9bb4211722
Applied tags aren't scored live, so compute the grounding on demand: run the
tag's head over the image's max-over-bag (whole-image + concept crops), argmax
→ the region that best explains the tag on this image, mirroring what
score_image records for live suggestions.
- heads.py: extract _image_bag (now shared by score_image) + ground_applied_tag.
Returns (grounding, has_head): has_head False = no head to localize with →
no overlay; grounding None = the whole-image vector won → whole-image frame.
- tags.py: GET /api/images/<id>/tags/<id>/grounding → {grounding, has_head}.
- TagChip/TagPanel: applied chips inject fcSuggestionHover and fetch grounding
on hover (cached per image+tag, race-guarded), reusing Step 3's overlay in
both the modal and Explore. No new frontend overlay code.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM
344 lines
14 KiB
Python
344 lines
14 KiB
Python
"""Suggestion read-path (tagging-v2): suggestions come from trained HEADS, not
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Camie predictions or centroids. Heads are inserted directly (training needs
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scikit-learn, ml image only); scoring is numpy-only (available via pgvector)."""
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import pytest
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from sqlalchemy import select
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from backend.app.models import ImageRecord, ImageRegion, MLSettings, TagHead, TagKind
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from backend.app.models.tag import image_tag
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from backend.app.services.ml.allowlist import AllowlistService
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from backend.app.services.ml.heads import ground_applied_tag
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from backend.app.services.ml.suggestions import SuggestionService
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from backend.app.services.tag_service import TagService
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pytestmark = pytest.mark.integration
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def _emb(slot: int, val: float = 3.0) -> list[float]:
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"""An embedding pointing along axis `slot` (so its L2-normalized form is the
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unit vector e_slot — a head with weights e_slot scores it sigmoid(1)≈0.73)."""
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v = [0.0] * 1152
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v[slot] = val
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return v
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async def _img(db, sha: str, emb=None) -> ImageRecord:
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img = ImageRecord(
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path=f"/images/{sha}.jpg", sha256=sha, size_bytes=1, mime="image/jpeg",
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width=1, height=1, origin="imported_filesystem",
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integrity_status="unknown", siglip_embedding=emb,
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)
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db.add(img)
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await db.flush()
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return img
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async def _embver(db) -> str:
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s = (await db.execute(select(MLSettings).where(MLSettings.id == 1))).scalar_one()
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return s.embedder_model_version
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async def _head(db, tag_id: int, slot: int, suggest_threshold: float = 0.5):
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weights = [0.0] * 1152
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weights[slot] = 1.0
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db.add(TagHead(
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tag_id=tag_id, embedding_version=await _embver(db),
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weights=weights, bias=0.0, suggest_threshold=suggest_threshold,
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auto_apply_threshold=None, n_pos=10, n_neg=30,
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ap=0.8, precision_cv=0.9, recall=0.6,
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))
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@pytest.mark.asyncio
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async def test_head_suggestion_surfaces_for_matching_image(db):
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tag = await TagService(db).find_or_create("glasses", TagKind.general)
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img = await _img(db, "a" * 64, _emb(0))
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await _head(db, tag.id, slot=0)
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await db.commit()
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sl = await SuggestionService(db).for_image(img.id)
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general = sl.by_category["general"]
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assert len(general) == 1
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s = general[0]
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assert s.canonical_tag_id == tag.id
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assert s.source == "head"
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assert s.creates_new_tag is False
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assert s.via_alias is False and s.raw_name is None
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assert s.score > 0.5
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@pytest.mark.asyncio
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async def test_no_embedding_means_no_suggestions(db):
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img = await _img(db, "b" * 64, None)
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tag = await TagService(db).find_or_create("cat", TagKind.general)
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await _head(db, tag.id, slot=0)
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await db.commit()
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assert (await SuggestionService(db).for_image(img.id)).by_category == {}
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@pytest.mark.asyncio
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async def test_no_heads_means_no_suggestions(db):
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img = await _img(db, "c" * 64, _emb(0))
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await db.commit() # no heads trained yet
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assert (await SuggestionService(db).for_image(img.id)).by_category == {}
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@pytest.mark.asyncio
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async def test_applied_tag_not_suggested(db):
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tag = await TagService(db).find_or_create("dog", TagKind.general)
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img = await _img(db, "d" * 64, _emb(0))
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await _head(db, tag.id, slot=0)
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await db.execute(
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image_tag.insert().values(
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image_record_id=img.id, tag_id=tag.id, source="manual"
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)
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)
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await db.commit()
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sl = await SuggestionService(db).for_image(img.id)
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assert "general" not in sl.by_category or not sl.by_category["general"]
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@pytest.mark.asyncio
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async def test_threshold_override_surfaces_below_cut(db):
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# A head with a high suggest_threshold won't surface on a so-so score, but
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# the dropdown's override=0 floor surfaces every head regardless.
