Product recognition demo for supermarket shelf images
7736465bee
The audit's own numbers were right; several claims built on them were not, and the advisors found each one: - 'wins both axes at both resolutions' - false at live, where the lane trades 59% coverage for 93% precision against Van's 66% at 39%. Stated as the trade it is. - G1's bootstrap now exists: the local lane's correct set is a strict superset of Van's on the stream, so the 95% lower bound is a hard +0.0 pp - a floor of that pairing, not a margin. tracks_final.json is level with Van and does not clear it. - The far-unknown rate is 0.066% on 4580 crops at the shipped configuration, not 0.30% on 2650 at the old one. - The E-3 ablation compared text-presence *and* a different argmax; both arms now go through the same DecisionPolicy ordering. Text adds 9-10 pp of coverage at full resolution while raising precision. - The sweep table swept one axis while pinning the other; replaced with the joint sweep. - The two Re-measured tables are dated snapshots, labeled as such. |
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| recognization | ||
| .gitignore | ||