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edge

Masks derived from edge detectors.

Modules:

  • _1d –

    1D matrices

  • _3x3 –

    2D matrices.

  • _5x5 –

    2D matrices.

  • _abstract –

Classes:

  • ASobel –

    Modified Sobel-Feldman operator from AWarpSharp.

  • Cross –

    "HotDoG" Operator from AVS ExTools by Dogway.

  • EdgeDetect –

    Abstract edge detection interface.

  • EuclideanDistance –
  • ExKirsch –

    Extended Russell Kirsch compass operator. 5x5 matrices.

  • ExLaplacian1 –

    Extended Pierre-Simon de Laplace operator, 1st implementation.

  • ExLaplacian2 –

    Extended Pierre-Simon de Laplace operator, 2nd implementation.

  • ExLaplacian3 –

    Extended Pierre-Simon de Laplace operator, 3rd implementation.

  • ExLaplacian4 –

    Extended Pierre-Simon de Laplace operator, 4th implementation.

  • ExPrewitt –

    Extended Judith M. S. Prewitt operator.

  • ExSobel –

    Extended Sobel-Feldman operator.

  • FDoG –

    Flow-based Difference of Gaussian

  • FDoGTCanny –

    Flow-based Difference of Gaussian TCanny Vapoursynth plugin.

  • Farid –

    Farid & Simoncelli operator.

  • FreyChen –

    Chen Frei operator. 3x3 matrices properly implemented.

  • FreyChenG41 –

    "Chen Frei" operator. 3x3 matrices from G41Fun.

  • Kayyali –

    Kayyali operator.

  • Kirsch –

    Russell Kirsch compass operator.

  • KirschTCanny –

    Russell Kirsch compass TCanny Vapoursynth plugin operator.

  • Kroon –

    Dirk-Jan Kroon operator.

  • KroonTCanny –

    Dirk-Jan Kroon TCanny Vapoursynth plugin operator.

  • Laplacian1 –

    Pierre-Simon de Laplace operator 1st implementation.

  • Laplacian2 –

    Pierre-Simon de Laplace operator 2nd implementation.

  • Laplacian3 –

    Pierre-Simon de Laplace operator 3rd implementation.

  • Laplacian4 –

    Pierre-Simon de Laplace operator 4th implementation.

  • LoG –

    Laplacian of Gaussian operator.

  • MagDirection –

    Direction of magnitude calculation.

  • MagnitudeMatrix –
  • Matrix1D –
  • Matrix3x3 –
  • Matrix5x5 –
  • MatrixEdgeDetect –
  • Max –
  • MinMax –

    Min/max mask with separate luma/chroma radii.

  • Prewitt –

    Judith M. S. Prewitt operator.

  • PrewittStd –

    Judith M. S. Prewitt Vapoursynth plugin operator.

  • PrewittTCanny –

    Judith M. S. Prewitt TCanny plugin operator.

  • RScharr –

    Refined H. Scharr operator to more accurately calculate

  • RidgeDetect –
  • Robinson3 –

    Robinson compass operator level 3.

  • Robinson5 –

    Robinson compass operator level 5.

  • Scharr –

    Original H. Scharr optimised operator which attempts

  • ScharrTCanny –

    H. Scharr optimised TCanny Vapoursynth plugin operator.

  • SingleMatrix –
  • Sobel –

    Sobel-Feldman operator.

  • SobelStd –

    Sobel-Feldman Vapoursynth plugin operator.

  • SobelTCanny –

    Sobel-Feldman Vapoursynth plugin operator.

  • TEdge –

    (TEdgeMasktype=2) Avisynth plugin.

  • TEdgeTedgemask –

    (tedgemask.TEdgeMask(threshold=0.0, type=2)) Vapoursynth plugin.

  • TheToof –

    TheToof compass operator from SharpAAMCmod.

  • Tritical –

    Operator used in Tritical's original TCanny filter.

  • TriticalTCanny –

    Operator used in Tritical's original TCanny filter.

Functions:

Attributes:

EdgeDetectLike module-attribute 

EdgeDetectLike: TypeAlias = type[EdgeDetect] | EdgeDetect | str

Type alias for anything that can resolve to a EdgeDetect.

This includes
  • A string identifier.
  • A class type subclassing EdgeDetect.
  • An instance of a EdgeDetect.

EdgeDetectT module-attribute 

EdgeDetectT = EdgeDetectLike

Deprecated alias of EdgeDetectLike.

