Files
BGfilter/bgfilter/config.py
T
lhk229 dfc85566c7 Add bf16 precision option for ViTMatte (--precision, default fp32)
bf16 halves the matting model's activation memory -- its full-resolution
attention is the pipeline's memory peak -- with visually identical alpha
(measured: 0 px alpha deviation > 0.25 on samples; cross-check veto
behaviour unchanged, region IoU 0.984).

Guarded by a hardware check so it never lands on a slow emulation path:
CUDA requires torch.cuda.is_bf16_supported(); CPU requires the same
oneDNN native-bf16 gate PyTorch uses for matmul routing (AVX512-BF16/
AMX). Without support it warns and falls back to fp32 -- on a Zen2 EPYC
the fallback kernels measured 17-370x slower than fp32, so silent bf16
there would be a performance landmine.

Segmentation stays fp32: torchvision deform_conv2d (used by BiRefNet)
has no bf16 CPU kernel, and the segmenter is not the memory peak.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-06 13:32:51 +08:00

136 lines
4.9 KiB
Python

from __future__ import annotations
from dataclasses import fields, replace
from pathlib import Path
from typing import Any, TypeVar
from .settings import (
AlphaPostSettings,
ChromaSettings,
CrossCheckSettings,
DespillSettings,
ForegroundSettings,
ModelSettings,
PipelineSettings,
SegmentationSettings,
TrimapSettings,
)
T = TypeVar("T")
# Canonical weights per segmentation backend (selected at runtime via --seg-backend).
_SEG_MODELS = {"birefnet": "ZhengPeng7/BiRefNet", "anime-seg": "skytnt/anime-seg"}
def _load_yaml(path: str | Path) -> dict[str, Any]:
try:
import yaml
except ModuleNotFoundError as exc:
raise RuntimeError("Missing dependency 'PyYAML'. Install it with: pip install PyYAML") from exc
with Path(path).open("r", encoding="utf-8") as handle:
data = yaml.safe_load(handle) or {}
if not isinstance(data, dict):
raise ValueError(f"Config file must contain a YAML mapping: {path}")
return data
def _update_dataclass(instance: T, values: dict[str, Any] | None) -> T:
if not values:
return instance
allowed = {field.name for field in fields(instance)}
unknown = sorted(set(values) - allowed)
if unknown:
cls_name = type(instance).__name__
raise ValueError(f"Unknown {cls_name} field(s): {', '.join(unknown)}")
return replace(instance, **values)
def settings_from_dict(data: dict[str, Any]) -> PipelineSettings:
data = dict(data)
screen_color = data.pop("screen_color", None)
allowed_sections = {"chroma", "trimap", "alpha_post", "cross_check", "foreground", "despill", "model", "segmentation"}
unknown_sections = sorted(set(data) - allowed_sections)
if unknown_sections:
raise ValueError(f"Unknown config section(s): {', '.join(unknown_sections)}")
return PipelineSettings(
chroma=_update_dataclass(ChromaSettings(), data.get("chroma")),
trimap=_update_dataclass(TrimapSettings(), data.get("trimap")),
alpha_post=_update_dataclass(AlphaPostSettings(), data.get("alpha_post")),
cross_check=_update_dataclass(CrossCheckSettings(), data.get("cross_check")),
foreground=_update_dataclass(ForegroundSettings(), data.get("foreground")),
despill=_update_dataclass(DespillSettings(), data.get("despill")),
model=_update_dataclass(ModelSettings(), data.get("model")),
segmentation=_update_dataclass(SegmentationSettings(), data.get("segmentation")),
screen_color=screen_color,
)
def load_settings(path: str | Path | None = None) -> PipelineSettings:
if path is None:
return PipelineSettings()
return settings_from_dict(_load_yaml(path))
def override_settings(settings: PipelineSettings, **overrides: Any) -> PipelineSettings:
chroma = settings.chroma
trimap = settings.trimap
alpha_post = settings.alpha_post
foreground = settings.foreground
despill = settings.despill
model = settings.model
segmentation = settings.segmentation
model_updates = {
key: overrides[key]
for key in ["model_name", "device", "matting_method", "fallback_to_chroma_alpha", "precision"]
if overrides.get(key) is not None
}
trimap_updates = {
key: overrides[key]
for key in [
"sure_bg_threshold",
"sure_fg_threshold",
"unknown_radius_ratio",
"fg_safe_radius_ratio",
]
if overrides.get(key) is not None
}
if overrides.get("trimap_mode") is not None:
trimap_updates["mode"] = overrides["trimap_mode"]
despill_updates: dict[str, Any] = {}
if overrides.get("despill") is not None:
despill_updates["enabled"] = overrides["despill"]
cross_check_updates: dict[str, Any] = {}
if overrides.get("cross_check") is not None:
cross_check_updates["enabled"] = overrides["cross_check"]
seg_updates: dict[str, Any] = {}
if overrides.get("device") is not None:
seg_updates["device"] = overrides["device"]
if overrides.get("seg_backend") is not None:
backend = overrides["seg_backend"]
if backend not in _SEG_MODELS:
raise ValueError(
f"Unknown --seg-backend '{backend}'. Use one of: {', '.join(_SEG_MODELS)}."
)
seg_updates["backend"] = backend
seg_updates["model_name"] = _SEG_MODELS[backend]
screen_color = (
overrides["screen_color"]
if overrides.get("screen_color") is not None
else settings.screen_color
)
return PipelineSettings(
chroma=chroma,
trimap=_update_dataclass(trimap, trimap_updates),
alpha_post=alpha_post,
cross_check=_update_dataclass(settings.cross_check, cross_check_updates),
foreground=foreground,
despill=_update_dataclass(despill, despill_updates),
model=_update_dataclass(model, model_updates),
segmentation=_update_dataclass(segmentation, seg_updates),
screen_color=screen_color,
)