View Source Evision.ShapeContextDistanceExtractor (Evision v0.1.33)
Summary
Functions
getAngularBins
getBendingEnergyWeight
getCostExtractor
getImageAppearanceWeight
getImages
getImages
getInnerRadius
getIterations
getOuterRadius
getRadialBins
getRotationInvariant
getShapeContextWeight
getStdDev
getTransformAlgorithm
Establish the number of angular bins for the Shape Context Descriptor used in the shape matching pipeline.
Set the weight of the Bending Energy in the final value of the shape distance. The bending energy definition depends on what transformation is being used to align the shapes. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy.
Set the algorithm used for building the shape context descriptor cost matrix.
Set the weight of the Image Appearance cost in the final value of the shape distance. The image appearance cost is defined as the sum of squared brightness differences in Gaussian windows around corresponding image points. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy. If this value is set to a number different from 0, is mandatory to set the images that correspond to each shape.
Set the images that correspond to each shape. This images are used in the calculation of the Image Appearance cost.
Set the inner radius of the shape context descriptor.
setIterations
Set the outer radius of the shape context descriptor.
Establish the number of radial bins for the Shape Context Descriptor used in the shape matching pipeline.
setRotationInvariant
Set the weight of the shape context distance in the final value of the shape distance. The shape context distance between two shapes is defined as the symmetric sum of shape context matching costs over best matching points. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy.
Set the value of the standard deviation for the Gaussian window for the image appearance cost.
Set the algorithm used for aligning the shapes.
Types
@type t() :: %Evision.ShapeContextDistanceExtractor{ref: reference()}
Type that represents an ShapeContextDistanceExtractor
struct.
ref.
reference()
The underlying erlang resource variable.
Functions
getAngularBins
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
int
Python prototype (for reference only):
getAngularBins() -> retval
getBendingEnergyWeight
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
float
Python prototype (for reference only):
getBendingEnergyWeight() -> retval
@spec getCostExtractor(t()) :: Evision.HistogramCostExtractor.t() | {:error, String.t()}
getCostExtractor
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
Evision.HistogramCostExtractor.t()
Python prototype (for reference only):
getCostExtractor() -> retval
getImageAppearanceWeight
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
float
Python prototype (for reference only):
getImageAppearanceWeight() -> retval
@spec getImages(t()) :: {Evision.Mat.t(), Evision.Mat.t()} | {:error, String.t()}
getImages
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- image1:
Evision.Mat.t()
. - image2:
Evision.Mat.t()
.
Python prototype (for reference only):
getImages([, image1[, image2]]) -> image1, image2
@spec getImages(t(), [{atom(), term()}, ...] | nil) :: {Evision.Mat.t(), Evision.Mat.t()} | {:error, String.t()}
getImages
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- image1:
Evision.Mat.t()
. - image2:
Evision.Mat.t()
.
Python prototype (for reference only):
getImages([, image1[, image2]]) -> image1, image2
getInnerRadius
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
float
Python prototype (for reference only):
getInnerRadius() -> retval
getIterations
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
int
Python prototype (for reference only):
getIterations() -> retval
getOuterRadius
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
float
Python prototype (for reference only):
getOuterRadius() -> retval
getRadialBins
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
int
Python prototype (for reference only):
getRadialBins() -> retval
getRotationInvariant
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
bool
Python prototype (for reference only):
getRotationInvariant() -> retval
getShapeContextWeight
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
float
Python prototype (for reference only):
getShapeContextWeight() -> retval
getStdDev
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
float
Python prototype (for reference only):
getStdDev() -> retval
@spec getTransformAlgorithm(t()) :: Evision.ShapeTransformer.t() | {:error, String.t()}
getTransformAlgorithm
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
Return
- retval:
Evision.ShapeTransformer.t()
Python prototype (for reference only):
getTransformAlgorithm() -> retval
Establish the number of angular bins for the Shape Context Descriptor used in the shape matching pipeline.
Positional Arguments
self:
Evision.ShapeContextDistanceExtractor.t()
nAngularBins:
int
.The number of angular bins in the shape context descriptor.
Python prototype (for reference only):
setAngularBins(nAngularBins) -> None
Set the weight of the Bending Energy in the final value of the shape distance. The bending energy definition depends on what transformation is being used to align the shapes. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy.
