Skip to content

edge_funcs

Classes:

  • dre_edgemask –

    Edgemask with dynamic range enhancement prefiltering.

Functions:

dre_edgemask

Bases: CustomEnum

Edgemask with dynamic range enhancement prefiltering.

Methods:

  • __call__ –

    Creates an edgemask with dynamic range enhancement (DRE) prefiltering.

Attributes:

  • CLAHE –

    Contrast Limited Adaptive Histogram Equalization.

  • RETINEX –

    Retinex-based edgemask.

CLAHE class-attribute instance-attribute 

CLAHE = cast('dre_edgemask', object())

Contrast Limited Adaptive Histogram Equalization. Based on the OpenCV implementation

RETINEX class-attribute instance-attribute 

RETINEX = cast('dre_edgemask', object())

Retinex-based edgemask.

__call__ 

__call__(
    clip: VideoNode,
    tsigma: float = 1,
    brz: float = 0.122,
    *,
    sigmas: Sequence[float] = [50, 200, 350]
) -> ConstantFormatVideoNode

__call__(
    clip: VideoNode,
    tsigma: float = 1,
    brz: float = 0.122,
    *,
    limit: float = 0.0305,
    tile: int = 5
) -> ConstantFormatVideoNode

__call__(
    clip: VideoNode, tsigma: float = 1, brz: float = 0.122, **kwargs: Any
) -> ConstantFormatVideoNode

__call__(
    clip: VideoNode, tsigma: float = 1, brz: float = 0.122, **kwargs: Any
) -> ConstantFormatVideoNode

Creates an edgemask with dynamic range enhancement (DRE) prefiltering.

This function serves as a wrapper around the retinex and vszip.CLAHE functions, applying one of them as a prefilter before generating the edgemask.

Parameters:

  • clip

    (VideoNode) –

    Source clip.

  • tsigma

    (float, default: 1 ) –

    Sigma value for TCanny edge detection. Defaults to 1.

  • brz

    (float, default: 0.122 ) –

    Binarization threshold (32-bit float scale). Defaults to 0.122.

  • sigmas

    –

    Sigma values for the retinex prefilter. Defaults to [50, 200, 350].

  • limit

    –

    Limit for CLAHE prefilter. Defaults to 0.0305.

  • tile

    –

    Tile size for CLAHE prefilter. Defaults to 5.

Returns:

  • ConstantFormatVideoNode –

    Edgemask clip with applied DRE prefiltering.

Source code 
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
def __call__(
    self, clip: vs.VideoNode, tsigma: float = 1, brz: float = 0.122, **kwargs: Any
) -> ConstantFormatVideoNode:
    """
    Creates an edgemask with dynamic range enhancement (DRE) prefiltering.

    This function serves as a wrapper around the `retinex` and `vszip.CLAHE` functions,
    applying one of them as a prefilter before generating the edgemask.

    :param clip:            Source clip.
    :param tsigma:          Sigma value for TCanny edge detection. Defaults to 1.
    :param brz:             Binarization threshold (32-bit float scale). Defaults to 0.122.
    :param sigmas:          Sigma values for the retinex prefilter. Defaults to [50, 200, 350].
    :param limit:           Limit for CLAHE prefilter. Defaults to 0.0305.
    :param tile:            Tile size for CLAHE prefilter. Defaults to 5.
    :return:                Edgemask clip with applied DRE prefiltering.
    """
    luma = get_y(clip)

    dreluma = self._prefilter(luma, **kwargs)

    tcanny = PrewittTCanny.edgemask(dreluma, sigma=tsigma, scale=1)
    tcanny = Morpho.minimum(tcanny, coords=Coordinates.CORNERS)

    kirsch = Kirsch(MagDirection.N | MagDirection.EAST).edgemask(luma)

    add_clip = ExprOp.ADD(tcanny, kirsch)

    if brz > 0:
        add_clip = Morpho.binarize(add_clip, brz)

    return ColorRange.FULL.apply(add_clip)

limited_linemask 

limited_linemask(
    clip: VideoNode,
    sigmas: list[float] = [0.000125, 0.0025, 0.0055],
    detail_sigmas: list[float] = [0.011, 0.013],
    edgemasks: Sequence[GenericMaskT] = [Kirsch],
    **kwargs: Any
) -> ConstantFormatVideoNode
Source code 
111
112
113
114
115
116
117
118
119
120
121
122
123
124
def limited_linemask(
    clip: vs.VideoNode,
    sigmas: list[float] = [0.000125, 0.0025, 0.0055],
    detail_sigmas: list[float] = [0.011, 0.013],
    edgemasks: Sequence[GenericMaskT] = [Kirsch],
    **kwargs: Any
) -> ConstantFormatVideoNode:
    clip_y = plane(clip, 0)

