P6 — Image→Persona Analyzer

Feature flag: features.enable_image2persona (defaults false). Keep the flag off until the modder/QA lane verifies pipelines and hashes.
Checker: python tools/check_current_system.py --profile p6_image2persona --base http://127.0.0.1:8001

Intent

Turn 1–N reference images into structured Persona hints: appearance tags, color palette, pose anchors, expression prototypes, and downstream style/LoRA suggestions. The analyzer is deterministic (hash-stable) so assets can be versioned, diffed, and merged with the Persona schema and provenance logs.

Pipeline Overview

1. Normalization – Each image is EXIF-transposed and converted to RGB before hashing (sha1(version + dims + bytes)) to guarantee stable digests and provenance sidecars.
2. Palette extraction – RGB median-cut quantization (5–8 swatches) produces normalized swatches (hex, rgb, luma, ratio, name). Sorting favours coverage, then hex to keep output stable across runs.
3. Appearance tagging – Heuristics derive species, fur_skin, colorways, accent_colors, and clothing_motifs from palette statistics (with optional contributor overrides via hooks).
4. Pose anchors – A grayscale percentile mask estimates a subject bounding box; anchors are emitted for face, hands, and feet with normalized coordinates and confidence scores.
5. Expression prototypes – Brightness/contrast metrics seed a neutral baseline plus optional smile, soft_smile, and anger prototypes. Each carries mood, trigger hints, and average confidence.
6. Style fusion – Appearance tags feed StyleSuggestionRegistry, returning studio-friendly style hints plus optional LoRA names (names only, no URLs/downloads).
7. Merge – Multiple images merge through weighted averages. Conflicts (e.g., disagreeing species or primary_color) are surfaced for review.

The top-level summary lives under metadata.image2persona when merged into a Persona profile and includes:

{
  "appearance": {...},
  "palette": [...],
  "pose_anchors": {...},
  "expression_set": {...},
  "style": {
    "styles": [{"id": "studio-portrait-soft", "priority": 0.6}],
    "lora": [{"name": "portraitplus-v15", "priority": 0.55}],
    "applied_tags": ["species:human", "clothing:minimalist"]
  },
  "conflicts": [{"field": "appearance.species", "values": ["human", "unspecified"]}]
}

Python API

from comfyvn.persona.image2persona import (
    analyze_images,
    ImagePersonaAnalyzer,
    PersonaImageOptions,
)

sources = ["./persona_refs/front.png", "./persona_refs/profile.png"]
options = PersonaImageOptions(debug=True)
suggestion = analyze_images(sources, persona_id="heroine-01", options=options)

print(suggestion.summary["appearance"]["colorways"])
# ['primary:warm:orange', 'secondary:neutral:stone', 'accent:cool:teal']

profile = {}
analyzer = ImagePersonaAnalyzer(options)
merged_profile = analyzer.merge_into_persona_profile(profile, suggestion)

• PersonaImageOptions.hooks accepts optional callables (appearance, palette, anchors, expressions, summary) for modder overrides. Each hook receives the current payload and can return replacements/patches.
• options.debug=True attaches metrics, palette tokens, and anchor boxes to each per-image report for tooling dashboards.
• Output is fully JSON serializable; call suggestion.as_json(indent=2) to persist snapshots for reviews.

Style & LoRA Suggestions

comfyvn/persona/style_suggestions.py ships a baseline registry. Contributors can extend it:

from comfyvn.persona.style_suggestions import StyleSuggestionRegistry

registry = StyleSuggestionRegistry.default()
registry.register_style("species:android", "hard-light-cyberpunk", 0.7)
registry.register_lora("colorway:accent:cool:teal", "cyan-rim-v12", 0.5)

options = PersonaImageOptions(style_registry=registry)

The analyzer only surfaces names; downstream fetchers are intentionally out-of-scope.

Debugging & Determinism

• Hashes include the analyzer version string (p6.image2persona.v1). Bumping the algorithm requires updating ANALYZER_VERSION and documenting changes in the changelog.
• conflicts enumerate mismatched attributes so producers can reconcile persona packs manually.
• Enable LOG_LEVEL=DEBUG and wrap extractor calls to log suggestion.provenance for QA pipelines.
• Smoke tests: feed the same image set twice and assert identical summary_digest values. Mix formats (PNG/JPEG/WebP) to confirm EXIF normalization.

Integration Notes

• Persona Manager consumers should treat metadata.image2persona as advisory data. Leave canonical persona fields (name, expression, poses) unchanged unless the user confirms merges.
• GUI/CLI panels can surface the palette and anchor previews by reading PersonaSuggestion.per_image[*].debug when debug mode is enabled.
• Feature flag stays off until p6_image2persona checker passes (docs, files, flag defaults, API surface).