannels (int numStreamedChannels) const

template<typename T>
auto	substituteVariableWithImg (T &img) const

auto	operator- () const

template<typename CastT>
auto	cast () const

auto	storageToOriginal (const ImageDescriptor &desc)
	Apply shift/scale to the operand,.

auto	originalToStorage (const ImageDescriptor &desc)
	Apply shift/scale to the operand,.

template<typename Op>
auto	channelReduction ()

	ADD_CHANNEL_REDUCTION_OPERATOR (channelSum, add)

	ADD_CHANNEL_REDUCTION_OPERATOR (channelProd, mult)

	ADD_CHANNEL_REDUCTION_OPERATOR (channelMax, max)

	ADD_CHANNEL_REDUCTION_OPERATOR (channelMin, min)

	ADD_CHANNEL_REDUCTION_OPERATOR (length, length)

auto	channelMean ()

auto	squaredLength () const

template<typename RhsT>
auto	channelDistance (const ExprBaseTpl< RhsT > &other) const

template<typename T, int Dim>
auto	channelDistance (const Eigen::Matrix< T, Dim, 1 > c)

template<typename RhsT>
auto	dot (const ExprBaseTpl< RhsT > &other) const

template<typename VariableT>
auto	stashThenApply (const ExprBaseTpl< VariableT > &varExpr) const

template<typename VarT = double>
auto	hnormalized () const

template<typename VarT = double>
auto	normalized () const

auto	homogeneous () const

auto	appendZero () const

template<typename LhsT, typename RhsT>
auto	select (const ExprBaseTpl< LhsT > &lhs, const ExprBaseTpl< RhsT > &rhs) const
	Ternary (condition.x ? if_true : if_false) operator.

template<typename LhsT, typename RhsT>
auto	select (LhsT lhs, RhsT rhs, typename std::enable_if< std::is_arithmetic_v< LhsT > &&std::is_arithmetic_v< RhsT > >::type *=nullptr) const
	Ternary (condition.x ? if_true : if_false) operator.

template<typename LhsT, typename RhsT>
auto	select (LhsT lhs, const ExprBaseTpl< RhsT > &rhs, typename std::enable_if< std::is_arithmetic_v< LhsT > >::type *=nullptr) const
	Ternary (condition.x ? if_true : if_false) operator.

template<typename LhsT, typename RhsT>
auto	select (const ExprBaseTpl< LhsT > &lhs, RhsT rhs, typename std::enable_if< std::is_arithmetic_v< RhsT > >::type *=nullptr) const
	Ternary (condition.x ? if_true : if_false) operator.

	ADD_REDUCTION_OPERATOR (sum, add)

	ADD_REDUCTION_OPERATOR (prod, mult)

	ADD_ARG_REDUCTION_OPERATOR (min, min)

	ADD_ARG_REDUCTION_OPERATOR (max, max)

Eigen::Matrix< double, Eigen::Dynamic, 1 >	mean () const

Eigen::Matrix< double, Eigen::Dynamic, 1 >	l1Norm () const

Eigen::Matrix< double, Eigen::Dynamic, 1 >	squaredl2Norm () const

Eigen::Matrix< double, Eigen::Dynamic, 1 >	l2Norm () const

Eigen::Matrix< double, Eigen::Dynamic, 1 >	lpNorm (double p) const

Eigen::Matrix< double, Eigen::Dynamic, 1 >	lInfNorm () const

template<typename ImgType = void>
auto	evaluateIntoImage (bool clearShiftScale=false) const
	Create an empty image and evaluate this expression into it.

auto	toMask () const

auto	toDeformation (const ImageDescriptorWorld imgDesc) const

template<bool includeDeformation = false>
auto	resample (const ImageDescriptorWorld &inputDesc, const ImageDescriptorWorld &outputDesc) const

template<bool includeDeformation = false, typename T = SharedImage>
auto	resample (SharedImage &inputDesc, SharedImage &outputDesc, std::enable_if_t< std::is_same_v< T, SharedImage > > *=nullptr) const

template<bool includeDeformation = false, typename T = SharedImageSet>
auto	resample (SharedImageSet &inputDesc, SharedImageSet &outputDesc, std::enable_if_t< std::is_same_v< T, SharedImageSet > > *=nullptr) const

