def filterchain() -> Union[vs.VideoNode, Tuple[vs.VideoNode, ...]]:
"""Regular VapourSynth filterchain"""
import EoEfunc as eoe
import havsfunc as haf
import lvsfunc as lvf
import vardefunc as vdf
from adptvgrnMod import adptvgrnMod
from ccd import ccd
from muvsfunc import SSIM_downsample
from vsutil import depth, get_y, iterate
src = pre_freeze().std.AssumeFPS(fpsnum=24000, fpsden=1001)
src = depth(src, 16)
# TO-DO: Figure out how they post-sharpened it. Probably some form of unsharpening?
src_y = depth(get_y(src), 32)
descale = lvf.kernels.Bicubic(b=0, c=3 / 4).descale(src_y, 1440, 810)
double = vdf.scale.nnedi3cl_double(descale, pscrn=1)
rescale = depth(SSIM_downsample(double, 1920, 1080), 16)
scaled = vdf.misc.merge_chroma(rescale, src)
denoise = core.knlm.KNLMeansCL(scaled, d=1, a=3, s=4, h=0.4, channels='Y')
stab = haf.GSMC(denoise, radius=2, planes=[0])
cdenoise = ccd(stab, threshold=5, matrix='709')
decs = vdf.noise.decsiz(cdenoise,
sigmaS=4,
min_in=208 << 8,
max_in=232 << 8)
dehalo = haf.YAHR(decs, blur=2, depth=32)
halo_mask = lvf.mask.halo_mask(decs, rad=3, brz=0.3, thma=0.42)
dehalo_masked = core.std.MaskedMerge(decs, dehalo, halo_mask)
dehalo_min = core.std.Expr([dehalo_masked, decs], "x y min")
aa = lvf.aa.nneedi3_clamp(dehalo_min, strength=1.5)
# Some scenes have super strong aliasing that I really don't wanna scenefilter until BDs. Thanks, Silver Link!
aa_strong = lvf.sraa(dehalo_min, rfactor=1.35)
aa_spliced = lvf.rfs(aa, aa_strong, [])
upscale = lvf.kernels.Bicubic(b=0, c=3 / 4).scale(descale, 1920, 1080)
credit_mask = lvf.scale.descale_detail_mask(src_y, upscale, threshold=0.08)
credit_mask = iterate(credit_mask, core.std.Deflate, 3)
credit_mask = iterate(credit_mask, core.std.Inflate, 3)
credit_mask = iterate(credit_mask, core.std.Maximum, 2)
merge_credits = core.std.MaskedMerge(aa_spliced, src,
depth(credit_mask, 16))
deband = flt.masked_f3kdb(merge_credits, rad=18, thr=32, grain=[24, 0])
grain: vs.VideoNode = adptvgrnMod(deband,
seed=42069,
strength=0.15,
luma_scaling=10,
size=1.25,
sharp=80,
static=True,
grain_chroma=False)
return grain
def filterchain() -> Union[vs.VideoNode, Tuple[vs.VideoNode, ...]]:
"""Main filterchain"""
import lvsfunc as lvf
import rekt
import vardefunc as vdf
from muvsfunc import SSIM_downsample
from vsutil import depth, get_y
src = JP_BD.clip_cut
rkt = rekt.rektlvls(src, [0, -1], [15, 15], [0, -1], [15, 15])
cloc = depth(rkt, 32).resize.Bicubic(chromaloc_in=1, chromaloc=0)
descale = lvf.kernels.Bilinear().descale(get_y(cloc), 1280, 720)
supersample = vdf.scale.nnedi3_upscale(descale)
downscaled = SSIM_downsample(supersample,
src.width,
src.height,
smooth=((3**2 - 1) / 12)**0.5,
sigmoid=True,
filter_param_a=0,
filter_param_b=0)
scaled = vdf.misc.merge_chroma(downscaled, cloc)
scaled = depth(scaled, 16)
dft = core.dfttest.DFTTest(scaled,
sigma=0.6,
sbsize=8,
sosize=6,
tbsize=3,
tosize=1)
decs = vdf.noise.decsiz(dft, sigmaS=4, min_in=200 << 8, max_in=232 << 8)
baa = lvf.aa.based_aa(decs, str(shader_file))
sraa = lvf.sraa(decs, rfactor=1.5)
clmp = lvf.aa.clamp_aa(decs, baa, sraa, strength=1.5)
deband = flt.masked_f3kdb(clmp, rad=16, thr=[20, 16])
