#include <ImFusion/ImageMath/Tpl/ExprBaseTpl.h>

Base class for compile-time optimized expressions (curiously recurring template pattern (CRTP)). More...

Inheritance diagram for ImFusion::ImageMath::ExprBaseTpl< ImplType >:

Detailed Description

template<typename ImplType>
class ImFusion::ImageMath::ExprBaseTpl< ImplType >

Base class for compile-time optimized expressions (curiously recurring template pattern (CRTP)).

Template Parameters

ImplType Child class

ExprBaseTpl provides a compile-time optimized interface for arithmetic expressions on ImFusion images. Arithmetic operations are combined into a ExprBaseTpl object expressing the full expression. This expression is evaluation if assigned to a Array object. No temporary images are required and each pixel is only touched once while evaluating the full expression tree at once.

Example usage for compile-time optimized expressions:

 SharedImage img1(...);
 SharedImage img2(...);
 SharedImage img3(...);
 SharedImage img4(...);
 
 // Expression wrapper for SharedImage
 Array<SharedImage> img1Expr(img1);
 // Expression wrapper for SharedImage
 Array<SharedImage> img2Expr(img2);
 // Expression wrapper for SharedImage
 Array<SharedImage> img3Expr(img3);
 // Expression wrapper for SharedImage
 Array<SharedImage> img4Expr(img4);
 
 // Expression object
 auto expr1 = (img1Expr + img2Expr) * img3Expr;
 // Evaluation of expr1 into img4
img4Expr = expr1;

Public Member Functions
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

Special functions
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.

Channel swizzling
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

Arithmetic operators
auto	operator- () const

Predefined unary operators
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

Predefined tenary operators
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.

Predefined reduction operators
	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

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

Special operations
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

Member Function Documentation

◆ polyWrapper()

template<typename ImplType>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::polyWrapper ( ) const

inline

Returns: a polymorphic expression which wraps *this

◆ uniquePolyWrapper()

template<typename ImplType>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::uniquePolyWrapper ( ) const

inline

Returns: a unique pointer to a polymorphic expression which wraps *this

◆ sharedPolyWrapper()

template<typename ImplType>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::sharedPolyWrapper ( ) const

inline

Returns: a shared pointer to a polymorphic expression which wraps *this

◆ binaryOp() [1/2]

template<typename ImplType>

template<typename Op, typename RhsT>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::binaryOp	(	const ExprBaseTpl< RhsT > &	rhs,
		const Op &	func = Op() ) const

inline

Returns: an expression which represents the binary expression Op with *this as left-hand argument and rhs as right-hand argument, respectively

Op must provide a binary functor interface, e.g.:

struct Op
{
    template <typename LhsT, typename RhsT>
    IMFUSION_STRONG_INLINE auto operator()(LhsT lhs, RhsT rhs) const
    {
        ...
    }
 
    std::string evalString(const std::string& lhsStr, const std::string& rhsStr) const
    {
        ...
    }
};

◆ binaryOp() [2/2]

template<typename ImplType>

template<typename Op, typename StringOp, typename RhsT>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::binaryOp	(	const ExprBaseTpl< RhsT > &	rhs,
		const Op &	func,
		const StringOp &	stringFunc ) const

inline

Returns: an expression which represents the binary expression given as the functions of type Op StringOp with *this as left-hand argument and rhs as right-hand argument, respectively

Should provide lambdas for CPU as well as GPU evaluation. E.g.:

expr.binaryOp([](LhsT lhs, RhsT rhs) { return lhs + rhs; }, [](const std::string& lhsStr, const std::string& rhsStr) { return "(" + lhsStr

")+(" + rhsStr + ")"; };

◆ unaryOp() [1/2]

template<typename ImplType>

template<typename Op>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::unaryOp ( const Op & func = Op() ) const

inline

Returns: an expression which represents the binary expression Op with *this as argument

Op must provide a unary functor interface, e.g.:

struct Op
{
    template <typename OperandT>
    IMFUSION_STRONG_INLINE OperandT operator()(OperandT operand) const
    {
        ...
    }
 
    std::string evalString(const std::string& operandStr) const
    {
        ...
    }
};

◆ unaryOp() [2/2]

template<typename ImplType>

template<typename Op, typename StringOp>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::unaryOp	(	const Op &	func,
		const StringOp &	stringFunc ) const

inline

Returns: an expression which represents the binary expression given as the functions of type Op StringOp with *this as left-hand argument and rhs as right-hand argument, respectively

