Suriyakumarvijayanayagam
dad04e8cda
Five components that ship as one product:
- behavision/ the recognition engine. RTSP ingest, YuNet detection, IoU
tracking, ArcFace embeddings, a FAISS/SQLite gallery, and a
FastAPI dashboard. Identity is decided once per TRACK from an
average of at least three embeddings, never per frame.
- agent/ the Go edge agent: supervises the engine, holds a durable
spool, and drains it to MQTT. Nothing is acked before the
broker confirms.
- desktop/ the shop PC application (Wails + React + tray).
- server/ the cloud API, MQTT consumer, reports and assistant.
- web/ platform.loyaly.ai, the head-office app, embedded in the
server binary.
The gallery stores 512-float embeddings and timestamps - no images unless
`app.store_faces` is switched on. Those embeddings are biometric personal
data under GDPR and India's DPDP: template inversion reconstructs a
recognisable face from an ArcFace vector, so data/behavision.db is treated
as a biometric database and DELETE /api/visitors/{id} is a real erasure.
CLAUDE.md carries the reasoning behind every non-obvious decision here,
including the ones that were measured and the ones that were wrong first.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HViLj9gYNRtSr7YVZmW5sn
18 lines
505 B
JSON
18 lines
505 B
JSON
{
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"$schema": "https://wails.io/schemas/config.v2.json",
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"name": "Behavision",
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"outputfilename": "Behavision",
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"frontend:install": "npm install",
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"frontend:build": "npm run build",
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"frontend:dev:watcher": "npm run dev",
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"frontend:dev:serverUrl": "auto",
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"author": { "name": "Loyaly" },
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"info": {
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"companyName": "Loyaly",
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"productName": "Behavision",
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"productVersion": "0.1.0",
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"copyright": "© Loyaly",
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"comments": "Footfall and customer recognition for retail"
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}
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}
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