@spec getAlpha(Keyword.t()) :: any() | {:error, String.t()}

@spec getAlpha(t()) :: number() | {:error, String.t()}

getAlpha

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: float

@copybrief setAlpha @see setAlpha/2

Python prototype (for reference only):

getAlpha() -> retval

@spec getFGSLambda(Keyword.t()) :: any() | {:error, String.t()}

@spec getFGSLambda(t()) :: number() | {:error, String.t()}

getFGSLambda

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: float

@copybrief setFGSLambda @see setFGSLambda/2

Python prototype (for reference only):

getFGSLambda() -> retval

@spec getFGSSigma(Keyword.t()) :: any() | {:error, String.t()}

@spec getFGSSigma(t()) :: number() | {:error, String.t()}

getFGSSigma

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: float

@copybrief setFGSSigma @see setFGSSigma/2

Python prototype (for reference only):

getFGSSigma() -> retval

@spec getK(Keyword.t()) :: any() | {:error, String.t()}

@spec getK(t()) :: integer() | {:error, String.t()}

getK

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: integer()

@copybrief setK @see setK/2

Python prototype (for reference only):

getK() -> retval

@spec getMaxFlow(Keyword.t()) :: any() | {:error, String.t()}

@spec getMaxFlow(t()) :: number() | {:error, String.t()}

getMaxFlow

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: float

@copybrief setMaxFlow @see setMaxFlow/2

Python prototype (for reference only):

getMaxFlow() -> retval

@spec getModelIter(Keyword.t()) :: any() | {:error, String.t()}

@spec getModelIter(t()) :: integer() | {:error, String.t()}

getModelIter

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: integer()

@copybrief setModelIter @see setModelIter/2

Python prototype (for reference only):

getModelIter() -> retval

@spec getRefineModels(Keyword.t()) :: any() | {:error, String.t()}

@spec getRefineModels(t()) :: boolean() | {:error, String.t()}

getRefineModels

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: bool

@copybrief setRefineModels @see setRefineModels/2

Python prototype (for reference only):

getRefineModels() -> retval

@spec getSuperpixelMode(Keyword.t()) :: any() | {:error, String.t()}

@spec getSuperpixelMode(t()) :: integer() | {:error, String.t()}

getSuperpixelMode

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: integer()

@copybrief setSuperpixelMode @see setSuperpixelMode/2

Python prototype (for reference only):

getSuperpixelMode() -> retval

@spec getSuperpixelNNCnt(Keyword.t()) :: any() | {:error, String.t()}

@spec getSuperpixelNNCnt(t()) :: integer() | {:error, String.t()}

getSuperpixelNNCnt

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: integer()

@copybrief setSuperpixelNNCnt @see setSuperpixelNNCnt/2

Python prototype (for reference only):

getSuperpixelNNCnt() -> retval

@spec getSuperpixelRuler(Keyword.t()) :: any() | {:error, String.t()}

@spec getSuperpixelRuler(t()) :: number() | {:error, String.t()}

getSuperpixelRuler

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: float

@copybrief setSuperpixelRuler @see setSuperpixelRuler/2

Python prototype (for reference only):

getSuperpixelRuler() -> retval

@spec getSuperpixelSize(Keyword.t()) :: any() | {:error, String.t()}

@spec getSuperpixelSize(t()) :: integer() | {:error, String.t()}

getSuperpixelSize

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: integer()

@copybrief setSuperpixelSize @see setSuperpixelSize/2

Python prototype (for reference only):

getSuperpixelSize() -> retval

@spec getUseGlobalSmootherFilter(Keyword.t()) :: any() | {:error, String.t()}

@spec getUseGlobalSmootherFilter(t()) :: boolean() | {:error, String.t()}

getUseGlobalSmootherFilter

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: bool

@copybrief setUseGlobalSmootherFilter @see setUseGlobalSmootherFilter/2

Python prototype (for reference only):

getUseGlobalSmootherFilter() -> retval

@spec getUseVariationalRefinement(Keyword.t()) :: any() | {:error, String.t()}

@spec getUseVariationalRefinement(t()) :: boolean() | {:error, String.t()}

getUseVariationalRefinement

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Return

• retval: bool

@copybrief setUseVariationalRefinement @see setUseVariationalRefinement/2

Python prototype (for reference only):

getUseVariationalRefinement() -> retval

@spec setAlpha(Keyword.t()) :: any() | {:error, String.t()}

@spec setAlpha(t()) :: t() | {:error, String.t()}

Alpha is a parameter defining a global weight for transforming geodesic distance into weight.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• alpha: float.

Python prototype (for reference only):

setAlpha([, alpha]) -> None

@spec setAlpha(t(), [{:alpha, term()}] | nil) :: t() | {:error, String.t()}

Alpha is a parameter defining a global weight for transforming geodesic distance into weight.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• alpha: float.

