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fix(cog-pose-estimation): emit frames under default config (ADR-159 A1)

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pose_v1 has no confidence head, so infer() emits a constant 0.185 per
frame. The config default_min_confidence was 0.3 and the runtime gates
on confidence >= min_confidence, so a default install silently emitted
ZERO pose.frame events while health reported healthy.

- Add inference::MODEL_TYPICAL_CONFIDENCE (0.185, the validation PCK@50)
  as the single published per-frame confidence.
- Pin default_min_confidence() to MODEL_TYPICAL_CONFIDENCE so a default
  install clears its own gate and emits.
- Warn at run.started when min_confidence exceeds the model typical
  confidence (disclosed, not silent); document the trade-off in the
  config field, the JSON schema, and inference.rs.

Failing-on-old test: default_config_emits_frames_with_real_model
(with old 0.3 it panics: "default install would emit zero pose.frame
events").

Co-Authored-By: claude-flow <ruv@ruv.net>
This commit is contained in:
ruv
2026-06-11 23:10:00 -04:00
parent 2e4461d64d
commit 98bf8c4726
5 changed files with 94 additions and 7 deletions
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v2/crates/cog-pose-estimation/src/inference.rs
+17 -4
View File
@@ -27,6 +27,16 @@ pub const INPUT_SUBCARRIERS: usize = 56;
pub const INPUT_TIMESTEPS: usize = 20;
pub const OUTPUT_KEYPOINTS: usize = 17;
/// The model's typical self-reported confidence. `pose_v1` has **no confidence
/// head** (the head emits 34 keypoint coordinates only), so per-frame confidence
/// is not available from the network. This is the validation-set PCK@50 (18.5%)
/// the training run reported, used as the published per-frame confidence floor.
///
/// Surfaced as a public constant so the runtime can warn when a configured
/// `min_confidence` threshold exceeds it — otherwise a default install would
/// silently emit zero `pose.frame` events while health reports healthy.
pub const MODEL_TYPICAL_CONFIDENCE: f32 = 0.185;
#[derive(Debug, Clone)]
pub struct CsiWindow {
pub data: Vec<f32>, // length INPUT_SUBCARRIERS * INPUT_TIMESTEPS
@@ -283,12 +293,15 @@ impl InferenceEngine {
let out = model.net.forward(&t)?; // [1, 34]
let flat: Vec<f32> = out.flatten_all()?.to_vec1()?;
// Confidence from pose_v1 is a published constant rather than per-frame —
// the trained model didn't emit a confidence head. Use the validation-set
// PCK@50 (18.5%) as the published self-reported confidence so downstream
// consumers can gate display decisions on it.
// the trained model has no confidence head (the head emits 34 keypoint
// coordinates only), so a real per-frame value is genuinely unavailable.
// We surface the validation-set PCK@50 (`MODEL_TYPICAL_CONFIDENCE`) as the
// honest self-reported confidence. The runtime's `min_confidence` default
// is pinned at or below this so a default install actually emits frames
// (and warns if an operator raises the threshold above the model's reach).
Ok(PoseOutput {
keypoints: flat,
confidence: 0.185,
confidence: MODEL_TYPICAL_CONFIDENCE,
})
}
}