Public Member Functions inherited from NoiseGl< ImplType >
void	tagAndAssignNames (std::unordered_map< ImageMath::internal::TaggingIndex, const void * > &taggedLeaves, std::unordered_map< std::type_index, int > &countPerLeafType, const std::string &prefix) const override
	We need to tag leaves and tell unique leaves that they are responsible to define the uniforms and set the shader arguments.

void	getUniformDefinitionList (std::string &definitionList, const std::vector< int > &indices, const std::string &prefix) const override
	Collect uniform/sampler definitions.

void	getVariableDefinitionList (std::string &definitionList, const std::vector< int > &indices, const std::string &prefix) const override
	Collect variable definitions.

int	setArguments (GL::Program &p, const std::vector< int > &indicesIn, const std::string &prefix) const override
	Set uniform/sampler arguments.

std::string	evalString (bool tagAndAssign=true) const override
	Implementation of GlExprInterface interface.

std::vector< internal::GlExprInterface * >	children () override
	Used for traversing the expression tree. Contains the immediate children of node.

std::vector< const internal::GlExprInterface * >	children () const override
	Used for traversing the expression tree. Contains the immediate children of node.

Public Member Functions inherited from GlExprInterface
ExprInterface &	exprInterface ()
	Get image descriptor of the wrapped expression.

const ExprInterface &	exprInterface () const

virtual bool	setMagFilter (ImageMath::MagFilter mag)
	Set interpolation behaviour of the current leaf (only)

virtual bool	setWrap (ImageMath::Wrap wrap)
	Set interpolation behaviour of the current leaf (only)

bool	setMagFilterRecursive (ImageMath::MagFilter mag)
	Set interpolation behaviour of the current leaf and all of its children.

bool	setWrapRecursive (ImageMath::Wrap wrap)
	Set wrap behaviour of the current leaf and all of its children.

Static Public Attributes
static constexpr bool	has_variable = false

Protected Attributes
AlphaT	m_alpha

BetaT	m_beta

Protected Attributes inherited from NoiseGlBase
std::string	m_name = "uninitialized"

bool	m_tagged = false

Additional Inherited Members
Protected Member Functions inherited from NoiseGlBase
void	tagAndAssignNamesImpl (std::unordered_map< ImageMath::internal::TaggingIndex, const void * > &taggedLeaves, std::unordered_map< std::type_index, int > &countPerLeafType, const std::string &prefix, internal::uintptr_t imgDescPtr) const

void	getUniformDefinitionListImpl (std::string &definitionList, const std::vector< int > &indices, const std::string &prefix) const

void	getVariableDefinitionListImpl (std::string &definitionList, const std::vector< int > &indices, const std::string &prefix, NoiseType noiseType) const

int	setArgumentsImpl (GL::Program &p, const std::string &prefix, const vec3f &dimensions, const vec3i &stride, uint32_t seedHash) const

std::string	evalStringImpl (bool tagAndAssign, const std::string &alphaString, const std::string &betaString, int numChannels, NoiseType noiseType) const

Member Function Documentation

◆ imgDesc()

template<typename imf_img_typeT, typename AlphaT = Scalar<float>, typename BetaT = Scalar<float>>

ImageDescriptor imgDesc ( ) const

inlineoverridevirtual

Return ImageDescriptor of this expression. This reference is expected to remain the same while the class exists.

Implements ExprInterface.

◆ numImgs()

template<typename imf_img_typeT, typename AlphaT = Scalar<float>, typename BetaT = Scalar<float>>

int numImgs ( ) const

inlineoverridevirtual

Return number of images of this expression.

Implements ExprInterface.

◆ deviceStrategy()

template<typename imf_img_typeT, typename AlphaT = Scalar<float>, typename BetaT = Scalar<float>>

ImageMath::DeviceStrategy deviceStrategy ( ) const

inlineoverridevirtual

Return DeviceStrategy of this expression.

Implements ExprInterface.

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

ImFusion/ImageMath/Tpl/Noise.h

Detailed Description

Public Types

Public Member Functions

Static Public Attributes

Protected Attributes

Additional Inherited Members

Member Function Documentation

◆ imgDesc()

◆ numImgs()

◆ deviceStrategy()