grain = vdf.noise.Graigasm(thrs=[x << 8 for x in (32, 80, 128, 176)],
strengths=[(0.25, 0.0), (0.20, 0.0),
(0.15, 0.0), (0.0, 0.0)],
sizes=(1.20, 1.15, 1.10, 1),
sharps=(80, 70, 60, 50),
grainers=[
vdf.noise.AddGrain(seed=69420,
constant=False),
vdf.noise.AddGrain(seed=69420,
constant=False),
vdf.noise.AddGrain(seed=69420,
constant=True)
]).graining(deband)
return grain
def filterchain() -> Union[vs.VideoNode, Tuple[vs.VideoNode, ...]]:
"""Main filterchain"""
import lvsfunc as lvf
import rekt
import vardefunc as vdf
from awsmfunc import bbmod
from ccd import ccd
from muvsfunc import SSIM_downsample
from vsutil import depth, get_y
src = JP_BD.clip_cut
rkt = rekt.rektlvls(src, [0, -1], [30, 17], [0], [17])
bb_y = bbmod(rkt, top=2, left=2, right=2, bottom=2, u=False, v=False, blur=9999)
bb_uv = bbmod(bb_y, left=2, right=2, y=False)
bb = depth(bb_uv, 32)
descale = lvf.kernels.Spline36().descale(get_y(bb), 1280, 720)
up_chr = vdf.scale.to_444(bb, 1920, 1080, True).resize.Bicubic(1280, 720)
descale_merge = vdf.misc.merge_chroma(descale, up_chr)
denoise_down = lvf.deblock.vsdpir(descale_merge, strength=0.5, mode='deblock', matrix=1, i444=True, cuda=True)
supersample = vdf.scale.nnedi3_upscale(get_y(denoise_down))
downscaled = SSIM_downsample(supersample, bb.width, bb.height, smooth=((3 ** 2 - 1) / 12) ** 0.5,
sigmoid=True, filter_param_a=0, filter_param_b=0)
scaled = vdf.misc.merge_chroma(downscaled, bb)
scaled = depth(scaled, 16)
den_uv = ccd(scaled, matrix='709')
decs = vdf.noise.decsiz(den_uv, sigmaS=8, min_in=200 << 8, max_in=232 << 8)
nn_aa = lvf.aa.nnedi3(opencl=True, dh=False)(decs)
sraa = lvf.sraa(decs, rfactor=1.75)
clmp = lvf.aa.clamp_aa(decs, nn_aa, sraa)
dehalo = lvf.dehalo.masked_dha(clmp, brightstr=0.65)
deband = flt.masked_f3kdb(dehalo, rad=17, thr=[24, 16], grain=[24, 12])
grain = vdf.noise.Graigasm(
thrs=[x << 8 for x in (32, 80, 128, 176)],
strengths=[(0.20, 0.0), (0.15, 0.0), (0.10, 0.0), (0.0, 0.0)],
sizes=(1.20, 1.15, 1.10, 1),
sharps=(100, 80, 60, 20),
grainers=[
vdf.noise.AddGrain(seed=69420, constant=False),
vdf.noise.AddGrain(seed=69420, constant=False),
vdf.noise.AddGrain(seed=69420, constant=True)
]).graining(deband)
no_flt = lvf.rfs(grain, depth(bb, 16), no_filter)
return no_flt
def filterchain() -> Union[vs.VideoNode, Tuple[vs.VideoNode, ...]]:
"""Regular VapourSynth filterchain"""
import havsfunc as haf
import lvsfunc as lvf
import vardefunc as vdf
from adptvgrnMod import adptvgrnMod
from muvsfunc import SSIM_downsample
from vsutil import depth, get_y, iterate
src = pre_freeze()
src = depth(src, 16)
src_y = depth(get_y(src), 32)
descale = lvf.kernels.Bicubic(b=0, c=3 / 4).descale(src_y, 1440, 810)
double = vdf.scale.nnedi3cl_double(descale, pscrn=1)
rescale = depth(SSIM_downsample(double, 1920, 1080), 16)
scaled = vdf.misc.merge_chroma(rescale, src)
denoise = core.knlm.KNLMeansCL(scaled, d=1, a=3, s=4, h=0.3, channels='Y')
decs = vdf.noise.decsiz(denoise,
sigmaS=4,
min_in=208 << 8,
max_in=232 << 8)
dehalo = haf.YAHR(decs, blur=2, depth=28)
halo_mask = lvf.mask.halo_mask(decs, rad=3, brz=0.3, thma=0.42)
dehalo_masked = core.std.MaskedMerge(decs, dehalo, halo_mask)
aa = lvf.aa.nneedi3_clamp(dehalo_masked, strength=1.5)
