rescale ¶

Bases: RescaleBase

Rescale wrapper supporting everything you need for (fractional) descaling, re-upscaling and masking-out details.

Examples usage:

• Basic 720p rescale:

  from vsscale import Rescale
  from vskernels import Bilinear
  
  rs = Rescale(clip, 720, Bilinear)
  final = rs.upscale
  

• Adding aa and dehalo on doubled clip:

  from vsaa import based_aa
  from vsdehalo import fine_dehalo
  
  aa = based_aa(rs.doubled, supersampler=False)
  dehalo = fine_dehalo(aa, ...)
  
  rs.doubled = dehalo
  

• Loading line_mask and credit_mask:

  from vsmasktools import diff_creditless_oped
  from vsexprtools import ExprOp
  
  rs.default_line_mask()
  
  oped_credit_mask = diff_creditless_oped(...)
  credit_mask = rs.default_credit_mask(thr=0.209, ranges=(200, 300), postfilter=4)
  rs.credit_mask = ExprOp.ADD.combine(oped_credit_mask, credit_mask)
  

• Fractional rescale:

  from vsscale import Rescale
  from vskernels import Bilinear
  
  # Forcing the height to a float will ensure a fractional descale
  rs = Rescale(clip, 800.0, Bilinear)
  >>> rs.descale_args
  ScalingArgs(
      width=1424, height=800, src_width=1422.2222222222222, src_height=800.0,
      src_top=0.0, src_left=0.8888888888889142, mode='hw'
  )
  
  # while doing this will not
  rs = Rescale(clip, 800, Bilinear)
  >>> rs.descale_args
  ScalingArgs(width=1422, height=800, src_width=1422, src_height=800, src_top=0, src_left=0, mode='hw')
  

• Cropping is also supported:

  from vsscale import Rescale
  from vskernels import Bilinear
  
  # Descaling while cropping the letterboxes at the top and bottom
  rs = Rescale(clip, 874, Bilinear, crop=(0, 0, 202, 202))
  >>> rs.descale_args
  ScalingArgs(
      width=1554, height=548, src_width=1554.0, src_height=547.0592592592592,
      src_top=0.4703703703703752, src_left=0.0, mode='hw'
  )
  
  # Same thing but ensuring the width is fractional descaled
  rs = Rescale(clip, 874.0, Bilinear, crop=(0, 0, 202, 202))
  >>> rs.descale_args
  ScalingArgs(
      width=1554, height=548, src_width=1553.7777777777778, src_height=547.0592592592592,
      src_top=0.4703703703703752, src_left=0.11111111111108585, mode='hw'
  )
  

Initialize the rescaling process.

Parameters:

• clip ¶

  (VideoNode) –

  Clip to be rescaled.

• height ¶

  (int | float) –

  Height to be descaled to. If passed as a float, a fractional descale is performed.

• kernel ¶

  (KernelLike) –

  Kernel used for descaling.

• upscaler ¶

  (ScalerLike, default: ArtCNN ) –

  Scaler that supports doubling. Defaults to ArtCNN.

• downscaler ¶

  (ScalerLike, default: Hermite(linear=True) ) –

  Scaler used to downscale the upscaled clip back to input resolution. Defaults to Hermite(linear=True).

• width ¶

  (int | float | None, default: None ) –

  Width to be descaled to. If None, it is automatically calculated from the height.

• base_height ¶

  (int | None, default: None ) –

  Integer height to contain the clip within. If None, it is automatically calculated from the height.

• base_width ¶

  (int | None, default: None ) –

  Integer width to contain the clip within. If None, it is automatically calculated from the width.

• crop ¶

  (tuple[LeftCrop, RightCrop, TopCrop, BottomCrop], default: CropRel() ) –

  Cropping values to apply before descale. The ratio descale_height / source_height is preserved even after descale. The cropped area is restored when calling the upscale property.

• shift ¶

  (tuple[TopShift, LeftShift], default: (0, 0) ) –

  Pixel shifts to apply during descale and upscale. Defaults to (0, 0).

• field_based ¶

  (FieldBasedLike | bool | None, default: None ) –

  Whether the input is cross-converted or interlaced content.

• border_handling ¶

  (int | BorderHandling, default: MIRROR ) –

  Adjusts how the clip is padded internally during the scaling process. Accepted values are:

  • 0 (MIRROR): Assume the image was resized with mirror padding.
  • 1 (ZERO): Assume the image was resized with zero padding.
  • 2 (EXTEND): Assume the image was resized with extend padding, where the outermost row was extended infinitely far.

  Defaults to 0.

Methods:

• default_credit_mask –

  Load a credit mask by making a difference mask between src and rescaled clips

• default_line_mask –

  Load a default Kirsch line mask in the class instance. Additionally, it is returned.

Attributes:

• credit_mask (VideoNode) –

  Gets the credit mask to be applied on the upscaled clip.

• descale –

  Gets the descaled clip.