Should provide lambdas for CPU as well as GPU evaluation. E.g.:

expr.unaryOp([](OperandT operand) { return std::abs(operand); }, [](const std::string& operandStr) { return "abs(" + operandStr ")"; };

◆ reduce()

template<typename ImplType>

template<typename Op>

reduction_type ImFusion::ImageMath::ExprBaseTpl< ImplType >::reduce ( std::vector< vec4i > * arg = nullptr ) const

inline

Returns: an expression which represents a reduction of *this using the operator Op

◆ channelSwizzle()

template<typename ImplType>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::channelSwizzle ( const std::vector< std::size_t > & indices ) const

inline

Returns: an expression which swizzles the channel indices of *this according to indices, i.e. the channel 0 gets mapped to the channel indices[0].

◆ streamChannels()

template<typename ImplType>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::streamChannels ( int numStreamedChannels ) const

inline

Returns: an expression which streams *this over numStreamedChannels channels

◆ substituteVariableWithImg()

template<typename ImplType>

template<typename T>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::substituteVariableWithImg ( T & img ) const

inline

Returns: an expression which replaces each Variable in the expression *this by img

◆ operator-()

template<typename ImplType>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::operator- ( ) const

inline

Returns: an expression of the opposite of *this

◆ storageToOriginal()

template<typename ImplType>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::storageToOriginal ( const ImageDescriptor & desc )

inline

Apply shift/scale to the operand,.

See also: ImageDescriptor::storageToOriginal

◆ originalToStorage()

template<typename ImplType>

auto ImFusion::ImageMath::ExprBaseTpl< ImplType >::originalToStorage ( const ImageDescriptor & desc )

inline

Apply shift/scale to the operand,.

See also: ImageDescriptor::originalToStorage

◆ mean()

template<typename ImplType>

Eigen::Matrix< double, Eigen::Dynamic, 1 > ImFusion::ImageMath::ExprBaseTpl< ImplType >::mean ( ) const

inline

Returns: the reduction using mean of *this

◆ l1Norm()

template<typename ImplType>

Eigen::Matrix< double, Eigen::Dynamic, 1 > ImFusion::ImageMath::ExprBaseTpl< ImplType >::l1Norm ( ) const

inline

Returns: the reduction using l1norm of *this

◆ squaredl2Norm()

template<typename ImplType>

Eigen::Matrix< double, Eigen::Dynamic, 1 > ImFusion::ImageMath::ExprBaseTpl< ImplType >::squaredl2Norm ( ) const

inline

Returns: the reduction using the squared l2-norm of *this

◆ l2Norm()

template<typename ImplType>

Eigen::Matrix< double, Eigen::Dynamic, 1 > ImFusion::ImageMath::ExprBaseTpl< ImplType >::l2Norm ( ) const

inline

Returns: the reduction using l2norm of *this

◆ lpNorm()

template<typename ImplType>

Eigen::Matrix< double, Eigen::Dynamic, 1 > ImFusion::ImageMath::ExprBaseTpl< ImplType >::lpNorm ( double p ) const

inline

Returns: the reduction using lpnorm of *this

◆ lInfNorm()

template<typename ImplType>

Eigen::Matrix< double, Eigen::Dynamic, 1 > ImFusion::ImageMath::ExprBaseTpl< ImplType >::lInfNorm ( ) const

inline

Returns: the reduction using lpnorm of *this

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

ImFusion/ImageMath/Tpl/ExprBaseTpl.h
ImFusion/ImageMath/Tpl/Array.h
ImFusion/ImageMath/Tpl/ResampleTpl.h

Detailed Description

Public Member Functions

Special functions

Channel swizzling

Arithmetic operators

Predefined unary operators

Predefined tenary operators

Predefined reduction operators

Operations that create new images

Special operations

Member Function Documentation

◆ polyWrapper()

◆ uniquePolyWrapper()

◆ sharedPolyWrapper()

◆ binaryOp() [1/2]

◆ binaryOp() [2/2]

◆ unaryOp() [1/2]

◆ unaryOp() [2/2]

◆ reduce()

◆ channelSwizzle()

◆ streamChannels()

◆ substituteVariableWithImg()

◆ operator-()

◆ storageToOriginal()

◆ originalToStorage()

◆ mean()

◆ l1Norm()

◆ squaredl2Norm()

◆ l2Norm()

◆ lpNorm()

◆ lInfNorm()