# Strong aliasing on the transformation scene (and probably elsewhere that I missed). Thanks, Silver Link!
aa_strong = lvf.sraa(dehalo_masked, rfactor=1.35)
aa_spliced = lvf.rfs(aa, aa_strong, [(7056, 7322)])
upscale = lvf.kernels.Bicubic(b=0, c=3 / 4).scale(descale, 1920, 1080)
credit_mask = lvf.scale.descale_detail_mask(src_y, upscale, threshold=0.08)
credit_mask = iterate(credit_mask, core.std.Deflate, 3)
credit_mask = iterate(credit_mask, core.std.Inflate, 3)
credit_mask = iterate(credit_mask, core.std.Maximum, 2)
merge_credits = core.std.MaskedMerge(aa_spliced, src,
depth(credit_mask, 16))
deband = flt.masked_f3kdb(merge_credits, rad=18, thr=32, grain=[24, 0])
grain: vs.VideoNode = adptvgrnMod(deband,
seed=42069,
strength=0.15,
luma_scaling=10,
size=1.25,
sharp=80,
static=True,
grain_chroma=False)
return grain
def filterchain() -> Union[vs.VideoNode, Tuple[vs.VideoNode, ...]]:
"""Main VapourSynth filterchain"""
import havsfunc as haf
import lvsfunc as lvf
import vardefunc as vdf
from ccd import ccd
from muvsfunc import SSIM_downsample
from vsutil import depth, get_y
src = JP_BD.clip_cut
src = depth(src, 32)
src_y = get_y(src)
l_mask = vdf.mask.FDOG().get_mask(src_y, lthr=0.065, hthr=0.065).std.Maximum().std.Minimum()
l_mask = l_mask.std.Median().std.Convolution([1] * 9)
# Rescaling
descale = flt.auto_descale(src_y)
desc_i = flt.descale_fields(src_y, kernel=lvf.kernels.BicubicSharp)
descale = lvf.rfs(descale, desc_i, [(1555, 1685)])
supersample = vdf.scale.nnedi3cl_double(descale, use_znedi=True, pscrn=1)
downscaled = SSIM_downsample(supersample, src.width, src.height, smooth=((3 ** 2 - 1) / 12) ** 0.5,
sigmoid=True, filter_param_a=0, filter_param_b=0)
scaled_mask = core.std.MaskedMerge(src_y, downscaled, l_mask)
scaled = depth(vdf.misc.merge_chroma(scaled_mask, src), 16)
# Denoising
l_mask_16 = depth(l_mask, 16).std.Minimum()
dft = core.dfttest.DFTTest(scaled, sigma=1.25, tbsize=3, tosize=1)
dft_masked = core.std.MaskedMerge(dft, scaled, l_mask_16)
ccd_uv = ccd(dft, threshold=4, matrix='709')
ccd_uv = core.std.MaskedMerge(ccd_uv, dft_masked, l_mask_16, planes=[1, 2])
decs = vdf.noise.decsiz(ccd_uv, sigmaS=4, min_in=212 << 8, max_in=240 << 8)
# AA and slight lineart enhancement
baa = lvf.aa.based_aa(decs, shader_file)
sraa = lvf.sraa(decs, rfactor=1.5, downscaler=lvf.kernels.Bicubic(b=-1/2, c=1/4).scale)
clmp = lvf.aa.clamp_aa(decs, baa, sraa, strength=1.5)
sraa_strong = flt.transpose_sraa(decs, rfactor=1.2, downscaler=lvf.kernels.Bicubic(b=-1/2, c=1/4).scale)
clmp = lvf.rfs(clmp, sraa_strong, [])
darken = haf.FastLineDarkenMOD(clmp, strength=36)
# Debanding and graining
deband = core.average.Mean([
flt.masked_f3kdb(darken, rad=18, thr=[28, 24]),
flt.masked_placebo(darken, rad=15, thr=4)
])
grain = vdf.noise.Graigasm(
thrs=[x << 8 for x in (32, 80, 128, 176)],
strengths=[(0.15, 0.0), (0.10, 0.0), (0.10, 0.0), (0.0, 0.0)],
sizes=(1.15, 1.10, 1.05, 1),
sharps=(60, 50, 50, 50),
grainers=[
vdf.noise.AddGrain(seed=69420, constant=True),
vdf.noise.AddGrain(seed=69420, constant=True),
vdf.noise.AddGrain(seed=69420, constant=True)
]).graining(deband)
return grain
def pre_filterchain() -> Union[vs.VideoNode, Tuple[vs.VideoNode, ...]]:
"""
Regular filtering to get the output images to stitch.
