forked from vnguyen/product-recognition-demo

History

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
..
evaluations/2026-09-29-session	Enroll from a repo data dir; read packshots in every orientation	2026-09-29 02:33:47 +09:00
packshots	fix(catalog): correct sku_l10 to 400g and enroll its packshot	2026-09-29 02:45:21 +09:00
README.md	Enroll from a repo data dir; read packshots in every orientation	2026-09-29 02:33:47 +09:00

README.md

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