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tag = await TagService(db).find_or_create("horse", TagKind.general)
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img = await _img(db, "e" * 64, _emb(1)) # orthogonal to the head → score 0.5
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await _head(db, tag.id, slot=0, suggest_threshold=0.6)
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await db.commit()
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svc = SuggestionService(db)
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assert svc and not (await svc.for_image(img.id)).by_category.get("general")
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flooded = await svc.for_image(img.id, threshold_override=0.0)
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assert any(s.canonical_tag_id == tag.id for s in flooded.by_category["general"])
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@pytest.mark.asyncio
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async def test_system_tag_surfaces_at_flat_floor_despite_high_threshold(db):
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# A system tag's head uses the flat _SYSTEM_TAG_SUGGEST_FLOOR (0.65), not its
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# precision-tuned suggest_threshold — so a matching image (~0.73) surfaces it
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# for rejection even though its 0.9 auto threshold would hide it.
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from backend.app.services.ml.heads import _SYSTEM_TAG_SUGGEST_FLOOR
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assert _SYSTEM_TAG_SUGGEST_FLOOR == 0.65
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tag = await TagService(db).find_or_create("wip sketchy", TagKind.general)
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tag.is_system = True
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img = await _img(db, "1" * 64, _emb(0)) # matches head → ~0.73
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await _head(db, tag.id, slot=0, suggest_threshold=0.9)
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await db.commit()
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sl = await SuggestionService(db).for_image(img.id)
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# System tags surface under their OWN "system" category, not "general".
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assert any(
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s.canonical_tag_id == tag.id for s in sl.by_category.get("system", [])
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)
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assert not sl.by_category.get("general")
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@pytest.mark.asyncio
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async def test_system_tag_below_floor_stays_hidden(db):
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# Below the 0.65 floor (~0.5 on an orthogonal image) the system tag is not
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# surfaced — the floor still gates, it isn't "always show".
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tag = await TagService(db).find_or_create("wip faint", TagKind.general)
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tag.is_system = True
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img = await _img(db, "2" * 64, _emb(1)) # orthogonal → 0.5
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await _head(db, tag.id, slot=0, suggest_threshold=0.9)
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await db.commit()
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sl = await SuggestionService(db).for_image(img.id)
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assert not sl.by_category.get("system")
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@pytest.mark.asyncio
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async def test_content_tag_ignores_system_floor(db):
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# A NON-system head with the same high threshold does NOT get the floor: the
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# ~0.73 match stays hidden below its 0.9 auto threshold (floor is system-only).
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tag = await TagService(db).find_or_create("glasses hi", TagKind.general)
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img = await _img(db, "3" * 64, _emb(0)) # matches head → ~0.73
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await _head(db, tag.id, slot=0, suggest_threshold=0.9)
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await db.commit()
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sl = await SuggestionService(db).for_image(img.id)
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assert not sl.by_category.get("general")
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@pytest.mark.asyncio
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async def test_concept_region_surfaces_via_max_over_bag(db):
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# Max-over-bag: the whole-image vector is orthogonal to the head (scores the
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# 0.5 midpoint, under a 0.7 cut → nothing), but a concept CROP that aligns
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# with the head lifts the max over the bag above the cut. A small/local
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# concept surfaces ONLY because of the crop.