RidgeDetectLike module-attribute 

RidgeDetectLike: TypeAlias = type[RidgeDetect] | RidgeDetect | str

Type alias for anything that can resolve to a RidgeDetect.

This includes
  • A string identifier.
  • A class type subclassing RidgeDetect.
  • An instance of a RidgeDetect.

RidgeDetectT module-attribute 

RidgeDetectT = RidgeDetectLike

Deprecated alias of RidgeDetectLike.

ASobel 

ASobel(**kwargs: Any)

Bases: Matrix3x3, EdgeDetect

Modified Sobel-Feldman operator from AWarpSharp.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Cross 

Cross(**kwargs: Any)

Bases: RidgeDetect, EuclideanDistance, Matrix3x3

"HotDoG" Operator from AVS ExTools by Dogway. Plain and simple cross first order derivative.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [1, 0, 0, 0, 0, 0, 0, 0, -1],
    [0, 0, -1, 0, 0, 0, 1, 0, 0],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

EdgeDetect 

EdgeDetect(**kwargs: Any)

Bases: ABC

Abstract edge detection interface.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

EuclideanDistance 

EuclideanDistance(**kwargs: Any)

Bases: MatrixEdgeDetect, ABC

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ExKirsch 

ExKirsch(mag_directions: MagDirection = ALL, **kwargs: Any)

Bases: MagnitudeMatrix, Max

Extended Russell Kirsch compass operator. 5x5 matrices.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, mag_directions: MagDirection = MagDirection.ALL, **kwargs: Any) -> None:
    super().__init__(**kwargs)

    self.mag_directions = mag_directions

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

mag_directions instance-attribute 

mag_directions = mag_directions

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [
        9,
        9,
        9,
        9,
        9,
        9,
        5,
        5,
        5,
        9,
        -7,
        -3,
        0,
        -3,
        -7,
        -7,
        -3,
        -3,
        -3,
        -7,
        -7,
        -7,
        -7,
        -7,
        -7,
    ],
    [
        9,
        9,
        9,
        9,
        -7,
        9,
        5,
        5,
        -3,
        -7,
        9,
        5,
        0,
        -3,
        -7,
        9,
        -3,
        -3,
        -3,
        -7,
        -7,
        -7,
        -7,
        -7,
        -7,
    ],
    [
        9,
        9,
        -7,
        -7,
        -7,
        9,
        5,
        -3,
        -3,
        -7,
        9,
        5,
        0,
        -3,
        -7,
        9,
        5,
        -3,
        -3,
        -7,
        9,
        9,
        -7,
        -7,
        -7,
    ],
    [
        -7,
        -7,
        -7,
        -7,
        -7,
        9,
        -3,
        -3,
        -3,
        -7,
        9,
        5,
        0,
        -3,
        -7,
        9,
        5,
        5,
        -3,
        -7,
        9,
        9,
        9,
        9,
        -7,
    ],
    [
        -7,
        -7,
        -7,
        -7,
        -7,
        -7,
        -3,
        -3,
        -3,
        -7,
        -7,
        -3,
        0,
        -3,
        -7,
        9,
        5,
        5,
        5,
        9,
        9,
        9,
        9,
        9,
        9,
    ],
    [
        -7,
        -7,
        -7,
        -7,
        -7,
        -7,
        -3,
        -3,
        -3,
        9,
        -7,
        -3,
        0,
        5,
        9,
        -7,
        -3,
        5,
        5,
        9,
        -7,
        9,
        9,
        9,
        9,
    ],
    [
        -7,
        -7,
        -7,
        9,
        9,
        -7,
        -3,
        -3,
        5,
        9,
        -7,
        -3,
        0,
        5,
        9,
        -7,
        -3,
        -3,
        5,
        9,
        -7,
        -7,
        -7,
        9,
        9,
    ],
    [
        -7,
        9,
        9,
        9,
        9,
        -7,
        -3,
        5,
        5,
        9,
        -7,
        -3,
        0,
        5,
        9,
        -7,
        -3,
        -3,
        -3,
        9,
        -7,
        -7,
        -7,
        -7,
        -7,
    ],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ExLaplacian1 

ExLaplacian1(**kwargs: Any)

Bases: SingleMatrix, Matrix5x5

Extended Pierre-Simon de Laplace operator, 1st implementation.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [
        0,
        0,
        -1,
        0,
        0,
        0,
        0,
        -1,
        0,
        0,
        -1,
        -1,
        8,
        -1,
        -1,
        0,
        0,
        -1,
        0,
        0,
        0,
        0,
        -1,
        0,
        0,
    ]
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ExLaplacian2 

