Files
BGfilter/bgfilter/settings.py
T
lhk229 62f175948e Auto-detect the background colour (default); drop the green heuristic
Replace the hardcoded green-screen auto-detection with a general flat-colour
detector. When screen_color is null the background colour is now detected from the
image border (dominant colour of the border strip) and used directly as the chroma
model, with a failure gate that raises when the border is not one clean flat colour
(gradient / texture / subject filling the frame).

- chroma: add detect_background_color + _background_border_cluster; the null case of
  estimate_background_model samples the detected cluster directly (no seed search);
  compute_bg_confidence is now always perceptual (Lab/RGB distance). Removed the green
  heuristic (initial_green_candidates), the green multiplicative gating, the now-unused
  _smoothstep, and five green-only ChromaSettings fields.
- pipeline: reuse the detected colour for de-spill in the auto case.
- settings / default.yaml: add detect_* tuning fields; refresh screen_color docs.
- README: document auto-detection + the failure gate, trimap modes, birefnet config.

A supplied --screen-color hex still uses the seed-search refinement. Validated:
detects green / pastel / text samples correctly, raises on gradient / two-colour, CLI
exits 1 on failure, green and pastel mattes unchanged in quality.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-01 20:34:31 +08:00

123 lines
4.9 KiB
Python

from __future__ import annotations
from dataclasses import dataclass
@dataclass(frozen=True)
class ChromaSettings:
border_ratio: float = 0.04
min_samples: int = 2048
hue_sigma_min: float = 7.0
lab_sigma_min: float = 10.0
rgb_sigma_min: float = 0.08
# Background-colour auto-detection (used when screen_color is None): find the
# flat colour that dominates the image border; raise if none is clean enough.
detect_cluster_radius: float = 12.0 # Lab radius grouping border pixels into the background cluster
detect_min_border_share: float = 0.55 # min fraction of the border that must be this one colour
detect_corner_tol: float = 20.0 # max Lab distance a corner may sit from the cluster centre
@dataclass(frozen=True)
class TrimapSettings:
sure_bg_threshold: float = 0.92
sure_fg_threshold: float = 0.12
unknown_radius_ratio: float = 0.012
fg_safe_radius_ratio: float = 0.006
min_unknown_radius: int = 4
min_fg_safe_radius: int = 2
# Semantic fusion thresholds (used by fuse_trimap when segmentation is on).
seg_core_threshold: float = 0.60
seg_loose_threshold: float = 0.08
# Trimap mode for the segmentation pipeline (the chroma-only pipeline ignores it):
# "directional" (default) -- chroma magnitude + seg + a hue-direction split. In
# the chroma-unknown zone a confidently-segmented pixel stays foreground
# unless it is displaced toward the background hue: a neutral background-
# coloured garment (e.g. a white shirt) is kept, while a background-hued
# residual (e.g. blue trapped between hair strands) is left UNKNOWN for
# ViTMatte / chroma-suppress to clear.
# "seg" -- original fuse_trimap: seg topology + chroma veto, no hue split.
# "directional-hard-bg" -- like "directional" but hard-marks background-hued
# pixels as background; more aggressive, can eat cool/shadowed white cloth.
mode: str = "directional"
seg_low: float = 0.15 # seg below this -> background-eligible; at/above -> foreground-eligible
bg_hue_proj_min: float = 4.0 # Lab a*/b* projection onto bg direction above which a pixel is background-hued
@dataclass(frozen=True)
class AlphaPostSettings:
min_component_area_ratio: float = 0.00001
fill_hole_area_ratio: float = 0.00002
alpha_floor: float = 0.002
alpha_ceil: float = 0.998
# Chroma-guided alpha suppression: in the unknown band, pull alpha toward 0
# where background (green) confidence is high, clearing spill in gaps/holes.
chroma_suppress: bool = True
chroma_suppress_bg_low: float = 0.35
chroma_suppress_bg_high: float = 0.80
chroma_suppress_strength: float = 1.0
@dataclass(frozen=True)
class ForegroundSettings:
enabled: bool = True
method: str = "ml" # "ml" (pymatting) or "unmix" (legacy heuristic)
fallback_to_unmix: bool = True
ml_regularization: float = 1e-5
# Legacy "unmix" method parameters (used only when method == "unmix").
edge_low: float = 0.005
edge_high: float = 0.995
min_unmix_alpha: float = 0.08
unmix_strength: float = 0.70
local_strength: float = 0.45
local_blur_radius: int = 11
local_alpha_threshold: float = 0.92
local_bg_confidence_max: float = 0.20
green_excess_margin: float = 0.015
bg_confidence_weight: float = 0.70
@dataclass(frozen=True)
class DespillSettings:
enabled: bool = True
edge_low: float = 0.005
strength: float = 0.92
green_excess_margin: float = 0.015
edge_expand_radius: int = 2
alpha_weight_floor: float = 0.35
# Custom-screen despill (when screen_color is set): margin, in Lab a*/b*
# units, of chroma allowed along the background colour direction before it is
# treated as spill. Larger keeps more of the subject's own colour.
color_margin_lab: float = 4.0
@dataclass(frozen=True)
class ModelSettings:
model_name: str = "hustvl/vitmatte-small-composition-1k"
device: str = "cuda"
matting_method: str = "vitmatte"
fallback_to_chroma_alpha: bool = False
@dataclass(frozen=True)
class SegmentationSettings:
enabled: bool = True # False = chroma-only pipeline (no seg model)
backend: str = "anime-seg" # "anime-seg" or "birefnet"
model_name: str = "skytnt/anime-seg"
device: str = "cuda"
input_size: int = 1024
@dataclass(frozen=True)
class PipelineSettings:
chroma: ChromaSettings = ChromaSettings()
trimap: TrimapSettings = TrimapSettings()
alpha_post: AlphaPostSettings = AlphaPostSettings()
foreground: ForegroundSettings = ForegroundSettings()
despill: DespillSettings = DespillSettings()
model: ModelSettings = ModelSettings()
segmentation: SegmentationSettings = SegmentationSettings()
# Background-colour prior. None = auto-detect the flat background colour from the
# image border (raises if there is no clean flat background). A hex string like
# "#CFEFFF" sets it explicitly.
screen_color: str | None = None