mirror of
https://github.com/ruvnet/RuView
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ruv
42b261f807
Edge optimization (ADR-152 optimize track): ONNX Runtime fp32 is the CPU latency win (3.2 ms/window, ~3.4x faster than torch, parity 2.4e-7); ORT dynamic int8 reaches 2.44 MB (paper's ~2.2 MB claim plausible only via conv-capable toolchains; -0.16pt PCK@20, +18% MPJPE, 2x slower); torch dynamic quant converts 0% of this conv-only model; fp16 halves storage free but is slower on CPU. Measurement (b) BLOCKED-ON-DATA: only 1,077 paired ESP32 windows exist (stop rule <2k). Forensic recheck of the surviving April holdout RETRACTS the ADR-079 '92.9% PCK@20' figure: constant-output model, absolute (not torso) threshold, 69 near-static frames — mean predictor scores 100% under that protocol; torso-PCK@20 is 19.1%. Corroborates PR #535. Stale citations removed from user-guide, readme-details, ADR-152 §2.1.3; no-citation rule extended to ADR-079 accuracy claims. Unblock: >=2k-window multi-pose paired session + torso-PCK re-baseline. Co-Authored-By: claude-flow <ruv@ruv.net>
20 lines
261 B
Plaintext
20 lines
261 B
Plaintext
# Upstream clone (WiFlow-STD, DY2434) -- never commit third-party code/weights
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upstream/
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# Local python env
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.venv/
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# Downloaded data / artifacts
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data/
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downloads/
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*.pth
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*.pt
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*.npy
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*.npz
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*.zip
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*.mat
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*.safetensors
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results/parity_fixture.json
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__pycache__/
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*.onnx
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