ruv
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cd1c391afc
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feat(worldmodel): ADR-147 Phase 3+5 — RuViewOccDataset domain adapter + retraining pipeline
Phase 3 — scripts/ruview_occ_dataset.py:
- RuViewOccDataset: WorldGraph JSON snapshots → OccWorld (F,H,W,D) tensors
- Indoor class remapping: person→7, floor→9, wall→11, furniture→16, free→17
- Zero ego-poses (fixed indoor sensor, no ego-motion)
- record_snapshot() helper for training data accumulation
- Validated: 5 windows, (16,200,200,16) tensor, person+floor voxels confirmed
Phase 5 — scripts/occworld_retrain.py:
- record: stream WorldGraph snapshots from sensing server REST API
- vqvae: fine-tune VQVAE tokenizer on RuView occupancy (200 epochs, AdamW)
- transformer: fine-tune autoregressive transformer with frozen VQVAE
wifi-densepose-worldmodel v0.3.0 published to crates.io
Co-Authored-By: claude-flow <ruv@ruv.net>
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2026-05-29 18:46:56 -04:00 |