Positional Arguments
self:
Evision.ShapeContextDistanceExtractor.t()
bendingEnergyWeight:
float
.The weight of the Bending Energy in the final distance value.
Python prototype (for reference only):
setBendingEnergyWeight(bendingEnergyWeight) -> None
@spec setCostExtractor(t(), Evision.HistogramCostExtractor.t()) :: t() | {:error, String.t()}
Set the algorithm used for building the shape context descriptor cost matrix.
Positional Arguments
self:
Evision.ShapeContextDistanceExtractor.t()
comparer:
Evision.HistogramCostExtractor.t()
.Smart pointer to a HistogramCostExtractor, an algorithm that defines the cost matrix between descriptors.
Python prototype (for reference only):
setCostExtractor(comparer) -> None
Set the weight of the Image Appearance cost in the final value of the shape distance. The image appearance cost is defined as the sum of squared brightness differences in Gaussian windows around corresponding image points. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy. If this value is set to a number different from 0, is mandatory to set the images that correspond to each shape.
Positional Arguments
self:
Evision.ShapeContextDistanceExtractor.t()
imageAppearanceWeight:
float
.The weight of the appearance cost in the final distance value.
Python prototype (for reference only):
setImageAppearanceWeight(imageAppearanceWeight) -> None
@spec setImages(t(), Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in()) :: t() | {:error, String.t()}
Set the images that correspond to each shape. This images are used in the calculation of the Image Appearance cost.
Positional Arguments
self:
Evision.ShapeContextDistanceExtractor.t()
image1:
Evision.Mat.t()
.Image corresponding to the shape defined by contours1.
image2:
Evision.Mat.t()
.Image corresponding to the shape defined by contours2.
Python prototype (for reference only):
setImages(image1, image2) -> None
Set the inner radius of the shape context descriptor.
Positional Arguments
self:
Evision.ShapeContextDistanceExtractor.t()
innerRadius:
float
.The value of the inner radius.
Python prototype (for reference only):
setInnerRadius(innerRadius) -> None
setIterations
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
- iterations:
int
Python prototype (for reference only):
setIterations(iterations) -> None
Set the outer radius of the shape context descriptor.
Positional Arguments
self:
Evision.ShapeContextDistanceExtractor.t()
outerRadius:
float
.The value of the outer radius.
Python prototype (for reference only):
setOuterRadius(outerRadius) -> None
Establish the number of radial bins for the Shape Context Descriptor used in the shape matching pipeline.
Positional Arguments
self:
Evision.ShapeContextDistanceExtractor.t()
nRadialBins:
int
.The number of radial bins in the shape context descriptor.
Python prototype (for reference only):
setRadialBins(nRadialBins) -> None
setRotationInvariant
Positional Arguments
- self:
Evision.ShapeContextDistanceExtractor.t()
- rotationInvariant:
bool
Python prototype (for reference only):
setRotationInvariant(rotationInvariant) -> None
Set the weight of the shape context distance in the final value of the shape distance. The shape context distance between two shapes is defined as the symmetric sum of shape context matching costs over best matching points. The final value of the shape distance is a user-defined linear combination of the shape context distance, an image appearance distance, and a bending energy.
Positional Arguments
self:
Evision.ShapeContextDistanceExtractor.t()
shapeContextWeight:
float
.The weight of the shape context distance in the final distance value.
Python prototype (for reference only):
setShapeContextWeight(shapeContextWeight) -> None
Set the value of the standard deviation for the Gaussian window for the image appearance cost.
Positional Arguments
self:
Evision.ShapeContextDistanceExtractor.t()
sigma:
float
.Standard Deviation.
Python prototype (for reference only):
setStdDev(sigma) -> None
@spec setTransformAlgorithm(t(), Evision.ShapeTransformer.t()) :: t() | {:error, String.t()}
Set the algorithm used for aligning the shapes.
Positional Arguments
self:
Evision.ShapeContextDistanceExtractor.t()
transformer:
Evision.ShapeTransformer.t()
.Smart pointer to a ShapeTransformer, an algorithm that defines the aligning transformation.
Python prototype (for reference only):
setTransformAlgorithm(transformer) -> None