ExLaplacian2(**kwargs: Any)

Bases: SingleMatrix, Matrix5x5

Extended Pierre-Simon de Laplace operator, 2nd implementation.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [
        0,
        1,
        -1,
        1,
        0,
        1,
        1,
        -4,
        1,
        1,
        -1,
        -4,
        8,
        -4,
        -1,
        1,
        1,
        -4,
        1,
        1,
        0,
        1,
        -1,
        1,
        0,
    ]
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ExLaplacian3 

ExLaplacian3(**kwargs: Any)

Bases: SingleMatrix, Matrix5x5

Extended Pierre-Simon de Laplace operator, 3rd implementation.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [
        -1,
        1,
        -1,
        1,
        -1,
        1,
        2,
        -4,
        2,
        1,
        -1,
        -4,
        8,
        -4,
        -1,
        1,
        2,
        -4,
        2,
        1,
        -1,
        1,
        -1,
        1,
        -1,
    ]
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ExLaplacian4 

ExLaplacian4(**kwargs: Any)

Bases: SingleMatrix, Matrix5x5

Extended Pierre-Simon de Laplace operator, 4th implementation.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        24,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
        -1,
    ]
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ExPrewitt 

ExPrewitt(**kwargs: Any)

Bases: RidgeDetect, EuclideanDistance, Matrix5x5

Extended Judith M. S. Prewitt operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [
        2,
        1,
        0,
        -1,
        -2,
        2,
        1,
        0,
        -1,
        -2,
        2,
        1,
        0,
        -1,
        -2,
        2,
        1,
        0,
        -1,
        -2,
        2,
        1,
        0,
        -1,
        -2,
    ],
    [
        2,
        2,
        2,
        2,
        2,
        1,
        1,
        1,
        1,
        1,
        0,
        0,
        0,
        0,
        0,
        -1,
        -1,
        -1,
        -1,
        -1,
        -2,
        -2,
        -2,
        -2,
        -2,
    ],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ExSobel 

ExSobel(**kwargs: Any)

Bases: RidgeDetect, EuclideanDistance, Matrix5x5

Extended Sobel-Feldman operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [
        2,
        1,
        0,
        -1,
        -2,
        2,
        1,
        0,
        -1,
        -2,
        4,
        2,
        0,
        -2,
        -4,
        2,
        1,
        0,
        -1,
        -2,
        2,
        1,
        0,
        -1,
        -2,
    ],
    [
        2,
        2,
        4,
        2,
        2,
        1,
        1,
        2,
        1,
        1,
        0,
        0,
        0,
        0,
        0,
        -1,
        -1,
        -2,
        -1,
        -1,
        -2,
        -2,
        -4,
        -2,
        -2,
    ],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

FDoG 

FDoG(**kwargs: Any)

Bases: RidgeDetect, EuclideanDistance, Matrix5x5

Flow-based Difference of Gaussian

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = [2, 2]

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [
        1,
        1,
        0,
        -1,
        -1,
        2,
        2,
        0,
        -2,
        -2,
        3,
        3,
        0,
        -3,
        -3,
        2,
        2,
        0,
        -2,
        -2,
        1,
        1,
        0,
        -1,
        -1,
    ],
    [
        1,
        2,
        3,
        2,
        1,
        1,
        2,
        3,
        2,
        1,
        0,
        0,
        0,
        0,
        0,
        -1,
        -2,
        -3,
        -2,
        -1,
        -1,
        -2,
        -3,
        -2,
        -1,
    ],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

FDoGTCanny 

FDoGTCanny(**kwargs: Any)

Bases: Matrix5x5, EdgeDetect

Flow-based Difference of Gaussian TCanny Vapoursynth plugin.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Farid 

Farid(**kwargs: Any)

