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mask

Functions:

  • base_dehalo_mask –

    Based on muvsfunc.YAHRmask, stand-alone version with some tweaks. Adopted from jvsfunc.

base_dehalo_mask 

base_dehalo_mask(
    src: VideoNode,
    expand: float = 0.5,
    iterations: int = 2,
    brz0: float = 0.31,
    brz1: float = 1.0,
    shift: int = 8,
    pre_ss: bool = True,
    multi: float = 1.0,
) -> VideoNode

Based on muvsfunc.YAHRmask, stand-alone version with some tweaks. Adopted from jvsfunc.

Parameters:

  • src

    (VideoNode) –

    Input clip.

  • expand

    (float, default: 0.5 ) –

    Expansion of edge mask.

  • iterations

    (int, default: 2 ) –

    Protects parallel lines and corners that are usually damaged by strong dehaloing.

  • brz0

    (float, default: 0.31 ) –

    Adjusts the internal line thickness.

  • brz1

    (float, default: 1.0 ) –

    Adjusts the internal line thickness.

  • shift

    (int, default: 8 ) –

    8-bit corrective shift value for fine-tuning expansion.

  • pre_ss

    (bool, default: True ) –

    Perform the mask creation at 2x.

  • multi

    (float, default: 1.0 ) –

    Final pixel value multiplier.

Returns:

  • VideoNode –

    Dehalo mask.

Source code 
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def base_dehalo_mask(
    src: vs.VideoNode,
    expand: float = 0.5,
    iterations: int = 2,
    brz0: float = 0.31,
    brz1: float = 1.0,
    shift: int = 8,
    pre_ss: bool = True,
    multi: float = 1.0,
) -> vs.VideoNode:
    """
    Based on `muvsfunc.YAHRmask`, stand-alone version with some tweaks. Adopted from jvsfunc.

    Args:
        src: Input clip.
        expand: Expansion of edge mask.
        iterations: Protects parallel lines and corners that are usually damaged by strong dehaloing.
        brz0: Adjusts the internal line thickness.
        brz1: Adjusts the internal line thickness.
        shift: 8-bit corrective shift value for fine-tuning expansion.
        pre_ss: Perform the mask creation at 2x.
        multi: Final pixel value multiplier.

    Returns:
        Dehalo mask.
    """

    assert check_progressive(src, base_dehalo_mask)

    luma = get_y(src)

    if pre_ss:
        luma = NNEDI3().supersample(luma)

    exp_edges = norm_expr(
        [luma, Morpho.maximum(luma, iterations=2)],
        "y x - {shift} - range_half *",
        shift=scale_delta(shift, 8, luma),
        func=base_dehalo_mask,
    )

    edgemask = PrewittTCanny.edgemask(exp_edges, sigma=sqrt(expand * 2), mode=-1, multi=16)

    halo_mask = Morpho.maximum(exp_edges, iterations=iterations)
    halo_mask = Morpho.minimum(halo_mask, iterations=iterations)
    halo_mask = Morpho.binarize(halo_mask, brz0, 1.0, 0.0)

    if brz1 != 1.0:
        halo_mask = Morpho.inflate(halo_mask, iterations=2)
        halo_mask = Morpho.binarize(halo_mask, brz1)

    mask = norm_expr(
        [edgemask, BlurMatrix.BINOMIAL()(halo_mask)], "x y min {multi} *", multi=multi, func=base_dehalo_mask
    )

    if pre_ss:
        return vs.core.resize.Point(mask, src.width, src.height)

    return mask