The gates were tuned on image6 alone, where every crop is a facing of a product
the shelf actually holds. Wikimedia supermarket photos of milk, soy and snack
shelves share nothing with the LOPIA catalog, so every accept there is a false
accept by construction - and at the old lines there were 83 of them.
Text lane: TEXT_MIN_SHARED 2 -> 4. The vocabulary filter drops bigrams no name
contains, so a short garbage read can end up with a perfect ratio on two
coincidental pairs. 20 of 26 text-lane answers on those shelves rested on
exactly two: '避くて おいしい' named sku_l12 through おい/いし.
Local lane: LOCAL_ACCEPT 2.0 -> 4.0. The residual accepts were geometric
matches with no text overlap at all, scoring 2.26-4.81.
Measured, 2297 distractor crops and 109 image6 facings:
accept floor image6 shown/correct precision false accepts
2.0 2 54 / 49 90.7% 83 (3.61%)
2.0 4 52 / 48 92.3% 30 (1.31%)
4.0 4 44 / 42 95.5% 8 (0.35%)
5.0 6 36 / 36 100.0% 0 (0.00%)
4.0/4 is the only region passing both G2 (>=95% precision) and G3 (<=1%
far-unknown) with coverage left. On the shipped evaluator: 66% end-to-end at
95% precision, 2 false accepts, against 77%/91%/5 before.
The two tests that pinned the old floors now pin the new ones, with the reads
that separate them.
