5 Commits

Author SHA1 Message Date
lhk229 08378e57f8 Add anime-seg segmentation backend (SkyTNT ISNet)
Add AnimeSegSegmenter (skytnt/anime-seg ISNet ONNX via onnxruntime, no remote
code) and a make_segmenter factory selected by SegmentationSettings.backend
("birefnet" | "anime-seg"). The ONNX output is already 0..1, so it slots into the
same soft-mask interface BiRefNetSegmenter uses.

On the anime samples anime-seg recovers more and more-coherent hair wisps than
BiRefNet (TestImage2 shoulder rescue: added px 1886 -> 3278, largest connected
component 147 -> 454), as expected from an anime-trained model. Default backend
stays birefnet.

Adds onnxruntime to requirements.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-30 23:58:22 +08:00
lhk229 a6a313d2d0 Add BiRefNet semantic segmentation module
Adds bgfilter/segmentation.py: BiRefNetSegmenter produces a soft subject mask
that defines topology -- it includes colour-contaminated foreground (green-tinted
hair) and excludes see-through holes (finger gaps), the distinction chroma/colour
cues cannot make. Validated on both samples: green hair -> foreground, finger gap
-> background, both correct.

Foundation of the semantic-guided redesign; the mask will drive trimap
construction next, with ViTMatte still refining soft edges.

- SegmentationSettings (ZhengPeng7/BiRefNet, 1024 input, fp32).
- Deps: torchvision, timm, einops, kornia. Weights load from HuggingFace via
  trust_remote_code; behind a firewall set HF_ENDPOINT=https://hf-mirror.com and
  bypass the proxy.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-30 21:07:24 +08:00
lhk229 9b7a192599 Use pymatting ML foreground estimation to remove edge spill
After the full-foreground despill (5ddf0cd) the residual green was confined to
semi-transparent hair (alpha < 0.5): 85% of the worst pixels had alpha < 0.3,
where a pixel-wise unmix (divide by small alpha) is too noisy to trust.

Replace the hand-rolled unmix/local-blur estimator with pymatting's
estimate_foreground_ml (Germer et al. multi-level closed form), which propagates
reliable foreground colour from high-alpha neighbours into the fringe and
estimates the background, so green spill is unmixed rather than clamped. The
despill pass stays as a light cleanup on top.

- foreground.method selects "ml" (default) or "unmix" (legacy heuristic kept as
  a fallback when pymatting is unavailable, matching the chroma fallback idiom).
- ForegroundEstimate now exposes rgb (F), background (B) and a correction map;
  debug outputs become foreground_rgb / foreground_background / foreground_correction.

Controlled comparison (same ViTMatte alpha, only foreground method changed),
edge_green_excess:
  TestImage  p95 0.176->0.031, mean 0.061->0.005
  TestImage2 p95 0.165->0.004, mean 0.052->0.002

Adds pymatting (pulls in numba) to requirements.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-30 17:33:35 +08:00
Codex 10705d49df Support YAML pipeline configuration 2026-06-30 15:03:15 +08:00
Codex 8fc53925e0 Implement green screen matting pipeline 2026-06-30 14:14:15 +08:00