Bases: NormalizeProcessor, RidgeDetect, EuclideanDistance, Matrix5x5

Farid & Simoncelli operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [
        0.004127602875174862,
        0.027308149775363867,
        0.04673225765917656,
        0.027308149775363867,
        0.004127602875174862,
        0.010419993699470744,
        0.06893849946536831,
        0.11797400212587895,
        0.06893849946536831,
        0.010419993699470744,
        0.0,
        0.0,
        0.0,
        0.0,
        0.0,
        -0.010419993699470744,
        -0.06893849946536831,
        -0.11797400212587895,
        -0.06893849946536831,
        -0.010419993699470744,
        -0.004127602875174862,
        -0.027308149775363867,
        -0.04673225765917656,
        -0.027308149775363867,
        -0.004127602875174862,
    ],
    [
        0.004127602875174862,
        0.010419993699470744,
        0.0,
        -0.010419993699470744,
        -0.004127602875174862,
        0.027308149775363867,
        0.06893849946536831,
        0.0,
        -0.06893849946536831,
        -0.027308149775363867,
        0.04673225765917656,
        0.11797400212587895,
        0.0,
        -0.11797400212587895,
        -0.04673225765917656,
        0.027308149775363867,
        0.06893849946536831,
        0.0,
        -0.06893849946536831,
        -0.027308149775363867,
        0.004127602875174862,
        0.010419993699470744,
        0.0,
        -0.010419993699470744,
        -0.004127602875174862,
    ],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

FreyChen 

FreyChen(**kwargs: Any)

Bases: NormalizeProcessor, MatrixEdgeDetect

Chen Frei operator. 3x3 matrices properly implemented.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = [
    2 * sqrt2,
    2 * sqrt2,
    2 * sqrt2,
    2 * sqrt2,
    2,
    2,
    6,
    6,
    3,
]

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [1, sqrt2, 1, 0, 0, 0, -1, -sqrt2, -1],
    [1, 0, -1, sqrt2, 0, -sqrt2, 1, 0, -1],
    [0, -1, sqrt2, 1, 0, -1, -sqrt2, 1, 0],
    [sqrt2, -1, 0, -1, 0, 1, 0, 1, -sqrt2],
    [0, 1, 0, -1, 0, -1, 0, 1, 0],
    [-1, 0, 1, 0, 0, 0, 1, 0, -1],
    [1, -2, 1, -2, 4, -2, 1, -2, 1],
    [-2, 1, -2, 1, 4, 1, -2, 1, -2],
    [1, 1, 1, 1, 1, 1, 1, 1, 1],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

sqrt2 class-attribute instance-attribute 

sqrt2 = sqrt(2)

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

FreyChenG41 

FreyChenG41(**kwargs: Any)

Bases: RidgeDetect, EuclideanDistance, Matrix3x3

"Chen Frei" operator. 3x3 matrices from G41Fun.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = [7, 7]

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [-7, 0, 7, -10, 0, 10, -7, 0, 7],
    [-7, -10, -7, 0, 0, 0, 7, 10, 7],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

Kayyali 

Kayyali(**kwargs: Any)

Bases: SingleMatrix, Matrix3x3

Kayyali operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [[6, 0, -6, 0, 0, 0, -6, 0, 6]]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Kirsch 

Kirsch(mag_directions: MagDirection = ALL, **kwargs: Any)

Bases: MagnitudeMatrix, Max, Matrix3x3

Russell Kirsch compass operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, mag_directions: MagDirection = MagDirection.ALL, **kwargs: Any) -> None:
    super().__init__(**kwargs)

    self.mag_directions = mag_directions

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

mag_directions instance-attribute 

mag_directions = mag_directions

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [5, 5, 5, -3, 0, -3, -3, -3, -3],
    [5, 5, -3, 5, 0, -3, -3, -3, -3],
    [5, -3, -3, 5, 0, -3, 5, -3, -3],
    [-3, -3, -3, 5, 0, -3, 5, 5, -3],
    [-3, -3, -3, -3, 0, -3, 5, 5, 5],
    [-3, -3, -3, -3, 0, 5, -3, 5, 5],
    [-3, -3, 5, -3, 0, 5, -3, -3, 5],
    [-3, 5, 5, -3, 0, 5, -3, -3, -3],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

KirschTCanny 

KirschTCanny(**kwargs: Any)

Bases: Matrix3x3, EdgeDetect

Russell Kirsch compass TCanny Vapoursynth plugin operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Kroon 

Kroon(**kwargs: Any)

Bases: RidgeDetect, EuclideanDistance, Matrix3x3

Dirk-Jan Kroon operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = [17, 17]

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [-17, 0, 17, -61, 0, 61, -17, 0, 17],
    [-17, -61, -17, 0, 0, 0, 17, 61, 17],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

KroonTCanny 

KroonTCanny(**kwargs: Any)

Bases: Matrix3x3, EdgeDetect

Dirk-Jan Kroon TCanny Vapoursynth plugin operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Laplacian1 

Laplacian1(**kwargs: Any)