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tag = await TagService(db).find_or_create("glasses", TagKind.general)
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img = await _img(db, "b1" * 32, _emb(5)) # whole-image ⟂ head
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await _head(db, tag.id, slot=0, suggest_threshold=0.7)
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await db.commit()
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# Whole-image alone: sigmoid(0)=0.5 < 0.7 → no suggestion.
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assert not (await SuggestionService(db).for_image(img.id)).by_category.get("general")
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# A concept crop aligned with the head, but stamped with a STALE model
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# version → filtered out of the bag, so still nothing.
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db.add(ImageRegion(
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image_record_id=img.id, kind="concept",
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rx=0.1, ry=0.1, rw=0.3, rh=0.3,
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siglip_embedding=_emb(0), embedding_version="stale-embedder-v0",
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))
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await db.commit()
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assert not (await SuggestionService(db).for_image(img.id)).by_category.get("general")
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# A matching-version concept crop → max-over-bag lifts it over the cut.
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db.add(ImageRegion(
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image_record_id=img.id, kind="concept",
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rx=0.4, ry=0.4, rw=0.3, rh=0.3,
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siglip_embedding=_emb(0), embedding_version=await _embver(db),
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))
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await db.commit()
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general = (await SuggestionService(db).for_image(img.id)).by_category["general"]
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s = next(x for x in general if x.canonical_tag_id == tag.id)
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assert s.score > 0.7
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# #1206: the winning crop grounds the tag — hover highlights THIS region
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# (the matching-version crop at 0.4,0.4,0.3,0.3), not the whole image.
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assert s.grounding is not None
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assert s.grounding["bbox"] == pytest.approx([0.4, 0.4, 0.3, 0.3])
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assert s.grounding["kind"] == "concept"
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@pytest.mark.asyncio
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async def test_grounding_none_when_whole_image_wins(db):
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# #1206: when the whole-image vector (not a crop) produces the winning score,
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# grounding is None — the tag came from the global vector, not a region.
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tag = await TagService(db).find_or_create("sky", TagKind.general)
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img = await _img(db, "d1" * 32, _emb(0)) # whole-image ALIGNED w/ head
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await _head(db, tag.id, slot=0, suggest_threshold=0.5)
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db.add(ImageRegion( # an orthogonal crop (0.5)
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image_record_id=img.id, kind="concept",
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rx=0.1, ry=0.1, rw=0.2, rh=0.2,
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siglip_embedding=_emb(5), embedding_version=await _embver(db),
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))
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await db.commit()
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general = (await SuggestionService(db).for_image(img.id)).by_category["general"]
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s = next(x for x in general if x.canonical_tag_id == tag.id)
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assert s.grounding is None
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@pytest.mark.asyncio
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async def test_stale_embedding_version_excluded_from_scoring(db):
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# Mid model-swap (#1190): an image still carrying an OLD-version whole-image
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# embedding must NOT be scored by heads trained in the new model's space —
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# even though the vector aligns with the head, it's the wrong coordinate
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# system, so nothing surfaces until it's re-embedded.
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tag = await TagService(db).find_or_create("glasses", TagKind.general)
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img = await _img(db, "c1" * 32, _emb(0))
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img.siglip_model_version = "some-old-model-v0" # != current embedder
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await _head(db, tag.id, slot=0, suggest_threshold=0.5)
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await db.commit()
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assert not (await SuggestionService(db).for_image(img.id)).by_category.get("general")
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@pytest.mark.asyncio
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async def test_rejected_tag_surfaced_flagged_then_reversible(db):
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# A dismissed suggestion is NOT dropped: it stays flagged rejected so the
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# rail can show it + offer one-click un-reject (operator-asked 2026-06-27).