This is preferable over handling it unfiltered, since it'll be faster than encoding it
and reduces the amount of jitter caused by the upscale after.
"""
import lvsfunc as lvf
import rekt
import vardefunc as vdf
from awsmfunc import bbmod
from muvsfunc import SSIM_downsample
from vsutil import depth, get_y, join, plane
src = JP_BD.clip_cut
# Fixing animation f**k-ups
if freeze_ranges:
src = core.std.FreezeFrames(
src,
[s[0] for s in freeze_ranges],
[e[1] for e in freeze_ranges],
[f[2] for f in freeze_ranges]
)
# Edgefixing
ef = rekt.rektlvls(
src, prot_val=[16, 235], min=16, max=235,
rownum=[0, src.height-1], rowval=[16, 16],
colnum=[0, src.width-1], colval=[16, 16],
)
bb_y = bbmod(ef, left=1, top=1, right=1, bottom=1, thresh=32, y=True, u=False, v=False)
bb_uv = bbmod(bb_y, left=2, top=2, right=2, bottom=2, y=False, u=True, v=True)
cshift = flt.shift_chroma(bb_uv, left=0.6)
cshift = lvf.rfs(bb_uv, cshift, cshift_left_ranges)
bb32 = depth(cshift, 32)
bb32_y = get_y(bb32)
# Descaling + DPIR while it's at a lower res (so I can actually run it because >memory issues xd)
descale = lvf.kernels.Catrom().descale(bb32_y, 1280, 720)
downscale = lvf.kernels.Catrom(format=vs.YUV444PS).scale(bb32, 1280, 720)
descale_444 = join([descale, plane(downscale, 1), plane(downscale, 2)])
denoise_y = lvf.deblock.vsdpir(descale_444, strength=2.75, mode='deblock', matrix=1, i444=True, cuda=True)
supersample = vdf.scale.fsrcnnx_upscale(get_y(denoise_y), shader_file=shader_file, downscaler=None)
downscaled = SSIM_downsample(supersample, src.width, src.height, smooth=((3 ** 2 - 1) / 12) ** 0.5,
sigmoid=True, filter_param_a=0, filter_param_b=0)
# Create credit mask
upscale = lvf.kernels.Catrom().scale(descale, src.width, src.height)
credit_mask = lvf.scale.descale_detail_mask(bb32_y, upscale, threshold=0.055) \
.std.Deflate().std.Deflate().std.Minimum()
# Merge early for additional accuracy with DPIR
merged = core.std.MaskedMerge(downscaled, bb32_y, credit_mask)
down_y = lvf.kernels.Catrom().scale(merged, src.width/2, src.height/2)
down_i444 = join([down_y, plane(bb32, 1), plane(bb32, 2)])
deblock_down = lvf.deblock.vsdpir(down_i444, strength=3, mode='denoise', matrix=1, i444=True, cuda=True)
scaled = depth(join([merged, plane(deblock_down, 1), plane(deblock_down, 2)]), 16)
# Final bit of "denoising"
dft = core.dfttest.DFTTest(scaled, sigma=2.0, tbsize=5, tosize=3, planes=[0])
decs = vdf.noise.decsiz(dft, sigmaS=4, min_in=208 << 8, max_in=232 << 8)
# AA
baa = lvf.aa.based_aa(decs, str(shader_file))
sraa = lvf.sraa(decs, rfactor=1.65)
clmp = lvf.aa.clamp_aa(decs, baa, sraa, strength=1.3)
dehalo = lvf.dehalo.masked_dha(clmp, rx=1.4, ry=1.4, brightstr=0.4)