• descale_args –

  Descale arguments. See ScalingArgs

• doubled –

  Gets the doubled clip.

• ignore_mask (VideoNode) –

  Gets the ignore mask to be applied on the descaled clip.

• line_mask (VideoNode) –

  Gets the lineart mask to be applied on the upscaled clip.

• rescale –

  Gets the rescaled clip.

• upscale –

  Returns the upscaled clip

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def __init__(
    self,
    clip: vs.VideoNode,
    /,
    height: int | float,
    kernel: KernelLike,
    upscaler: ScalerLike = ArtCNN,
    downscaler: ScalerLike = Hermite(linear=True),
    width: int | float | None = None,
    base_height: int | None = None,
    base_width: int | None = None,
    crop: tuple[LeftCrop, RightCrop, TopCrop, BottomCrop] = CropRel(),
    shift: tuple[TopShift, LeftShift] = (0, 0),
    field_based: FieldBasedLike | bool | None = None,
    border_handling: int | BorderHandling = BorderHandling.MIRROR,
    **kwargs: Any,
) -> None:
    """
    Initialize the rescaling process.

    Args:
        clip: Clip to be rescaled.
        height: Height to be descaled to. If passed as a float, a fractional descale is performed.
        kernel: Kernel used for descaling.
        upscaler: Scaler that supports doubling. Defaults to ``ArtCNN``.
        downscaler: Scaler used to downscale the upscaled clip back to input resolution. Defaults to
            ``Hermite(linear=True)``.
        width: Width to be descaled to. If ``None``, it is automatically calculated from the height.
        base_height: Integer height to contain the clip within. If ``None``, it is automatically calculated from the
            height.
        base_width: Integer width to contain the clip within. If ``None``, it is automatically calculated from the
            width.
        crop: Cropping values to apply before descale. The ratio ``descale_height / source_height`` is preserved
            even after descale. The cropped area is restored when calling the ``upscale`` property.
        shift: Pixel shifts to apply during descale and upscale. Defaults to ``(0, 0)``.
        field_based: Whether the input is cross-converted or interlaced content.
        border_handling: Adjusts how the clip is padded internally during the scaling process.
            Accepted values are:

               - ``0`` (MIRROR): Assume the image was resized with mirror padding.
               - ``1`` (ZERO):   Assume the image was resized with zero padding.
               - ``2`` (EXTEND): Assume the image was resized with extend padding,
                 where the outermost row was extended infinitely far.

            Defaults to ``0``.
    """
    self._line_mask: vs.VideoNode | None = None
    self._credit_mask: vs.VideoNode | None = None
    self._ignore_mask: vs.VideoNode | None = None
    self._crop = crop
    self._pre = clip

    self.descale_args = ScalingArgs.from_args(
        clip, height, width, base_height, base_width, shift[0], shift[1], crop, mode="hw"
    )

    super().__init__(clip, kernel, upscaler, downscaler, field_based, border_handling, **kwargs)

    if self._crop > (0, 0, 0, 0):
        self._clipy = self._clipy.std.Crop(*self._crop)

credit_mask: VideoNode

descale = cachedproperty[VideoNode, VideoNode](
    lambda self: _generate_descale(_clipy),
    lambda self, value: update_cache(self, "descale", value),
    lambda self: clear_cache(
        self, ["descale", "rescale", "doubled", "upscale"]
    ),
)

descale_args = from_args(
    clip,
    height,
    width,
    base_height,
    base_width,
    shift[0],
    shift[1],
    crop,
    mode="hw",
)

doubled = cachedproperty[VideoNode, VideoNode](
    lambda self: _generate_doubled(descale),
    lambda self, value: update_cache(self, "doubled", value),
    lambda self: clear_cache(self, ["doubled", "upscale"]),
)

ignore_mask: VideoNode

line_mask: VideoNode

rescale = cachedproperty[VideoNode, VideoNode](
    lambda self: _generate_rescale(descale),
    lambda self, value: update_cache(self, "rescale", value),
    lambda self: clear_cache(self, "rescale"),
)

upscale = cachedproperty[VideoNode, VideoNode](
    lambda self: CopyFrameProps(
        join([_generate_upscale(doubled), *(_chroma)]),
        _clipy,
        "_ChromaLocation",
    ),
    lambda self, value: update_cache(self, "upscale", value),
    lambda self: clear_cache(self, "upscale"),
)

default_credit_mask(
    rescale: VideoNode | None = None,
    src: VideoNode | None = None,
    thr: float = 0.216,
    expand: int = 4,
    ranges: FrameRangeN | FrameRangesN | None = None,
    stabilize: bool = True,
    scenechanges: Iterable[int] | None = None,
    **kwargs: Any
) -> VideoNode