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tag = await TagService(db).find_or_create("goblin", TagKind.general)
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img = await _img(db, "f" * 64, _emb(0))
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await _head(db, tag.id, slot=0)
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await db.commit()
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await AllowlistService(db).dismiss(img.id, tag.id)
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await db.commit()
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sl = await SuggestionService(db).for_image(img.id)
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s = next(x for x in sl.by_category["general"] if x.canonical_tag_id == tag.id)
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assert s.rejected is True
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await AllowlistService(db).undismiss(img.id, tag.id)
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await db.commit()
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sl2 = await SuggestionService(db).for_image(img.id)
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s2 = next(x for x in sl2.by_category["general"] if x.canonical_tag_id == tag.id)
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assert s2.rejected is False
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async def _figure(db, image_id, slot):
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v = [0.0] * 768
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v[slot] = 1.0
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db.add(ImageRegion(
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image_record_id=image_id, kind="figure",
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rx=0.0, ry=0.0, rw=1.0, rh=1.0,
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ccip_embedding=v, embedding_version="ccip-test",
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))
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@pytest.mark.asyncio
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async def test_ccip_character_surfaces_in_rail(db):
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# A character with a CCIP reference (a tagged figure) is suggested on a new
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# image whose figure matches — overlaid into the rail alongside the heads.
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raven = await TagService(db).find_or_create("Raven", TagKind.character)
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ref = await _img(db, "0" * 64, None) # the operator's tagged example
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await _figure(db, ref.id, slot=0)
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await db.execute(image_tag.insert().values(
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image_record_id=ref.id, tag_id=raven.id, source="manual",
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))
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query = await _img(db, "1" * 64, None) # untagged, matching figure
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await _figure(db, query.id, slot=0)
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await db.commit()
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sl = await SuggestionService(db).for_image(query.id)
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m = next(
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c for c in sl.by_category.get("character", [])
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if c.canonical_tag_id == raven.id
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)
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assert m.source == "ccip"
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# --- #1206 Step 4: on-demand grounding for ALREADY-APPLIED tag chips ---------
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# Applied tags aren't scored live, so ground_applied_tag recomputes the winning
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# bag row for one tag's head on demand — the data behind hovering an applied chip.
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@pytest.mark.asyncio
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async def test_ground_applied_tag_returns_winning_region(db):
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# Whole-image vector is orthogonal to the head; a concept crop aligns with it,
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# so the crop is the max-over-bag winner → grounding is THAT region's box.
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tag = await TagService(db).find_or_create("glasses", TagKind.general)
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img = await _img(db, "g1" * 32, _emb(5)) # whole-image ⟂ head
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await _head(db, tag.id, slot=0)
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db.add(ImageRegion(
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image_record_id=img.id, kind="concept",
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rx=0.4, ry=0.4, rw=0.3, rh=0.3,
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siglip_embedding=_emb(0), embedding_version=await _embver(db),
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))
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await db.commit()
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grounding, has_head = await ground_applied_tag(db, img.id, tag.id)
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assert has_head is True
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assert grounding is not None
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assert grounding["bbox"] == pytest.approx([0.4, 0.4, 0.3, 0.3])
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assert grounding["kind"] == "concept"
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@pytest.mark.asyncio
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async def test_ground_applied_tag_none_when_whole_image_wins(db):
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# Whole-image vector aligns with the head and out-scores an orthogonal crop →
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# grounding None (has_head True): the tag is best explained by the global
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# vector, so the chip hover shows the subtle whole-image frame, not a box.
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tag = await TagService(db).find_or_create("sky", TagKind.general)
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img = await _img(db, "g2" * 32, _emb(0)) # whole-image ALIGNED
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await _head(db, tag.id, slot=0)
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db.add(ImageRegion(
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image_record_id=img.id, kind="concept",
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rx=0.1, ry=0.1, rw=0.2, rh=0.2,
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siglip_embedding=_emb(5), embedding_version=await _embver(db),
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))
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await db.commit()
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grounding, has_head = await ground_applied_tag(db, img.id, tag.id)
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assert has_head is True
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assert grounding is None
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@pytest.mark.asyncio
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async def test_ground_applied_tag_no_head(db):
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# A tag with no head in the current space (manual/artist/meta, or below the
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# head floor) can't be localized → (None, has_head False); the UI draws no
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# overlay at all, distinct from "the whole image won".
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tag = await TagService(db).find_or_create("artist:someone", TagKind.general)
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img = await _img(db, "g3" * 32, _emb(0))
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await db.commit()
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grounding, has_head = await ground_applied_tag(db, img.id, tag.id)
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assert has_head is False
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assert grounding is None
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