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mask

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.

  • brz

    –

    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.

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.

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

    :return:            Dehalo mask.
    """

    if FieldBased.from_video(src).is_inter:
        raise UnsupportedFieldBasedError('Only progressive video is supported!', base_dehalo_mask)

    luma = get_y(src)

    if pre_ss:
        luma = Nnedi3.scale(luma, luma.width * 2, luma.height * 2)

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

    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)

    if pre_ss:
        return Point.scale(mask, src.width, src.height)

    return mask