cwarp = core.warp.AWarpSharp2(dehalo, thresh=72, blur=3, type=1, depth=4, planes=[1, 2])
# Merge credits (if applicable)
merged = core.std.MaskedMerge(cwarp, depth(bb32, 16), depth(credit_mask, 16))
deband = core.average.Mean([
flt.masked_f3kdb(merged, rad=16, thr=[20, 24], grain=[24, 12]),
flt.masked_f3kdb(merged, rad=20, thr=[28, 24], grain=[24, 12]),
flt.masked_placebo(merged, rad=6, thr=2.5, itr=2, grain=4)
])
no_flt = lvf.rfs(deband, depth(bb32, 16), no_filter)
return no_flt
def filterchain() -> Union[vs.VideoNode, Tuple[vs.VideoNode, ...]]:
"""Main filterchain"""
import lvsfunc as lvf
import rekt
import vardefunc as vdf
from awsmfunc import bbmod
from muvsfunc import SSIM_downsample
from vsutil import depth, get_y
src = JP_BD.clip_cut
rkt = rekt.rektlvls(src, [0, -1], [17, 17], [0, -1], [17, 21])
bb_y = bbmod(rkt, top=2, left=2, right=1, u=False, v=False)
bb_uv = bbmod(bb_y, left=2, right=2, y=False)
bb = depth(bb_uv, 32)
descale = lvf.kernels.Mitchell().descale(get_y(bb), 1280, 720)
up_chr = vdf.scale.to_444(bb, 1920, 1080, True).resize.Bicubic(1280, 720)
descale_merge = vdf.misc.merge_chroma(descale, up_chr)
denoise_down = lvf.deblock.vsdpir(descale_merge, strength=5, mode='deblock', matrix=1, i444=True, cuda=True)
supersample = vdf.scale.nnedi3_upscale(get_y(denoise_down))
downscaled = SSIM_downsample(supersample, bb.width, bb.height, smooth=((3 ** 2 - 1) / 12) ** 0.5,
sigmoid=True, filter_param_a=0, filter_param_b=0)
den_chr_up = core.resize.Bicubic(denoise_down, bb.width, bb.height, bb.format.id)
den_chr_up_shift = core.resize.Bicubic(denoise_down, bb.width, bb.height, bb.format.id, src_left=-0.5)
den_chr_up = lvf.rfs(den_chr_up, den_chr_up_shift, shift_chr)
scaled = vdf.misc.merge_chroma(downscaled, den_chr_up)
scaled = depth(scaled, 16)
decs = vdf.noise.decsiz(scaled, sigmaS=4, min_in=208 << 8, max_in=232 << 8)
deband = core.average.Mean([
flt.masked_f3kdb(decs, rad=17, thr=[20, 24], grain=[24, 12]),
flt.masked_f3kdb(decs, rad=21, thr=[32, 24], grain=[24, 12]),
flt.masked_placebo(decs, rad=6, thr=2.8, itr=2, grain=4)
])
grain = vdf.noise.Graigasm(
thrs=[x << 8 for x in (32, 80, 128, 176)],
strengths=[(0.25, 0.0), (0.20, 0.0), (0.15, 0.0), (0.0, 0.0)],
sizes=(1.25, 1.20, 1.15, 1),
sharps=(80, 70, 60, 50),
grainers=[
vdf.noise.AddGrain(seed=69420, constant=False),
vdf.noise.AddGrain(seed=69420, constant=False),
vdf.noise.AddGrain(seed=69420, constant=True)
]).graining(deband)
grain_str = vdf.noise.Graigasm(
thrs=[x << 8 for x in (32, 80, 128, 176)],
strengths=[(0.35, 0.0), (0.30, 0.0), (0.25, 0.0), (0.0, 0.0)],
sizes=(1.25, 1.20, 1.15, 1),
sharps=(80, 70, 60, 50),
grainers=[
vdf.noise.AddGrain(seed=69420, constant=False),
vdf.noise.AddGrain(seed=69420, constant=False),
vdf.noise.AddGrain(seed=69420, constant=True)
