Product recognition demo for supermarket shelf images
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kiyo9w 22db40eb93 fix(labels): the tare facings are sku_l12, not unknown
Facings #46-48 carried the note 'possibly what stock.csv calls l12'. The l12
reconciliation settled it: the shelf tag under them reads ユーラス 野菜を
おいしく食べる旨タレ (380g) at ¥299, the price the l12 row carries, and the row
has been renamed to match. Leaving them unknown understated the catalog and
overstated precision.

Counts move from 61 in-catalog / 48 unknown to 64 / 45. The enrollment ceiling
falls 87% -> 83% because l12's three facings now count as in-catalog with no
enrolled view - an honest catalog gap, not a recognition regression.

Also records the Tier-3 source search: two reusable clips (CC BY 3.0 Wikimedia
1920x1080 supermarket pan; CC BY YouTube 360p mayonnaise-bay pan), 11 rejected
candidates, and the LOPIA walk that carries the standard YouTube licence and
was therefore not downloaded. Both clips are labelled tier3_proxy_candidate,
never Tier 3: that still needs the operator's own recorded walks.
2026-09-29 03:09:15 +09:00
.github/workflows chore: run the Python suite from the repository root 2026-09-28 17:26:58 +09:00
recognization fix(labels): the tare facings are sku_l12, not unknown 2026-09-29 03:09:15 +09:00
.gitignore Initial commit for push folder 2026-09-18 09:13:53 +09:00