Bases: SingleMatrix, Matrix3x3

Pierre-Simon de Laplace operator 1st implementation.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [[0, -1, 0, -1, 4, -1, 0, -1, 0]]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Laplacian2 

Laplacian2(**kwargs: Any)

Bases: SingleMatrix, Matrix3x3

Pierre-Simon de Laplace operator 2nd implementation.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [[1, -2, 1, -2, 4, -2, 1, -2, 1]]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Laplacian3 

Laplacian3(**kwargs: Any)

Bases: SingleMatrix, Matrix3x3

Pierre-Simon de Laplace operator 3rd implementation.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [[2, -1, 2, -1, -4, -1, 2, -1, 2]]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Laplacian4 

Laplacian4(**kwargs: Any)

Bases: SingleMatrix, Matrix3x3

Pierre-Simon de Laplace operator 4th implementation.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [[-1, -1, -1, -1, 8, -1, -1, -1, -1]]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

LoG 

LoG(**kwargs: Any)

Bases: SingleMatrix, Matrix5x5

Laplacian of Gaussian operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [
        0,
        0,
        -1,
        0,
        0,
        0,
        -1,
        -2,
        -1,
        0,
        -1,
        -2,
        16,
        -2,
        -1,
        0,
        -1,
        -2,
        -1,
        0,
        0,
        0,
        -1,
        0,
        0,
    ]
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

MagDirection

Bases: IntFlag

Direction of magnitude calculation.

Methods:

Attributes:

ALL class-attribute instance-attribute 

ALL = N | NW | W | SW | S | SE | E | NE

AXIS class-attribute instance-attribute 

AXIS = N | W | S | E

CORNERS class-attribute instance-attribute 

CORNERS = NW | SW | SE | NE

E class-attribute instance-attribute 

E = auto()

EAST class-attribute instance-attribute 

EAST = E | NE | SE

N class-attribute instance-attribute 

N = auto()

NE class-attribute instance-attribute 

NE = auto()

NORTH class-attribute instance-attribute 

NORTH = N | NW | NE

NW class-attribute instance-attribute 

NW = auto()

S class-attribute instance-attribute 

S = auto()

SE class-attribute instance-attribute 

SE = auto()

SOUTH class-attribute instance-attribute 

SOUTH = S | SW | SE

SW class-attribute instance-attribute 

SW = auto()

W class-attribute instance-attribute 

W = auto()

WEST class-attribute instance-attribute 

WEST = W | NW | SW

select_matrices 

select_matrices(matrices: Sequence[T]) -> Sequence[T]
Source code in vsmasktools/edge/_abstract.py 
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def select_matrices(self, matrices: Sequence[T]) -> Sequence[T]:
    # In Python <3.11, composite flags are included in MagDirection's
    # collection and iteration interfaces.
    primary_flags = [flag for flag in MagDirection if flag != 0 and flag & (flag - 1) == 0]
    assert len(matrices) == len(primary_flags) and self

    return [matrix for flag, matrix in zip(primary_flags, matrices) if self & flag]

MagnitudeMatrix 

MagnitudeMatrix(mag_directions: MagDirection = ALL, **kwargs: Any)

Bases: MatrixEdgeDetect

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, mag_directions: MagDirection = MagDirection.ALL, **kwargs: Any) -> None:
    super().__init__(**kwargs)

    self.mag_directions = mag_directions

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

mag_directions instance-attribute 

mag_directions = mag_directions

matrices class-attribute 

matrices: Sequence[Sequence[float]]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Matrix1D 

Matrix1D(**kwargs: Any)

Bases: EdgeDetect, ABC

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Matrix3x3 

Matrix3x3(**kwargs: Any)

Bases: EdgeDetect, ABC

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Matrix5x5 

Matrix5x5(**kwargs: Any)

Bases: EdgeDetect, ABC

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

MatrixEdgeDetect 

MatrixEdgeDetect(**kwargs: Any)

Bases: EdgeDetect

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Max 

Max(**kwargs: Any)

Bases: MatrixEdgeDetect, ABC

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

MinMax 

MinMax(rady: int = 2, radc: int = 0, **kwargs: Any)

Bases: EdgeDetect

Min/max mask with separate luma/chroma radii.