]).graining(deband)
grain = lvf.rfs(grain, grain_str, str_grain)
return grain
def filterchain() -> Union[vs.VideoNode, Tuple[vs.VideoNode, ...]]:
"""Main VapourSynth filterchain"""
import debandshit as dbs
import havsfunc as haf
import lvsfunc as lvf
import rekt
import vardefunc as vdf
from awsmfunc import bbmod
from ccd import ccd
from muvsfunc import SSIM_downsample
from vsutil import depth, get_w, get_y
src = JP_BD.clip_cut
src = depth(src, 16)
rkt_a = rekt.rektlvls(src, [0, 1, -2, -1], [12, -12, -10, 11],
[0, 1, -2, -1], [11, -12, -10, 11])
rkt_b = rekt.rektlvls(src, [0, -1], [15, 15], [0, 1, 2, 3, -4, -2, -1],
[12, 3, -1, 1, 2, 4, 12])
rkt_c = rekt.rektlvls(src, [-2, -1], [6, 11], [0, -2, -1], [15, 10, 15])
bb_c = bbmod(rkt_c, bottom=2, blur=35, y=False)
rkt = lvf.rfs(rkt_a, rkt_b, [(458, 522), (806, 919), (1148, 1179),
(1321, 1442), (1989, 2129)])
rkt = lvf.rfs(rkt, bb_c, [(2130, None)])
ef = depth(rkt, 32)
src_y = get_y(ef)
pre_den = core.dfttest.DFTTest(src_y, sigma=3.0)
l_mask = vdf.mask.FDOG().get_mask(
pre_den, lthr=0.125,
hthr=0.050).rgsf.RemoveGrain(4).rgsf.RemoveGrain(4)
l_mask = l_mask.std.Minimum().std.Deflate().std.Median().std.Convolution(
[1] * 9).std.Maximum()
# Descaling.
descaled = lvf.kernels.Catrom().descale(
src_y, get_w(720, src_y.width / src_y.height), 720)
descaled = core.resize.Bicubic(descaled, format=vs.YUV444P16)
# Slight AA in an attempt to forcibly fix starved lineart.
baa = lvf.aa.based_aa(descaled, shader_file)
sraa = lvf.aa.upscaled_sraa(descaled, rfactor=1.45)
clamp_aa = lvf.aa.clamp_aa(descaled, baa, sraa, strength=1.15)
clamp_aa = depth(get_y(clamp_aa), 32)
# Doing a mixed reupscale using nn3/fsrcnnx, grabbing the darkest parts of each
rescaled_nn3 = vdf.scale.nnedi3cl_double(clamp_aa, use_znedi=True, pscrn=1)
rescaled_fsrcnnx = vdf.scale.fsrcnnx_upscale(clamp_aa, rescaled_nn3.width,
rescaled_nn3.height,
shader_file)
rescaled = core.std.Expr([rescaled_nn3, rescaled_fsrcnnx], "x y min")
downscaled = SSIM_downsample(rescaled,
src_y.width,
src_y.height,
smooth=((3**2 - 1) / 12)**0.5,
sigmoid=True,
filter_param_a=-1 / 2,
filter_param_b=1 / 4)
downscaled = core.std.MaskedMerge(src_y, downscaled, l_mask)
scaled = depth(vdf.misc.merge_chroma(downscaled, ef), 16)
# Chroma warping to forcibly wrap it a bit nicer around the lineart. Also fixing slight shift. 4:2:0 was a mistake.
cwarp = scaled.warp.AWarpSharp2(thresh=72,
blur=3,
type=1,
depth=6,
planes=[1, 2])
# The textures and detail are very smeary, so gotta be careful not to make it even worse
stab = haf.GSMC(cwarp, radius=3, planes=[0], thSAD=75)
den_uv = ccd(stab, threshold=5, matrix='709')
decs = vdf.noise.decsiz(den_uv,
sigmaS=8.0,
min_in=200 << 8,
max_in=240 << 8)
