The live session scored crops with the matcher regardless of the configured identity backend, so a live scan used the old mechanism while the still path used the enrolled gallery - measured, the matcher accepts look-alikes and cannot say "unknown", which is exactly what a real shelf needs it to do. score_crop now routes to the gallery, and the decision uses a similarity scale (accept at 0.60 with a 0.04 margin) rather than inlier-count thresholds that mean nothing on a cosine. The synthetic walk is gone: demo.py, demo_replay.py, the /v1/demo endpoints and the walk benchmark are deleted, and the app's frame source is the camera on a device (the single-image replay stays for the simulator, which has no camera). stock-demo merges both demo shelves (27 products, 62 views, trained head) so one server recognises either image, and run-demo-server.sh starts it bound to 0.0.0.0 and prints the exact URL to put in Config.xcconfig. Verified over the LAN with 1280x960 frames: 40 frames in 5.3s, 9 products recognised on demo image 1. Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
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4.7 KiB
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