Product recognition demo for supermarket shelf images
a27841afa4
The engine owns the OCR backend, a shared OCR lock and a dedicated tag worker, so a tag pass can never occupy a classification worker or slow a frame. A live session plans rail bands on the frame loop (cheap), runs them on that worker, and attaches whatever the cache already knows; a still runs one synchronous pass. Tracks and detections now carry price_tag and reconciliation, and the summary carries price_tags plus compliance. Config can turn tags off per session. Compliance now fails closed on evidence quality. The first real run produced 106 "missing tag" violations on a shelf where only 8 tags were readable - our tag *detection* was incomplete, not the shelf. A row is only judged when at least half its facings carry tag evidence; otherwise it reports "tags detected for 14 of 91 facings in this row" as a hint. Missing-tag findings are one per row with a count, not one per facing, and price_mismatch still reports every disagreement. On add/image6.jpg the result is now 7 real price mismatches and no false violations. Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com> |
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