# Scenefiltered debanding. Not graining, since we kept most of the original grain anyway.
deband_wk = dbs.debanders.dumb3kdb(decs,
radius=16,
threshold=[28, 0],
grain=0)
deband_wk = core.placebo.Deband(deband_wk,
iterations=2,
threshold=3.5,
radius=12,
grain=0,
planes=2 | 4)
# Strong denoising + debanding to hopefully deal with all the awful bands. Courtesy of :b:arde
dft = core.dfttest.DFTTest(decs, sigma=4.0)
ccd_uv = ccd(dft, threshold=10, matrix='709')
f3k = dbs.debanders.dumb3kdb(ccd_uv, radius=8, threshold=[36, 24], grain=0)
plac = flt.masked_placebo(f3k,
rad=18,
thr=5.5,
itr=2,
grain=3.0,
mask_args={
'detail_brz': 100,
'lines_brz': 450
})
dft_diff = core.std.MakeDiff(decs, dft)
plac_diff = core.std.MergeDiff(plac, dft_diff)
deband = lvf.rfs(deband_wk, plac_diff, strong_debanding)
return deband
def filterchain() -> Union[vs.VideoNode, Tuple[vs.VideoNode, ...]]:
"""Regular VapourSynth filterchain"""
import EoEfunc.denoise as eoe
import havsfunc as haf
import lvsfunc as lvf
import vardefunc as vdf
from adptvgrnMod import adptvgrnMod
from ccd import ccd
from muvsfunc import SSIM_downsample
from vsutil import depth, get_y, iterate
from xvs import WarpFixChromaBlend
src = JP_clip.clip_cut.std.AssumeFPS(fpsnum=24000, fpsden=1001)
src = depth(src, 16)
# TO-DO: Figure out how they post-sharpened it. Probably some form of unsharpening?
src_y = depth(get_y(src), 32)
descale = lvf.kernels.Bicubic(b=0, c=3 / 4).descale(src_y, 1440, 810)
double = vdf.scale.nnedi3cl_double(descale, pscrn=1)
rescale = depth(SSIM_downsample(double, 1920, 1080), 16)
scaled = vdf.misc.merge_chroma(rescale, src)
denoise_ref = core.dfttest.DFTTest(scaled, sigma=1.8)
denoise = lvf.denoise.bm3d(scaled, sigma=[0.75, 0.65], ref=denoise_ref)
cdenoise = ccd(denoise, threshold=3, matrix='709')
decs = vdf.noise.decsiz(cdenoise,
sigmaS=4,
min_in=208 << 8,
max_in=232 << 8)
# Dehalo fuckery. F**k the sharpening, dude
dehalo = haf.YAHR(decs, blur=2, depth=32)
dehalo_2 = lvf.dehalo.masked_dha(dehalo, ry=2.5, rx=2.5)
halo_mask = lvf.mask.halo_mask(decs, rad=3, brz=0.3, thma=0.42)
dehalo_masked = core.std.MaskedMerge(decs, dehalo_2, halo_mask)
dehalo_min = core.std.Expr([dehalo_masked, decs], "x y min")
# Brightening the lines to undo the unsharpening's line darkening
bright = haf.FastLineDarkenMOD(dehalo_min, strength=-24)
# AA
baa = lvf.aa.based_aa(bright, str(shader_file))
sraa = lvf.sraa(bright, rfactor=1.45)
clmp = lvf.aa.clamp_aa(bright, baa, sraa, strength=1.45)
line_mask = core.std.Prewitt(clmp)
cwarp = WarpFixChromaBlend(clmp, thresh=96, depth=6)
cwarp = core.std.MaskedMerge(cwarp, clmp, line_mask)
upscale = lvf.kernels.Bicubic(b=0, c=3 / 4).scale(descale, 1920, 1080)
credit_mask = lvf.scale.descale_detail_mask(src_y, upscale, threshold=0.08)
credit_mask = iterate(credit_mask, core.std.Deflate, 3)
credit_mask = iterate(credit_mask, core.std.Inflate, 3)
credit_mask = iterate(credit_mask, core.std.Maximum, 2)
merge_credits = core.std.MaskedMerge(cwarp, src, depth(credit_mask, 16))
deband = flt.masked_f3kdb(merge_credits, rad=15, thr=20, grain=[12, 0])
grain: vs.VideoNode = adptvgrnMod(deband,
seed=42069,
strength=0.15,
luma_scaling=10,
size=1.25,
sharp=70,
static=True,
grain_chroma=False)
return grain