product-recognition-demo/recognization/data
kiyo9w 3fa82eec37
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docs(packshots): record why sku_l08 could not be sourced
The DECISION says l08 has no retailer listing and that the only corroborated
ペリペリミックス is a different brand at 50g. The Rakuten search that shows this
was sitting unreferenced in the repo root as rk2.html; it is now the evidence
file behind the claim, with a manifest in the same shape as l04/l07/l10.

The search returns 141 results and none is the product: every ペリペリ hit is
SPICEDREAM at 50g or 195ml. l08 is the one catalog row with no corroborating
source, so a wrong label there would not be detectable from the catalog alone.
2026-09-29 04:34:58 +09:00
..
evaluations/2026-09-29-session test(server): final smoke with the calibrated gates live 2026-09-29 04:32:38 +09:00
external-eval test(tier3): run the production pipeline over both reusable clips 2026-09-29 03:39:33 +09:00
external-shelves chore(eval): reconcile the distractor sets and refresh the sweep numbers 2026-09-29 04:17:54 +09:00
packshots docs(packshots): record why sku_l08 could not be sourced 2026-09-29 04:34:58 +09:00
README.md Enroll from a repo data dir; read packshots in every orientation 2026-09-29 02:33:47 +09:00

Recognition data

Everything the identity work needs to be reproducible: sourced packshots, evaluation runs, and the audits that produced them. Nothing here is ephemeral; a run that matters is written here, not to a temp directory.

packshots/source/

Front packshots as downloaded, before enrollment. ATTRIBUTION.json records the source URL, the product as printed, and the manufacturer for each. ocr-reads.json holds the OCR text each image produced, so a name/OCR refusal can be re-checked without re-running Vision.

rebuild_catalog.py reads this directory and writes a catalog:

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

evaluations/

One directory per session. Each holds the raw artifacts a claim was computed from, so a number in DECISION.md can be traced back to the run that produced it.

Directory Contents
stream/ WebSocket track dumps from stream_client.py, scored by score_stream.py.
still/ /v1/recognize responses for the still-image path.
catalog-audit/ rebuild_catalog.py --json reports.
scratch/ Intermediate images (rotations, crops) kept because they document a finding.

Scoring a stream dump:

.venv/bin/python code/score_stream.py data/evaluations/<session>/stream/<file>.json \
    --labels eval/labels/image6.json --stock-dir stock-lopia-clean