Coverage-first live labelling, merged catalog, shelf-intelligence decision
The live path abstained too much: a detected product whose best candidate missed the accept line was left blank, so a shelf where 59% of in-catalog facings were shown read as broken. Show the best candidate immediately as `provisional`, keep the track re-classifiable so a later attempt upgrades or corrects it, and never blank a label already on screen. - identity.py / identity_lanes.py: every decision now carries `provisional_sku` - the row the evidence supports well enough to show, separate from `best_sku`, which still means "cleared the gate". The accept line does not move: far-unknown false accepts stay at 0.066%. - live.py: a below-gate candidate labels the track with `identity_level: provisional` and `confirmed = False`, so the planner and the crop lane keep offering it. Accepted labels stay frozen. Inherited provisional labels stay re-classifiable. - Clients render provisional distinctly (amber chip, dashed box) via `LiveScanOverlayPolicy.isProvisional(identity)`, which now reads the wire level instead of only the state. - build_stock_all.py merges stock, stock-lopia, stock-mediya and stock-milk150 into stock-all (111 images, 60 SKUs). The server could only read one folder, so anything outside it came back blank. stock-demo is byte-identical to mediya+milk150 and is not a source. Measured on add/image6.jpg at live resolution: in-catalog facings shown 59.4% -> 86.0%, correct shown 38 -> 55, precision 97.4% -> 87.3%. On the wire at 8fps 0.5x: 65 of 79 tracks labelled, 742 accepted + 309 provisional observations, first label 1.27s. docs/research/2026-09-29-shelf-intelligence/ carries the experiments and the decision: group signals (combined AUC 0.991 sibling / 0.990 unrelated), OCR scheduling (group representatives cut calls 4.4x and wall 3.3x), and the finding that group propagation damages more labels than it rescues on this shelf, so groups schedule compute rather than overwrite labels. 331 tests pass.
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171 changed files with 554214 additions and 35 deletions
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@ -658,11 +658,36 @@ class DecisionPolicy:
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level = IDENTITY_REJECTED
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message = "No matching evidence"
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# Coverage-first: the row the evidence supports well enough to *show*,
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# even when it does not clear the accept line. `None` means the crop
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# carried no usable evidence at all, which is the only case that still
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# ends blank - a size-only read has no identity text and stays None.
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if answer is not None:
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provisional = answer
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elif local and local[0][1] > 0.0:
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# A vetoed local answer is still the best geometric guess, unless
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# the text named a different row - then that row is the better one.
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vetoed = bool(
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text_top
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and text_top[0] != local[0][0]
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and text_top[1] > local_text_floor(text, local[0][0])
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)
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provisional = text_top[0] if vetoed else local[0][0]
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elif (
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text
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and carries_identity(text_read or "")
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and self._shared_evidence(text_read or "", text[0][0]) >= self.text_min_shared
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):
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provisional = text[0][0]
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else:
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provisional = None
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top_score = local[0][1] if local else (text_top[1] if text_top else 0.0)
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return {
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"status": "success" if level == IDENTITY_ACCEPTED else level,
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"method": self.method,
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"best_sku": answer,
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"provisional_sku": provisional,
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"score": round(float(top_score), 2),
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"confidence": round(float(top_score), 4),
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"identity_level": level,
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