product-recognition-demo/recognization/stock-lopia-clean
kiyo9w 6a45fb990d fix(catalog): enroll the current l06 package, closing F-12
The enrolled sku_l06.jpg showed the superseded 内臓脂肪ケア wrapper. The shelf
and the current retail package both read 内臓脂肪を減らす キューピーフィッテ
210g, so the reference image was of a design the store no longer sells - the
catalog was pointing at the wrong package.

F-12 was recorded as blocked on a capture because Kewpie's own site serves the
old design for that JAN. An independent retailer listing carries the current
one, and it matches the shelf facings exactly (verified by eye against a crop
of add/image6.jpg before enrolling).

Measured effect on the corrected labels: live decision 60% -> 64%, end-to-end
59% -> 62%, full-resolution decision 81% -> 83%. Suite still 307.

Also lands 12 more external-proxy images (six SKUs, two source domains each)
and their scored result. Across both external sets - 20 images - the lane is
13 correct, 7 abstain, 0 false accepts.
2026-09-29 03:22:03 +09:00
..
references/rejected
README.md docs: match the false-accept record to the evaluator's own columns 2026-09-28 22:36:27 +09:00
sku_l01.jpg
sku_l02.jpg
sku_l03.jpg
sku_l05.jpg
sku_l06.jpg fix(catalog): enroll the current l06 package, closing F-12 2026-09-29 03:22:03 +09:00
sku_l09.jpg Enroll from a repo data dir; read packshots in every orientation 2026-09-29 02:33:47 +09:00
sku_l10.jpg fix(catalog): commit the enrolled sku_l10 view 2026-09-29 02:49:10 +09:00
sku_l11.jpg
stock.csv fix(catalog): sku_l12 is a vegetable tare, not 焼肉のたれ 中辛 2026-09-29 03:07:39 +09:00

LOPIA clean catalog

Official manufacturer pack shots, one front view per SKU. This replaces the views in ../stock-lopia/, which were 71-119 px crops cut from the test shelf add/image6.jpg itself: one 18 px sliver, duplicate crops, a wrong product on sku_l09, and five SKUs with no view at all. Enrolling from the test shelf is why every dark package collapsed onto one SKU and why the identity head was trained on its own exam.

Rebuild or extend with:

python code/rebuild_catalog.py --source stock-lopia-clean --output stock-lopia-clean \
    --replace --min-views 1 --csv stock-lopia/stock.csv

--min-views 1 because official pages publish a single front view per JAN. The default floor of 2 exists to catch accidental single-view enrollment from shelf crops, where several views are available.

Provenance

SKU Product Source Image
sku_l01 キユーピー エッグケア 305g kewpie.co.jp 4901577090301L.jpg
sku_l02 キユーピー 血圧ケア アマニ油マヨネーズ 200g kewpie.co.jp 4901577060052L.jpg
sku_l03 キユーピー からしマヨネーズ 200g kewpie.co.jp 4901577338779L.jpg
sku_l05 キユーピー ゼロ ノンコレステロール 310g kewpie.co.jp 4901577092381L.jpg
sku_l06 キユーピー 内臓脂肪ケア フィッテ 210g kewpie.co.jp (discontinued 2026秋) 4901577083600L.jpg
sku_l09 ピュアセレクト コクうま カロリーカット65% 360g ajinomoto.co.jp A140600321
sku_l11 キユーピー ハーフ 400g kewpie.co.jp 4901577031083L.jpg

Kewpie images follow https://img.kewpie.co.jp/products_src/g3/imgs/<JAN13>L.jpg; Ajinomoto images follow https://www.ajinomoto.co.jp/products/Image.aspx?PicType=0&PIMNO=<PIMNO>.

Known gaps

Five SKUs in ../stock-lopia/stock.csv have no official pack shot here, so no image lane can match them. They stay in stock.csv as text-only rows: the text lane builds a signature from the printed name, which is how it can name or veto a near-unknown the matcher cannot see. They are the current image-coverage ceiling, not a recognition failure:

SKU Catalog name Why it is missing
sku_l04 やまや めんたいマヨネーズタイプ 200g Yamaya's current lineup has no 200 g mentaiko mayo
sku_l07 丸和油脂 ラッキーマヨネーズ 200g Maruwa's current catalog has no 200 g Lucky Mayonnaise
sku_l08 スパイシーストーム ペリペリミックス 30g No official 30 g Peri-Peri Mix found
sku_l10 ピュアセレクト マヨネーズ 450g Ajinomoto's current lineup is 400/250/600 g/1 kg; no 450 g
sku_l12 焼肉のたれ 中辛 Brand not recorded in the catalog; ambiguous

The catalog names for these five disagree with the manufacturers' current lineups, so the shelf tags and the CSV need reconciling before enrollment.

Keep the text-only rows when rebuilding: the CSV carry-over must preserve every source row, not just the SKUs with a kept view. Dropping these five costs the text lane the signatures that cover them.

sku_l09.jpg is enrolled but only 305 px tall, below the 800 px source floor the enrollment protocol wants (§8 of the architecture decision). Its matcher scores dwarf the other references (85-129 inliers against 10-40), so it wins facings it should not; re-source it before trusting l09 precision. Measured on the corrected image6 labels, l09 is the largest single-SKU share of accepts at both resolutions: 18 of 48 accepts (37.5%) at full, 11 of 38 (28.9%) at live, against a true share of 13 of 61 facings (21.3%). That is a hubness ratio of 1.76 and 1.36 against the completion gate's limit of 2.0, so G7 passes; the stricter internal 30% share heuristic is what raises the alarm at full resolution. Re-sourcing the reference is the fix, not a threshold change.

Rejected

references/rejected/kewpie-mayonnaise-450g.jpg is Kewpie Mayonnaise 450g (JAN 4901577042072). It was briefly filed as sku_l09 and then as sku_l10 because the catalog's names pointed there, but it is neither product: l09 is Ajinomoto Pure Select コクうま カロリーカット 65% 360g and l10 is Pure Select マヨネーズ 450g. It is kept as provenance for that mix-up and is never enrolled.