tngo/product-recognition-demo
1
0
Fork 0
forked from vnguyen/product-recognition-demo
Code Pull requests Activity

Make the catalog hash honest, share the text helpers, drop the duplicate labels

Browse source 
`catalog_hash` hashed the CSV and the view *names*, so replacing
`sku_l09.jpg` with a different product's packshot left the hash unchanged and
a report could claim the same catalog while every l09 decision in it had
moved. It hashes each view's bytes now.

`identity_lanes` carried its own `normalize_text` and `bigrams`, near-copies
of the ones in `rebuild_catalog` that had already drifted (the lane's table
folded ユ to itself, the catalog's did not). The lane imports the catalog's
now, so one read scores the same either way.

`evidence/image6_v2.json` was byte-identical to `eval/labels/image6.json`; the
evidence scripts and the decision document point at the canonical file and the
copy is gone. `score_crop`'s docstring now states the contract its callers
already depend on: the dict's insertion order is the lane's ranking, and
re-sorting by value names a different SKU than the lane chose.

Tests: the lane is shared by the classify pool, so a concurrent-ranking test
pins that one BFMatcher does not cross crops under eight threads.
This commit is contained in:
tngo 2026-09-29 00:48:03 +09:00
parent fc49ba60e6
commit b6c87c45ea
36 changed files with 89 additions and 1524 deletions
Download patch file Download diff file Expand all files Collapse all files

8
recognization/docs/research/2026-09-28-recognition-architecture/evidence/README.md
View file

@ -3,16 +3,16 @@
Read-only against product code: every script imports from `code/` and writes
only into this folder. Run from `recognization/` with `.venv/bin/python`.
`image6_v2.json` is the corrected image6 label set (26 of 111 v1 labels
`eval/labels/image6.json` is the corrected image6 label set (26 of 111 v1 labels
changed; every row carries `v1_label`, `source`, and a `note` where changed).
`image6-v1-labels-overlay.jpg` shows the v1 labels on the shelf; green = catalog
label, red = unknown. `sheet.py` regenerates per-SKU contact sheets.
| Step | Command (prefix `E=docs/research/2026-09-28-recognition-architecture/evidence`) | Produces |
|---|---|---|
| Original matcher, both catalogs, full/live/live-with-unscaled-boxes | `.venv/bin/python $E/diag.py --stock stock-lopia-clean --labels $E/image6_v2.json [--live] [--bug] --out $E/run_stock-lopia-clean_<full\|live\|livebug>.pkl` (repeat with `--stock stock-lopia`) | `run_*.pkl` |
| Original matcher, both catalogs, full/live/live-with-unscaled-boxes | `.venv/bin/python $E/diag.py --stock stock-lopia-clean --labels $E/../../../eval/labels/image6.json [--live] [--bug] --out $E/run_stock-lopia-clean_<full\|live\|livebug>.pkl` (repeat with `--stock stock-lopia`) | `run_*.pkl` |
| Score them under v1 or v2 labels | `.venv/bin/python $E/analyze.py <labels.json> $E/run_*.pkl` | identity top-1, argmax, current gate |
| Matcher variants | `.venv/bin/python $E/variants.py --stock stock-lopia-clean --labels $E/image6_v2.json [--live] --scales 200,400 --root --geom affine --out $E/v_ms_root_aff_<full\|live>.pkl` (also `--tmpl-h 250/400`, no flags = raw) | `v_*.pkl` |
| Matcher variants | `.venv/bin/python $E/variants.py --stock stock-lopia-clean --labels $E/../../../eval/labels/image6.json [--live] --scales 200,400 --root --geom affine --out $E/v_ms_root_aff_<full\|live>.pkl` (also `--tmpl-h 250/400`, no flags = raw) | `v_*.pkl` |
| Variant ranking + open-set frontier | `.venv/bin/python $E/an2.py $E $(basename -a $E/v_*.pkl)` (`LABELS=image6_v2_lfo.json` for the leave-facing-out runs) | correct at 100/95/90 % precision |
| Leave-facing-out catalog | `.venv/bin/python $E/lfo_setup.py`, then `variants.py --stock $E/cat_<pack\|full> --labels $E/image6_v2_lfo.json --scales 200,400 --root --geom affine [--live] --out $E/lfo_cat_<pack\|full>_<full\|live>.pkl` | `lfo_*.pkl` |
| Unrelated-shelf distractors | `YOLO_OFFLINE=1 .venv/bin/python $E/distract.py stock-lopia-clean $E/cat_full` | `distract.pkl` |
@ -44,7 +44,7 @@ with no arguments raise `IndexError`; neither validates its own usage.
v1 labels are no longer a file on disk — `eval/labels/image6.json` is the v2
set. To score a run under v1, rebuild it from the `v1_label` field:
.venv/bin/python -c "import json;d=json.load(open('$E/image6_v2.json'));\
.venv/bin/python -c "import json;d=json.load(open('$E/../../../eval/labels/image6.json'));\
[f.update(label=f.pop('v1_label')) for f in d['facings']];\
json.dump(d,open('/tmp/image6_v1.json','w'),ensure_ascii=False)"