Peter
484278e70e
- embed: sha256-based dedup at listing (embed each unique hash once, carry other paths as aliases via a top-level path_aliases dict); resumable from any existing cache; atomic incremental flush every 50 files; explicit skip-ext filtering; schema bumped with processed_paths + path_aliases. - extend: new subcommand that merges new embeddings into an existing raw + facesets output without renumbering. Nearest person-centroid match above threshold, unmatched faces re-clustered into new person_NNN / _singletons. Optional --refine-out also extends facesets by centroid + quality gate. - dedup: new subcommand producing byte-identical + visual near-duplicate groups as a JSON report. - cluster/refine: fan every placement across canonical + aliases so each on-disk location gets represented. - safe_dst_name now always flattens the absolute path so filenames stay stable across runs when src_root shifts (fixes duplicate-copy bug that surfaced during the lzbkp_red extend). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
57 lines
3.2 KiB
Markdown
57 lines
3.2 KiB
Markdown
# face-sets
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Sort photos by similar face using InsightFace embeddings + agglomerative clustering, then refine into faceset-ready folders for downstream face-swap tooling (roop-unleashed, etc.).
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## Pipeline
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`sort_faces.py` is a single-file CLI with four subcommands:
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| step | what it does |
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|---------|------------------------------------------------------------------------------|
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| embed | Recursively scan a source tree, detect + embed every face, write `.npz` cache |
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| cluster | Raw agglomerative clustering of the cache into `person_NNN/` / `_singletons/` / `_noface/` |
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| refine | Initial cluster → centroid merge → quality gate → outlier rejection → size filter → `faceset_NNN/` |
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| dedup | Post-hoc near-duplicate report: byte-identical groups + visual near-dupes (same face + same size within a tight cosine threshold) |
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`embed` is resumable and incremental: it loads any existing cache at the target path and only hashes/embeds files it hasn't processed before. A periodic flush (default every 50 new files) writes the cache atomically, so a mid-run crash loses at most a few dozen embeddings.
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Byte-identical duplicates are detected via sha256 during the listing phase. The canonical file is embedded once; other paths with the same hash are carried as `aliases` on the cache's top-level `path_aliases` dict. Every alias is materialized by `cluster`/`refine`, so each on-disk location ends up represented in the output.
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Cache and outputs are kept out of the repo via `.gitignore`; defaults live under `work/`.
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## Typical run
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```bash
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# 1. Embed (CPU; InsightFace buffalo_l). Caches faces + metadata. Resumable.
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python sort_faces.py embed /mnt/x/src/nl work/cache/nl_full.npz
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# 2. Raw clusters (every multi-face cluster -> a person_NNN/ folder).
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python sort_faces.py cluster work/cache/nl_full.npz /mnt/e/temp_things/fcswp/nl_sorted/raw_full
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# 3. Refined facesets (filters for faceset-ready quality).
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python sort_faces.py refine work/cache/nl_full.npz /mnt/e/temp_things/fcswp/nl_sorted/facesets_full
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# 4. (Optional) report on byte-identical + visual near-duplicates.
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python sort_faces.py dedup work/cache/nl_full.npz
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```
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## Refine defaults
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| flag | default | meaning |
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|---|---|---|
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| `--initial-threshold` | 0.55 | cosine distance for stage-1 clustering |
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| `--merge-threshold` | 0.40 | centroid-level merge of over-split clusters |
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| `--outlier-threshold` | 0.55 | drop face if cosine dist from cluster centroid exceeds this (only if cluster ≥ 4) |
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| `--min-faces` | 15 | minimum unique images per faceset |
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| `--min-short` | 90 | minimum short-edge pixels of face bbox |
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| `--min-blur` | 40.0 | Laplacian-variance blur gate |
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| `--min-det-score` | 0.6 | InsightFace detector score gate |
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| `--mode` | copy | copy / move / symlink |
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## Prior runs (as of 2026-04-22)
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- `work/cache/kos11.npz` — 181 images, 333 faces from `Kos '11/` → `kos11_sorted/`
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- `work/cache/nl_all.npz` — 916 images, 1396 faces from `Neuer Ordner (2)/New Folder/` → `nl_sorted/raw/`, refined to 6 facesets (197, 120, 91, 47, 23, 18 images)
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Output lives outside the repo at `/mnt/e/temp_things/fcswp/`.
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