    return ExprOp.ADD(
        (normalize_mask(edge, clip_y, **kwargs) for edge in edgemasks),
        (tcanny_retinex(clip_y, s) for s in sigmas),
        (multi_detail_mask(clip_y, s) for s in detail_sigmas)
    )

luma_credit_mask 

luma_credit_mask(
    clip: VideoNode,
    thr: float = 0.9,
    edgemask: GenericMaskT = FDoGTCanny,
    draft: bool = False,
    **kwargs: Any
) -> ConstantFormatVideoNode
Source code 
83
84
85
86
87
88
89
90
91
92
93
94
95
96
def luma_credit_mask(
    clip: vs.VideoNode, thr: float = 0.9, edgemask: GenericMaskT = FDoGTCanny, draft: bool = False, **kwargs: Any
) -> ConstantFormatVideoNode:
    y = plane(clip, 0)

    edge_mask = normalize_mask(edgemask, y, **kwargs)

    credit_mask = norm_expr([edge_mask, y], f'y {scale_mask(thr, 32, y)} > y 0 ? x min', func=ringing_mask)

    if not draft:
        credit_mask = Morpho.maximum(credit_mask, iterations=4)
        credit_mask = Morpho.inflate(credit_mask, iterations=2)

    return credit_mask

luma_mask 

luma_mask(
    clip: VideoNode, thr_lo: float, thr_hi: float, invert: bool = True
) -> ConstantFormatVideoNode
Source code 
67
68
69
70
71
72
73
74
75
76
77
78
79
80
def luma_mask(clip: vs.VideoNode, thr_lo: float, thr_hi: float, invert: bool = True) -> ConstantFormatVideoNode:
    peak = get_peak_value(clip)

    lo, hi = (peak, 0) if invert else (0, peak)
    inv_pre, inv_post = (peak, '-') if invert else ('', '')

    thr_lo = scale_value(thr_lo, 32, clip)
    thr_hi = scale_value(thr_hi, 32, clip)

    return norm_expr(
        get_y(clip),
        f'x {thr_lo} < {lo} x {thr_hi} > {hi} {inv_pre} x {thr_lo} - {thr_lo} {thr_hi} - / {peak} * {inv_post} ? ?',
        func=ringing_mask
    )

ringing_mask 

ringing_mask(
    clip: VideoNode,
    rad: int = 2,
    brz: float = 0.35,
    thmi: float = 0.315,
    thma: float = 0.5,
    thlimi: float = 0.195,
    thlima: float = 0.392,
    credit_mask: GenericMaskT = Prewitt,
    **kwargs: Any
) -> ConstantFormatVideoNode
Source code 
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
def ringing_mask(
    clip: vs.VideoNode,
    rad: int = 2, brz: float = 0.35,
    thmi: float = 0.315, thma: float = 0.5,
    thlimi: float = 0.195, thlima: float = 0.392,
    credit_mask: GenericMaskT = Prewitt, **kwargs: Any
) -> ConstantFormatVideoNode:
    assert check_variable(clip, ringing_mask)

    thmi, thma, thlimi, thlima = (
        scale_mask(t, 32, clip) for t in [thmi, thma, thlimi, thlima]
    )

    blur_kernel = BlurMatrix.BINOMIAL(1, mode=ConvMode.SQUARE)

    edgemask = normalize_mask(credit_mask, plane(clip, 0), **kwargs)
    edgemask = limiter(edgemask)

    light = norm_expr(edgemask, f'x {thlimi} - {thma - thmi} / {ExprToken.RangeMax} *', func=ringing_mask)

    shrink = Morpho.dilation(light, rad)
    shrink = Morpho.binarize(shrink, brz)
    shrink = Morpho.erosion(shrink, 2)
    shrink = blur_kernel(shrink, passes=2)

    strong = norm_expr(edgemask, f'x {thmi} - {thlima - thlimi} / {ExprToken.RangeMax} *', func=ringing_mask)
    expand = Morpho.dilation(strong, iterations=rad)

    mask = norm_expr([expand, strong, shrink], 'x y z max -', func=ringing_mask)

    return ExprOp.convolution('x', blur_kernel, premultiply=2, multiply=2, clamp=True)(mask)

tcanny_retinex 

tcanny_retinex(
    clip: VideoNode,
    thr: float,
    sigma: Sequence[float] = [50, 200, 350],
    blur_sigma: float = 1.0,
) -> ConstantFormatVideoNode
Source code 
 99
100
101
102
103
104
105
106
107
108
def tcanny_retinex(
    clip: vs.VideoNode, thr: float, sigma: Sequence[float] = [50, 200, 350], blur_sigma: float = 1.0
) -> ConstantFormatVideoNode:
    blur = gauss_blur(clip, blur_sigma)

    msrcp = retinex(blur, sigma, upper_thr=thr, fast=True, func=tcanny_retinex)

    tcunnied = msrcp.tcanny.TCanny(mode=1, sigma=1)

    return Morpho.minimum(tcunnied, coords=Coordinates.CORNERS)