Methods:

Attributes:

Source code in vsmasktools/edge/_3x3.py 
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def __init__(self, rady: int = 2, radc: int = 0, **kwargs: Any) -> None:
    self.rady = rady
    self.radc = radc
    super().__init__(**kwargs)

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

radc instance-attribute 

radc: int = radc

rady instance-attribute 

rady: int = rady

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Prewitt 

Prewitt(**kwargs: Any)

Bases: RidgeDetect, EuclideanDistance, Matrix3x3

Judith M. S. Prewitt operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [1, 0, -1, 1, 0, -1, 1, 0, -1],
    [1, 1, 1, 0, 0, 0, -1, -1, -1],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

PrewittStd 

PrewittStd(**kwargs: Any)

Bases: Matrix3x3, EdgeDetect

Judith M. S. Prewitt Vapoursynth plugin operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

PrewittTCanny 

PrewittTCanny(**kwargs: Any)

Bases: Matrix3x3, EdgeDetect

Judith M. S. Prewitt TCanny plugin operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

RScharr 

RScharr(**kwargs: Any)

Bases: RidgeDetect, EuclideanDistance, Matrix3x3

Refined H. Scharr operator to more accurately calculate 1st derivatives for a 3x3 kernel with coeffs 47 and 162.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = [47, 47]

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [-47, 0, 47, -162, 0, 162, -47, 0, 47],
    [-47, -162, -47, 0, 0, 0, 47, 162, 47],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

RidgeDetect 

RidgeDetect(**kwargs: Any)

Bases: MatrixEdgeDetect

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

Robinson3 

Robinson3(mag_directions: MagDirection = ALL, **kwargs: Any)

Bases: MagnitudeMatrix, Max, Matrix3x3

Robinson compass operator level 3.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, mag_directions: MagDirection = MagDirection.ALL, **kwargs: Any) -> None:
    super().__init__(**kwargs)

    self.mag_directions = mag_directions

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

mag_directions instance-attribute 

mag_directions = mag_directions

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [1, 1, 1, 0, 0, 0, -1, -1, -1],
    [1, 1, 0, 1, 0, -1, 0, -1, -1],
    [1, 0, -1, 1, 0, -1, 1, 0, -1],
    [0, -1, -1, 1, 0, -1, 1, 1, 0],
    [],
    [],
    [],
    [],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Robinson5 

Robinson5(mag_directions: MagDirection = ALL, **kwargs: Any)

Bases: MagnitudeMatrix, Max, Matrix3x3

Robinson compass operator level 5.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, mag_directions: MagDirection = MagDirection.ALL, **kwargs: Any) -> None:
    super().__init__(**kwargs)

    self.mag_directions = mag_directions

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

mag_directions instance-attribute 

mag_directions = mag_directions

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [1, 2, 1, 0, 0, 0, -1, -2, -1],
    [2, 1, 0, 1, 0, -1, 0, -1, -2],
    [1, 0, -1, 2, 0, -2, 1, 0, -1],
    [0, -1, -2, 1, 0, -1, 2, 1, 0],
    [],
    [],
    [],
    [],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Scharr 

Scharr(**kwargs: Any)

Bases: RidgeDetect, EuclideanDistance, Matrix3x3

Original H. Scharr optimised operator which attempts to achieve the perfect rotational symmetry with coefficients 3 and 10.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = [3, 3]

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [-3, 0, 3, -10, 0, 10, -3, 0, 3],
    [-3, -10, -3, 0, 0, 0, 3, 10, 3],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ScharrTCanny 

ScharrTCanny(**kwargs: Any)

Bases: Matrix3x3, EdgeDetect

H. Scharr optimised TCanny Vapoursynth plugin operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

SingleMatrix 

SingleMatrix(**kwargs: Any)

Bases: MatrixEdgeDetect, ABC

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Sobel 

Sobel(**kwargs: Any)

Bases: RidgeDetect, EuclideanDistance, Matrix3x3

Sobel-Feldman operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [1, 0, -1, 2, 0, -2, 1, 0, -1],
    [1, 2, 1, 0, 0, 0, -1, -2, -1],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

SobelStd 

SobelStd(**kwargs: Any)

Bases: Matrix3x3, EdgeDetect

Sobel-Feldman Vapoursynth plugin operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

SobelTCanny 

SobelTCanny(**kwargs: Any)

Bases: Matrix3x3, EdgeDetect

Sobel-Feldman Vapoursynth plugin operator.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

TEdge 

TEdge(**kwargs: Any)

Bases: EuclideanDistance, Matrix1D

(TEdgeMasktype=2) Avisynth plugin.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = [62, 62]

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [12, -74, 0, 74, -12],
    [-12, 74, 0, -74, 12],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = ['h', 'v']

