RuView Model Training

RuView trains several kinds of model. Pick the track that matches the goal; all of them run on a laptop, with an optional GPU path.

Track A — Camera-free pose (WiFlow), no cameras, no labels

Trains 17-keypoint pose from 10 sensor signals. Fast, fully unsupervised, modest accuracy.

cd v2
# Pretrain on raw CSI (contrastive)
cargo run -p wifi-densepose-sensing-server -- --pretrain --dataset data/csi/ --pretrain-epochs 50
# Train pose head, save an RVF artifact
cargo run -p wifi-densepose-sensing-server -- --train --dataset data/mmfi/ --epochs 100 --save-rvf model.rvf

~84 s on an M4 Pro. Benchmarks: node scripts/benchmark-wiflow.js, eval: node scripts/eval-wiflow.js.

Track B — Camera-supervised pose (ADR-079) → 92.9% PCK@20