Python prototype (for reference only):

setAlpha([, alpha]) -> None

@spec setCostMap(t(), Evision.Mat.maybe_mat_in()) :: t() | {:error, String.t()}

Interface to provide a more elaborated cost map, i.e. edge map, for the edge-aware term. This implementation is based on a rather simple gradient-based edge map estimation. To used more complex edge map estimator (e.g. StructuredEdgeDetection that has been used in the original publication) that may lead to improved accuracies, the internal edge map estimation can be bypassed here.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

• costMap: Evision.Mat.

  a type CV_32FC1 Mat is required.

@see cv::ximgproc::createSuperpixelSLIC

Python prototype (for reference only):

setCostMap(costMap) -> None

@spec setFGSLambda(Keyword.t()) :: any() | {:error, String.t()}

@spec setFGSLambda(t()) :: t() | {:error, String.t()}

Sets the respective fastGlobalSmootherFilter() parameter.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• lambda: float.

Python prototype (for reference only):

setFGSLambda([, lambda]) -> None

@spec setFGSLambda(t(), [{:lambda, term()}] | nil) :: t() | {:error, String.t()}

Sets the respective fastGlobalSmootherFilter() parameter.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• lambda: float.

Python prototype (for reference only):

setFGSLambda([, lambda]) -> None

@spec setFGSSigma(Keyword.t()) :: any() | {:error, String.t()}

@spec setFGSSigma(t()) :: t() | {:error, String.t()}

Sets the respective fastGlobalSmootherFilter() parameter.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• sigma: float.

Python prototype (for reference only):

setFGSSigma([, sigma]) -> None

@spec setFGSSigma(t(), [{:sigma, term()}] | nil) :: t() | {:error, String.t()}

Sets the respective fastGlobalSmootherFilter() parameter.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• sigma: float.

Python prototype (for reference only):

setFGSSigma([, sigma]) -> None

@spec setK(Keyword.t()) :: any() | {:error, String.t()}

@spec setK(t()) :: t() | {:error, String.t()}

K is a number of nearest-neighbor matches considered, when fitting a locally affine model for a superpixel segment. However, lower values would make the interpolation noticeably faster. The original implementation of @cite Hu2017 uses 32.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• k: integer().

Python prototype (for reference only):

setK([, k]) -> None

@spec setK(t(), [{:k, term()}] | nil) :: t() | {:error, String.t()}

K is a number of nearest-neighbor matches considered, when fitting a locally affine model for a superpixel segment. However, lower values would make the interpolation noticeably faster. The original implementation of @cite Hu2017 uses 32.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• k: integer().

Python prototype (for reference only):

setK([, k]) -> None

@spec setMaxFlow(Keyword.t()) :: any() | {:error, String.t()}

@spec setMaxFlow(t()) :: t() | {:error, String.t()}

MaxFlow is a threshold to validate the predictions using a certain piece-wise affine model. If the prediction exceeds the treshold the translational model will be applied instead.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• maxFlow: float.

Python prototype (for reference only):

setMaxFlow([, maxFlow]) -> None

@spec setMaxFlow(t(), [{:maxFlow, term()}] | nil) :: t() | {:error, String.t()}

MaxFlow is a threshold to validate the predictions using a certain piece-wise affine model. If the prediction exceeds the treshold the translational model will be applied instead.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• maxFlow: float.

Python prototype (for reference only):

setMaxFlow([, maxFlow]) -> None

@spec setModelIter(Keyword.t()) :: any() | {:error, String.t()}

@spec setModelIter(t()) :: t() | {:error, String.t()}

Parameter defining the number of iterations for piece-wise affine model estimation.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• modelIter: integer().

Python prototype (for reference only):

setModelIter([, modelIter]) -> None

@spec setModelIter(t(), [{:modelIter, term()}] | nil) :: t() | {:error, String.t()}

Parameter defining the number of iterations for piece-wise affine model estimation.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• modelIter: integer().

Python prototype (for reference only):

setModelIter([, modelIter]) -> None

@spec setRefineModels(Keyword.t()) :: any() | {:error, String.t()}

@spec setRefineModels(t()) :: t() | {:error, String.t()}

Parameter to choose wether additional refinement of the piece-wise affine models is employed.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• refineModles: bool.

Python prototype (for reference only):

setRefineModels([, refineModles]) -> None

@spec setRefineModels(t(), [{:refineModles, term()}] | nil) ::
  t() | {:error, String.t()}

Parameter to choose wether additional refinement of the piece-wise affine models is employed.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• refineModles: bool.

Python prototype (for reference only):

setRefineModels([, refineModles]) -> None

@spec setSuperpixelMode(Keyword.t()) :: any() | {:error, String.t()}

@spec setSuperpixelMode(t()) :: t() | {:error, String.t()}

Parameter to choose superpixel algorithm variant to use:

• cv::ximgproc::SLICType SLIC segments image using a desired region_size (value: 100)
• cv::ximgproc::SLICType SLICO will optimize using adaptive compactness factor (value: 101)
• cv::ximgproc::SLICType MSLIC will optimize using manifold methods resulting in more content-sensitive superpixels (value: 102).

