fix: stop re-gating gallery scores in the live path
`score_crop` returns only scores the gallery already accepted: the raw 0.55 line, or the fine-tuned head's own 0.40. The live path then ranked that aggregate with `decide_identity(scale="cosine")`, whose defaults rewrite to COSINE_ACCEPT 0.60 / COSINE_AMBIGUOUS 0.50 - a second, higher line. Every head match between 0.40 and 0.60 was therefore refused or downgraded to ambiguous, which is the live regression: the head's own training views score 0.57-0.77. `engine.inspect` and `_classify_with_gallery` already avoid this by ranking through `decision_for_match`, which applies only the published margin. The live path now does the same: on the cosine scale it passes explicit zero accept lines, so the margin gate is the only extra gate. Regression tests: a 0.45 head-scale match is labelled (fails on the previous code), and a 0.45/0.44 pair inside the margin stays unnamed. Verified: `python -m unittest discover -s code -p 'test_*.py'` - 257 tests, OK, 2 skipped.
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2 changed files with 57 additions and 6 deletions
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@ -1146,9 +1146,17 @@ class LiveSession:
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from identity import aggregate_votes, decide_identity
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mean_scores = aggregate_votes(track.observations)
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if getattr(self.engine, "identity_scale", "inlier") == "cosine":
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# score_crop only returns a score the gallery already accepted, so
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# the aggregate must not be re-gated at COSINE_ACCEPT: that line is
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# above the head's own 0.40 and refused matches the gallery had
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# accepted. Only the margin gate is left to apply.
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decision = decide_identity(
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mean_scores, method=method, scale=getattr(self.engine, "identity_scale", "inlier")
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mean_scores, method=method, scale="cosine",
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min_score=0.0, min_confidence=0.0,
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)
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else:
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decision = decide_identity(mean_scores, method=method)
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track.candidates = [
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{"sku_id": row.get("sku_id"), "score": row.get("score")}
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for row in (decision.get("ranked_candidates") or [])[:3]
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@ -63,6 +63,18 @@ class FakeMatcher:
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return self.score_crop(crop)
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class CosineEngine(RecognitionEngine):
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"""A gallery-scale engine: score_crop only returns scores the gallery accepted."""
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@property
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def identity_scale(self):
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return "cosine"
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def score_crop(self, crop, method=None):
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scores, _ = self.matcher.score_crop(crop, method or "hybrid")
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return scores
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class FakeInventory:
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"""Stateful stand-in for InventoryManager, so stock assertions are real."""
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@ -94,10 +106,10 @@ class FakeInventory:
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return True
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def make_session(matcher=None, settings=None):
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def make_session(matcher=None, settings=None, engine_cls=RecognitionEngine):
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detector = FakeDetector()
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matcher = matcher or FakeMatcher()
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engine = RecognitionEngine(detector, matcher, FakeInventory(),
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engine = engine_cls(detector, matcher, FakeInventory(),
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settings=__import__("engine").EngineSettings(classify_workers=2))
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session = LiveSession("test", engine, settings=settings or LiveSettings(method="hybrid"))
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session.refresh_catalog()
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@ -203,6 +215,37 @@ class LabelLifecycleTests(unittest.TestCase):
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engine.shutdown()
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class CosineScaleTests(unittest.TestCase):
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"""A gallery-scale score is gated by the gallery, not re-gated by the live path."""
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def test_a_head_scale_match_is_labelled(self):
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"""0.45 clears the head's own 0.40 line but not COSINE_ACCEPT (0.60).
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score_crop only returns scores the gallery already accepted, so the live
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aggregate must not re-apply the cosine accept line: that refused every
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head match the gallery had accepted, which is the live regression.
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"""
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session, engine, _, _ = make_session(FakeMatcher(score=0.45), engine_cls=CosineEngine)
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for frame_id in range(1, 5):
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process(session, frame_id)
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self.assertTrue(wait_for(lambda: any(
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track["identity"]["state"] == "recognized" for track in process(session, 5)["tracks"]
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)), "a gallery-accepted head match must be labelled")
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engine.shutdown()
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def test_a_close_cosine_pair_stays_ambiguous(self):
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"""The margin gate still applies: two near-equal scores must not name a SKU."""
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session, engine, _, _ = make_session(FakeMatcher(score=0.45), engine_cls=CosineEngine)
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engine.matcher.score_crop = lambda crop, method=None: {"sku_a": 0.45, "other": 0.44}
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for frame_id in range(1, 8):
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process(session, frame_id)
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result = process(session, 9)
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for track in result["tracks"]:
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self.assertIsNone(track["identity"]["sku_id"],
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"a cosine pair inside the margin must not be named")
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engine.shutdown()
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class TagPassIntegrationTests(unittest.TestCase):
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"""The tag pass must reach the live result without blocking frames."""
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