Files
face-sets/sort_faces.py
Peter d53ab9fbfc Add enrich + export-swap pipeline for downstream face-swap ready output
- enrich: re-detects each cached face with buffalo_l (detection +
  landmark_2d_106 + landmark_3d_68, recognition module skipped for speed)
  and persists landmarks + pose into the cache so per-face frontality and
  landmark-symmetry quality signals become available.
- compute_quality: composite score combining det_score, face short-edge,
  blur, frontality (from pose pitch/yaw), and 2D-landmark symmetry with
  tunable weights. Default weighting 0.30/0.20/0.20/0.15/0.15.
- export-swap: builds facesets_swap_ready/ from an existing refine
  manifest. Per identity: tighter outlier gate (default 0.45), visual-
  near-dupe collapse (keep best representative per group), multi-face-
  per-source-image collapse (keep best bbox), rank by composite score,
  single-face-per-PNG crops at 512x512 with 0.5 bbox padding, ready-to-
  drop .fsz bundles (top-N + full), per-faceset manifest.json, NAME.txt
  placeholder for the operator. The multi-face-per-PNG collapse is the
  critical fix: roop-unleashed's .fsz loader appends every detected face
  in each PNG to the FaceSet, so any multi-face crop would contaminate
  the averaged embedding.
- Optional --candidates rescues raw_full singletons: matches against the
  final per-faceset centroids and routes to _candidates/to_<faceset>/
  for manual review; orphaned singletons that still cluster among
  themselves land in _candidates/new_<NNN>/.
- docs/analysis/: evaluation document captures the evidence, downstream
  requirements (FaceSet averaging, inswapper_128), opportunity matrix
  (R1-R14), and the recommended target state this export implements.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-23 22:37:32 +02:00

60 KiB