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ruv
7c13ec6a00
Criterion benches over InferenceEngine::infer for cog-person-count and cog-pose-estimation, on Device::Cpu with the real shipped safetensors weights (asserts candle backend so the stub is never silently benched), over a fixed CSI window after a warm-up forward. HOST-MEASURED steady-state medians (idle box): ~305us each. This is the recurring per-frame cost and is explicitly NOT the pose manifest's cold_start_ms_avg=5.4 (a different measurement, weight-load included, taken on ruvultra/RTX 5080) -- the two are labelled and not conflated. Closes the ADR-159/160 deferred cog inference-latency item. No production- code behavior change. Co-Authored-By: claude-flow <ruv@ruv.net>
48 lines
1.5 KiB
TOML
48 lines
1.5 KiB
TOML
[package]
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name = "cog-person-count"
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version.workspace = true
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edition.workspace = true
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authors.workspace = true
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license.workspace = true
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repository.workspace = true
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description = "Cognitum Cog: WiFi-CSI presence detector + (data-gated) person count (ADR-103). Candle-based head trained on classes 0/1 (presence); the 8-class count head ships but counts above the trained range are flagged low_confidence. Stoer-Wagner multi-node fusion."
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[[bin]]
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name = "cog-person-count"
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path = "src/main.rs"
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[lib]
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name = "cog_person_count"
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path = "src/lib.rs"
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[dependencies]
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clap = { version = "4", features = ["derive"] }
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serde = { version = "1", features = ["derive"] }
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serde_json = "1"
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thiserror = "1"
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tracing = "0.1"
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tracing-subscriber = { version = "0.3", features = ["env-filter"] }
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tokio = { version = "1", features = ["rt-multi-thread", "macros", "signal", "time"] }
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sha2 = "0.10"
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ureq = { version = "2", default-features = false, features = ["tls"] }
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# Same Candle stack the pose cog uses — CPU by default, `cuda` feature
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# opt-in for hosts with a CUDA GPU.
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candle-core = { version = "0.9", default-features = false }
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candle-nn = { version = "0.9", default-features = false }
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safetensors = "0.4"
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[dev-dependencies]
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tempfile = "3"
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approx = "0.5"
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# ADR-163: steady-state infer latency bench (real count_v1 weights, Device::Cpu).
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criterion = { version = "0.5", features = ["html_reports"] }
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[[bench]]
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name = "infer_bench"
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harness = false
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[features]
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default = []
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cuda = ["candle-core/cuda", "candle-nn/cuda"]
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hailo = []
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