Every threshold was fitted on image6, where each crop is a facing of a product
the shelf holds, so the set could not price a false accept. Measured on 4580
crops from 64 unrelated Wikimedia shelf photos at the shipped configuration:
LOCAL_ACCEPT 2.0 -> 4.0 false accepts 60 (1.31%) -> 3 (0.07%)
TEXT_MIN_SHARED 2 -> 4 the two-bigram reads that named sku_l12 via おい/いし
On image6 that is 44 shown / 42 correct at full resolution - 95.5% precision,
65.6% coverage - the highest-coverage cell of the joint sweep that passes both
G2 (>= 95%) and G3 (<= 1%). At live resolution 56% end-to-end at 97%.
The text lane's evidence floor gates its answer only: zeroing the row's score
would reorder the ranking and make the margin gate compare a different pair
than the one it was measured on.
code/sweep_accept_lines.py sweeps both axes jointly through the shipped
DecisionPolicy; the earlier table swept one axis while pinning the other, so
its baseline rows were not the old line.
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.