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

TEdgeTedgemask 

TEdgeTedgemask(**kwargs: Any)

Bases: Matrix1D, EdgeDetect

(tedgemask.TEdgeMask(threshold=0.0, type=2)) Vapoursynth plugin.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

TheToof 

TheToof(mag_directions: MagDirection = ALL, **kwargs: Any)

Bases: MagnitudeMatrix, Max, Matrix3x3

TheToof compass operator from SharpAAMCmod.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, mag_directions: MagDirection = MagDirection.ALL, **kwargs: Any) -> None:
    super().__init__(**kwargs)

    self.mag_directions = mag_directions

divisors class-attribute 

divisors: Sequence[float] | None = [4] * 4

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

mag_directions instance-attribute 

mag_directions = mag_directions

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [5, 10, 5, 0, 0, 0, -5, -10, -5],
    [10, 5, 0, 5, 0, -5, 0, -5, -10],
    [5, 0, -5, 10, 0, -10, 5, 0, -5],
    [0, -5, -10, 5, 0, -5, 10, 5, 0],
    [],
    [],
    [],
    [],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

Tritical 

Tritical(**kwargs: Any)

Bases: RidgeDetect, EuclideanDistance, Matrix3x3

Operator used in Tritical's original TCanny filter. Plain and simple orthogonal first order derivative.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

divisors class-attribute 

divisors: Sequence[float] | None = None

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

matrices class-attribute 

matrices: Sequence[Sequence[float]] = [
    [0, 0, 0, -1, 0, 1, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0, -1, 0],
]

mode_types class-attribute 

mode_types: Sequence[str] | None = None

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

ridgemask 

ridgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> VideoNode

Makes ridge mask based on convolution kernel.

The resulting mask can be thresholded with lthr, hthr and multiplied with multi. Using a 32-bit float clip is recommended.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    clamp: Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • VideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
def ridgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Makes ridge mask based on convolution kernel.

    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.
    Using a 32-bit float clip is recommended.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """

    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess_ridge(clip)

    mask = self._compute_ridge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess_ridge(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

TriticalTCanny 

TriticalTCanny(**kwargs: Any)

Bases: Matrix3x3, EdgeDetect

Operator used in Tritical's original TCanny filter. Plain and simple orthogonal first order derivative.

Methods:

Attributes:

Source code in vsmasktools/edge/_abstract.py 
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def __init__(self, **kwargs: Any) -> None:
    super().__init__()

    self.kwargs = kwargs

kwargs class-attribute instance-attribute 

kwargs: KwargsT | None = kwargs

depth_scale classmethod 

depth_scale(
    clip: VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def depth_scale(
    cls, clip: vs.VideoNode, bitdepth: VideoFormatLike | HoldsVideoFormat | int
) -> ConstantFormatVideoNode:
    assert check_variable(clip, cls)

    fmt = get_video_format(bitdepth)

    if fmt.sample_type == vs.INTEGER:
        return norm_expr(
            clip,
            ("x abs {peak} *", "x abs {peak} * neutral -"),
            format=fmt,
            func=cls,
            peak=get_peak_value(bitdepth, range_in=ColorRange.FULL),
        )
    return clip

edgemask 

edgemask(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> ConstantFormatVideoNode

Makes edge mask based on convolution kernel. The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

Parameters:

  • clip

    (VideoNode) –

    Source clip

  • lthr

    (float, default: 0.0 ) –

    Low threshold. Anything below lthr will be set to 0

  • hthr

    (float | None, default: None ) –

    High threshold. Anything above hthr will be set to the range max

  • multi

    (float, default: 1.0 ) –

    Multiply all pixels by this before thresholding

  • clamp

    (bool | tuple[float, float] | list[tuple[float, float]], default: False ) –

    Clamp to legal values if True or specified range (low, high)

  • planes

    (Planes, default: None ) –

    Which planes to process.

Returns:

  • ConstantFormatVideoNode –

    Mask clip

Source code in vsmasktools/edge/_abstract.py 
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@inject_self
@inject_kwargs_params
def edgemask(
    self,
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> ConstantFormatVideoNode:
    """
    Makes edge mask based on convolution kernel.
    The resulting mask can be thresholded with lthr, hthr and multiplied with multi.

