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.
Three defects, all found by scoring the live path against ground truth.
Inherited labels carried frame id 0. `_inherit_labels` set `label_box` but
never `label_frame_id`, so every inherited label was mapped back to the source
image with the first frame's offset. During a pan that puts the box a whole
pan-distance from the product it names, which is why most streamed tracks
matched no labelled facing. It now stamps the current frame and anchors to the
raw detection box rather than the smoothed track box, which lags a pan.
The reference lane upscaled views smaller than a pyramid level. `sku_l09.jpg`
is 407x305, so its 400 px level was a 305->400 blow-up: a blur with no
high-frequency detail to disagree with, which won 31 of 54 crops on the shelf
it was cut from. A view is now used only at the levels it actually has.
`score_stream.py` measured the wrong thing. It counted any facing touching the
window by one pixel (23 of 47 "in-catalog" facings were less than half
visible), scored a correct text-lane answer as a false accept because it
checked enrollment before correctness, and counted tracks rather than facings,
which reported 138% coverage of a 24-facing window. It now takes the union of
the window rects the client showed, keeps facings at least half inside, checks
correctness first, and reports facings named separately from labels correct.
Measured on add/image6.jpg, stock-lopia-clean, 20 s per run:
pan backend facings named precision
0 van 11/24 (46%) 52%
0 local 11/24 (46%) 100%
2 van 12/24 (50%) 45%
2 local 18/24 (75%) 100%
12 van 11/24 (46%) 28%
12 local 16/24 (67%) 83%
eval_identity on the same catalog is unchanged by the upscale fix (local 61%
end-to-end at 88% precision full, 59% at 95% live), and 1 of 602 distractor
crops from the 11 out-of-catalog shelf photos reaches 10 inliers, none reach 20.