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• mode: integer().

@see cv::ximgproc::createSuperpixelSLIC

Python prototype (for reference only):

setSuperpixelMode([, mode]) -> None

@spec setSuperpixelMode(t(), [{:mode, term()}] | nil) :: t() | {:error, String.t()}

Parameter to choose superpixel algorithm variant to use:

• cv::ximgproc::SLICType SLIC segments image using a desired region_size (value: 100)
• cv::ximgproc::SLICType SLICO will optimize using adaptive compactness factor (value: 101)
• cv::ximgproc::SLICType MSLIC will optimize using manifold methods resulting in more content-sensitive superpixels (value: 102).

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• mode: integer().

@see cv::ximgproc::createSuperpixelSLIC

Python prototype (for reference only):

setSuperpixelMode([, mode]) -> None

@spec setSuperpixelNNCnt(Keyword.t()) :: any() | {:error, String.t()}

@spec setSuperpixelNNCnt(t()) :: t() | {:error, String.t()}

Parameter defines the number of nearest-neighbor matches for each superpixel considered, when fitting a locally affine model.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• spNN: integer().

Python prototype (for reference only):

setSuperpixelNNCnt([, spNN]) -> None

@spec setSuperpixelNNCnt(t(), [{:spNN, term()}] | nil) :: t() | {:error, String.t()}

Parameter defines the number of nearest-neighbor matches for each superpixel considered, when fitting a locally affine model.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• spNN: integer().

Python prototype (for reference only):

setSuperpixelNNCnt([, spNN]) -> None

@spec setSuperpixelRuler(Keyword.t()) :: any() | {:error, String.t()}

@spec setSuperpixelRuler(t()) :: t() | {:error, String.t()}

Parameter to tune enforcement of superpixel smoothness factor used for oversegmentation.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• ruler: float.

@see cv::ximgproc::createSuperpixelSLIC

Python prototype (for reference only):

setSuperpixelRuler([, ruler]) -> None

@spec setSuperpixelRuler(t(), [{:ruler, term()}] | nil) :: t() | {:error, String.t()}

Parameter to tune enforcement of superpixel smoothness factor used for oversegmentation.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• ruler: float.

@see cv::ximgproc::createSuperpixelSLIC

Python prototype (for reference only):

setSuperpixelRuler([, ruler]) -> None

@spec setSuperpixelSize(Keyword.t()) :: any() | {:error, String.t()}

@spec setSuperpixelSize(t()) :: t() | {:error, String.t()}

Get the internal cost, i.e. edge map, used for estimating the edge-aware term.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• spSize: integer().

@see setCostMap/2

Python prototype (for reference only):

setSuperpixelSize([, spSize]) -> None

@spec setSuperpixelSize(t(), [{:spSize, term()}] | nil) :: t() | {:error, String.t()}

Get the internal cost, i.e. edge map, used for estimating the edge-aware term.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• spSize: integer().

@see setCostMap/2

Python prototype (for reference only):

setSuperpixelSize([, spSize]) -> None

@spec setUseGlobalSmootherFilter(Keyword.t()) :: any() | {:error, String.t()}

@spec setUseGlobalSmootherFilter(t()) :: t() | {:error, String.t()}

Sets whether the fastGlobalSmootherFilter() post-processing is employed.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• use_FGS: bool.

Python prototype (for reference only):

setUseGlobalSmootherFilter([, use_FGS]) -> None

@spec setUseGlobalSmootherFilter(t(), [{:use_FGS, term()}] | nil) ::
  t() | {:error, String.t()}

Sets whether the fastGlobalSmootherFilter() post-processing is employed.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• use_FGS: bool.

Python prototype (for reference only):

setUseGlobalSmootherFilter([, use_FGS]) -> None

@spec setUseVariationalRefinement(Keyword.t()) :: any() | {:error, String.t()}

@spec setUseVariationalRefinement(t()) :: t() | {:error, String.t()}

Parameter to choose wether the VariationalRefinement post-processing is employed.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• use_variational_refinement: bool.

Python prototype (for reference only):

setUseVariationalRefinement([, use_variational_refinement]) -> None

@spec setUseVariationalRefinement(t(), [{:use_variational_refinement, term()}] | nil) ::
  t() | {:error, String.t()}

Parameter to choose wether the VariationalRefinement post-processing is employed.

Positional Arguments

• self: Evision.XImgProc.RICInterpolator.t()

Keyword Arguments

• use_variational_refinement: bool.

Python prototype (for reference only):

setUseVariationalRefinement([, use_variational_refinement]) -> None