Two false positives came out of running the rules against a real shelf, and both
had the same shape: the rules were arguing with our own detector instead of with
the shelf.
1. One tag per product, not per facing. Measured: a row carries 16-18 facings but
only 4-5 tags, because four facings of a mayonnaise share a single tag. Counting
facings invents missing tags on a shelf that is perfectly labelled. The rules
now group a row's facings into products - by identity when the facings were
recognised, by size and spacing otherwise - and count products.
2. A product's tag may sit anywhere along its run. Measured: a run of
ピュアセレクト facings was split by geometry because one facing was detected
narrower than its neighbours (54 px beside 150 px), and the fragment was then
reported as missing the tag that was sitting further along its own run. A
product now counts as missing only when no tag exists for its SKU anywhere in
the row, and a fragment far narrower than the row's typical product is not
judged at all.
3. A mismatch needs one trustworthy anchor. Measured noise: a wrong identity plus
a garbled tag read (name match 0.11, no JAN) produced a confident "tag says 90,
catalog says 188" that was really two bad reads disagreeing. Without the tag's
JAN or a name that resembles the product, that is now a hint, not a violation.
Measured on add/image6.jpg through the real still path: 0 false violations without
identities (was 1), and with identities the only finding left is a genuine
tag-versus-catalog price difference. Coverage hints now read "tags detected for 2
of 4 products in this row". 143 tests pass.
Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Web client: price-tag boxes in a distinct style (teal, chip with the parsed
price), an OCR section in the product card showing the tag's price, name,
discount and the reconciliation verdict with both values, and a compliance strip
under the stage. The photo stage now draws the image into the canvas and uses the
same containment as the media, so boxes cannot drift from the product (they did:
the canvas stretched to the stage while the photo was contained).
Server fixes the browser runs forced out:
- Photo mode reconciled before identities existed, so every tag read "tag only".
The tag bundle is cached with the still and classify re-reconciles against the
identities it just produced, returning them per detection.
- The still path only ever read the first four bands (plan hands out two per
call); it now drains every band, twice at different upscales so the vote has
independent reads.
- Voting is confidence-weighted and a dead heat stays unread; the plausible
shelf-price range is 10-9999, which stops a misread from becoming a ¥26,300
price. The compliance coverage bar moved to 0.7 after 0.5 produced a false
"group without price tag" on a shelf where every facing has one.
Measured on add/image6.jpg: 8 readable tags with names and prices, 942 ms for
the whole still, 7 real price mismatches, no false violations, and hints that
say plainly when a row could not be read.
Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
The engine owns the OCR backend, a shared OCR lock and a dedicated tag worker, so
a tag pass can never occupy a classification worker or slow a frame. A live
session plans rail bands on the frame loop (cheap), runs them on that worker, and
attaches whatever the cache already knows; a still runs one synchronous pass.
Tracks and detections now carry price_tag and reconciliation, and the summary
carries price_tags plus compliance. Config can turn tags off per session.
Compliance now fails closed on evidence quality. The first real run produced 106
"missing tag" violations on a shelf where only 8 tags were readable - our tag
*detection* was incomplete, not the shelf. A row is only judged when at least
half its facings carry tag evidence; otherwise it reports "tags detected for 14
of 91 facings in this row" as a hint. Missing-tag findings are one per row with a
count, not one per facing, and price_mismatch still reports every disagreement.
On add/image6.jpg the result is now 7 real price mismatches and no false
violations.
Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
reconcile() compares one accepted identity with its tag and the catalog entry and
publishes a state plus the individual signals (JAN exact, name by longest common
substring, price against either the sale or the regular price). It never changes
the product identity: a disagreement is a second opinion shown next to the first,
and only a checksummed barcode outranks the matcher.
evaluate_compliance() is the first rule family: missing_price_tag, the owner's
missing_tag_group (>= 3 consecutive facings without a tag), orphan_tag,
price_mismatch, plus an unreadable_tags hint. Every rule fails closed on evidence
quality - a row whose tags could not be read produces "move closer", never a
violation. Findings must appear in 3 of the last 5 frames before they publish, so
the UI never flickers.
Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
