/v1/recognize: 111 detections, 53 named in 2.38 s, no view-suffixed ids, no missing product info. l06 now names all 4 of its facings - it was 1/4 at live resolution before the current package was enrolled, which is the F-12 fix visible in the product. /v1/stream, 20 s pan: 82 tracks labelled, 0 label changes, 0 unexplained. The label-memory fixes hold under a pan. |
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|---|---|---|
| .. | ||
| evaluations/2026-09-29-session | ||
| external-eval | ||
| packshots | ||
| 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