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def default_credit_mask(
    self,
    rescale: vs.VideoNode | None = None,
    src: vs.VideoNode | None = None,
    thr: float = 0.216,
    expand: int = 4,
    ranges: FrameRangeN | FrameRangesN | None = None,
    stabilize: bool = True,
    scenechanges: Iterable[int] | None = None,
    **kwargs: Any,
) -> vs.VideoNode:
    """
    Load a credit mask by making a difference mask between src and rescaled clips

    Args:
        rescale: Rescaled clip, defaults to rescaled instance clip.
        src: Source clip, defaults to source instance clip.
        thr: Threshold of the amplification expr, defaults to 0.216.
        expand: Additional expand radius applied to the mask, defaults to 4.
        ranges: If specified, ranges to apply the credit clip to.
        stabilize: Try to stabilize the mask by applying a temporal convolution and then binarized by a threshold.
            Only works when there are ranges specified.
        scenechanges: Explicit list of scenechange frames for stabilizing the mask.
        **kwargs: Additional keyword arguments for [based_diff_mask][vsmasktools.based_diff_mask]

    Returns:
        Generated mask.
    """
    if not src:
        src = self._clipy
    if not rescale:
        rescale = self.rescale

    src, rescale = get_y(src), get_y(rescale)

    credit_mask = based_diff_mask(src, rescale, thr=thr, expand=expand, func=self.default_credit_mask, **kwargs)

    if ranges is not None:
        if stabilize:
            credit_mask = stabilize_mask(credit_mask, 3, ranges, scenechanges, func=self.default_credit_mask)

        credit_mask = replace_ranges(credit_mask.std.BlankClip(keep=True), credit_mask, ranges)

    self.credit_mask = credit_mask

    return self.credit_mask

default_line_mask(
    clip: VideoNode | None = None, scaler: ScalerLike = Bilinear, **kwargs: Any
) -> VideoNode

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def default_line_mask(
    self, clip: vs.VideoNode | None = None, scaler: ScalerLike = Bilinear, **kwargs: Any
) -> vs.VideoNode:
    """
    Load a default Kirsch line mask in the class instance. Additionally, it is returned.

    Args:
        clip: Reference clip, defaults to doubled clip if None.
        scaler: Scaled used for matching the source clip format, defaults to Bilinear.

    Returns:
        Generated mask.
    """
    scaler = Scaler.ensure_obj(scaler)
    scale_kwargs = scaler.kwargs if clip else self.descale_args.kwargs(self.doubled) | scaler.kwargs

    clip = clip if clip else self.doubled

    line_mask = Kirsch.edgemask(clip, **kwargs).std.Maximum().std.Minimum()
    line_mask = scaler.scale(
        line_mask, self._clipy.width, self._clipy.height, format=self._clipy.format, **scale_kwargs
    )

    self.line_mask = line_mask

    return self.line_mask

Bases: VSObjectABC

Base class for Rescale wrapper

Attributes:

• descale –

  Gets the descaled clip.

• descale_args (ScalingArgs) –

  Descale arguments. See ScalingArgs

• doubled –

  Gets the doubled clip.

• rescale –

  Gets the rescaled clip.

• upscale –

  Returns the upscaled clip

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def __init__(
    self,
    clip: vs.VideoNode,
    /,
    kernel: KernelLike,
    upscaler: ScalerLike = ArtCNN,
    downscaler: ScalerLike = Hermite(linear=True),
    field_based: FieldBasedLike | bool | None = None,
    border_handling: int | BorderHandling = BorderHandling.MIRROR,
    **kwargs: Any,
) -> None:
    self._clipy, *chroma = split(clip)
    self._chroma = chroma

    self._kernel = Kernel.ensure_obj(kernel)
    self._upscaler = Scaler.ensure_obj(upscaler)

    self._downscaler = Scaler.ensure_obj(downscaler)

    self._field_based = FieldBased.from_param(field_based)

    self._border_handling = BorderHandling(int(border_handling))

    self.__add_props = kwargs.get("_add_props")

descale = cachedproperty[VideoNode, VideoNode](
    lambda self: _generate_descale(_clipy),
    lambda self, value: update_cache(self, "descale", value),
    lambda self: clear_cache(
        self, ["descale", "rescale", "doubled", "upscale"]
    ),
)

descale_args: ScalingArgs

doubled = cachedproperty[VideoNode, VideoNode](
    lambda self: _generate_doubled(descale),
    lambda self, value: update_cache(self, "doubled", value),
    lambda self: clear_cache(self, ["doubled", "upscale"]),
)

rescale = cachedproperty[VideoNode, VideoNode](
    lambda self: _generate_rescale(descale),
    lambda self, value: update_cache(self, "rescale", value),
    lambda self: clear_cache(self, "rescale"),
)

upscale = cachedproperty[VideoNode, VideoNode](
    lambda self: CopyFrameProps(
        join([_generate_upscale(doubled), *(_chroma)]),
        _clipy,
        "_ChromaLocation",
    ),
    lambda self, value: update_cache(self, "upscale", value),
    lambda self: clear_cache(self, "upscale"),
)