Product recognition demo for supermarket shelf images

kiyo9w 601d72296c fix(catalog): correct sku_l10 to 400g and enroll its packshot ... Ajinomoto ピュアセレクト マヨネーズ has no 450g size: the official lineup is 250g/400g/600g/1kg, the shelf tag in add/image6.jpg reads 400g, and DECISION.md already recorded the mismatch. Both CSVs carried 450g, so every l10 answer shipped a wrong size. The packshot is the exact 400g front (JAN 4901001114030, 1000x1000) with its source URL and the 450g rejection recorded in data/packshots/research/sku_l10/manifest.json. Enrolling it moves the catalog ceiling from 69% to 87% of in-catalog facings answerable by image (l10 was 11 unenrolled facings). Measured on the corrected image6 labels: local lane 92% identity at 84% precision full, 85% at 91% live. Also points external-eval defaults at the repository-local data path; the licensed Wikimedia corpus remains uncommitted pending manifest review.		2026-09-29 02:45:21 +09:00
.github/workflows	chore: run the Python suite from the repository root	2026-09-28 17:26:58 +09:00
recognization	fix(catalog): correct sku_l10 to 400g and enroll its packshot	2026-09-29 02:45:21 +09:00
.gitignore	Initial commit for push folder	2026-09-18 09:13:53 +09:00