    Args:
        clip: Source clip
        lthr: Low threshold. Anything below lthr will be set to 0
        hthr: High threshold. Anything above hthr will be set to the range max
        multi: Multiply all pixels by this before thresholding
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        Mask clip
    """
    assert check_variable(clip, self.__class__)

    clip_p = self._preprocess(clip)

    mask = self._compute_edge_mask(clip_p, planes=planes, **kwargs)

    mask = self._postprocess(mask, clip)

    return self._finalize_mask(mask, lthr, hthr, multi, clamp, planes)

ensure_obj classmethod 

ensure_obj(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> Self
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def ensure_obj(cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None) -> Self:
    return _base_ensure_obj(cls, value, func_except)

from_param classmethod 

from_param(
    value: type[Self] | Self | str | None = None,
    /,
    func_except: FuncExcept | None = None,
) -> type[Self]
Source code in vsmasktools/edge/_abstract.py 
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@classmethod
def from_param(
    cls, value: type[Self] | Self | str | None = None, /, func_except: FuncExcept | None = None
) -> type[Self]:
    return _base_from_param(cls, value, cls._err_class, func_except)

get_all_edge_detects 

get_all_edge_detects(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> list[ConstantFormatVideoNode]

Returns all the EdgeDetect subclasses

Parameters:

Returns:

  • list[ConstantFormatVideoNode] –

    A list of edge masks

Source code in vsmasktools/edge/_abstract.py 
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def get_all_edge_detects(
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> list[ConstantFormatVideoNode]:
    """
    Returns all the EdgeDetect subclasses

    Args:
        clip: Source clip
        lthr: See [EdgeDetect.get_mask][vsmasktools.edge.EdgeDetect.edgemask]
        hthr: See [EdgeDetect.get_mask][vsmasktools.edge.EdgeDetect.edgemask]
        multi: See [EdgeDetect.get_mask][vsmasktools.edge.EdgeDetect.edgemask]
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        A list of edge masks
    """
    # https://github.com/python/mypy/issues/4717
    all_subclasses = {
        s
        for s in get_subclasses(EdgeDetect)  # type: ignore[type-abstract]
        if not isabstract(s) and s.__module__.split(".")[-1] != "_abstract"
    }

    out = list[ConstantFormatVideoNode]()

    for edge_detect in sorted(all_subclasses, key=lambda x: x.__name__):
        try:
            mask = edge_detect().edgemask(clip, lthr, hthr, multi, clamp, planes, **kwargs)  # pyright: ignore[reportAbstractUsage]
        except AttributeError as e:
            from warnings import warn

            warn(str(e), RuntimeWarning)
            continue

        out.append(mask.text.Text(edge_detect.__name__))

    return out

get_all_ridge_detect 

get_all_ridge_detect(
    clip: VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any
) -> list[ConstantFormatVideoNode]

Returns all the RidgeDetect subclasses

Parameters:

Returns:

  • list[ConstantFormatVideoNode] –

    A list edge masks

Source code in vsmasktools/edge/_abstract.py 
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def get_all_ridge_detect(
    clip: vs.VideoNode,
    lthr: float = 0.0,
    hthr: float | None = None,
    multi: float = 1.0,
    clamp: bool | tuple[float, float] | list[tuple[float, float]] = False,
    planes: Planes = None,
    **kwargs: Any,
) -> list[ConstantFormatVideoNode]:
    """
    Returns all the RidgeDetect subclasses

    Args:
        clip: Source clip
        lthr: See [RidgeDetect.get_mask][vsmasktools.edge.RidgeDetect.ridgemask]
        hthr: See [RidgeDetect.get_mask][vsmasktools.edge.RidgeDetect.ridgemask]
        multi: See [RidgeDetect.get_mask][vsmasktools.edge.RidgeDetect.ridgemask]
        clamp: Clamp to legal values if True or specified range `(low, high)`
        planes: Which planes to process.

    Returns:
        A list edge masks
    """
    # https://github.com/python/mypy/issues/4717
    all_subclasses = {
        s
        for s in get_subclasses(RidgeDetect)  # type: ignore[type-abstract]
        if not isabstract(s) and s.__module__.split(".")[-1] != "_abstract"
    }

    out = list[ConstantFormatVideoNode]()

    for edge_detect in sorted(all_subclasses, key=lambda x: x.__name__):
        try:
            mask = edge_detect().ridgemask(clip, lthr, hthr, multi, clamp, planes, **kwargs)  # pyright: ignore[reportAbstractUsage]
        except AttributeError as e:
            from warnings import warn

            warn(str(e), RuntimeWarning)
            continue

        out.append(mask.text.Text(edge_detect.__name__))

    return out