Three reference configs under examples/analysis/:
- minimal.yaml: full-trial DTW on raw coordinates, no alignment or
segmentation. Smallest working example; a starting template.
- paper_c_headline.yaml: the representative Paper C pipeline.
Bilateral gait-cycle segmentation, per-sequence Procrustes, and
joint-angle DTW on knee and hip flexion triplets.
- per_joint_debug.yaml: per-joint DTW breakdown for diagnosing
which joint drives an unexpected distance.
tests/integration/test_analyze_examples.py exercises each example
twice: load_config must accept the YAML (catches drift between the
examples and the current schema), and run_analysis must execute the
config end-to-end against synthetic predictions (catches drift
between the examples and the executor). The Paper C example has an
extra guard verifying the knee-flexion triplets haven't been edited
to something unexpected.
Also wires docs/api/pipeline.md into the mkdocs nav so mkdocstrings
surfaces the full schema and executor API.
Captures the MeTRAbs SHA-256 and filename plus tensorflow /
tensorflow-metal / numpy / neuropose / python versions, and reserves
slots for seed, deterministic, and analysis_config. Populated
automatically by Estimator.process_video when the model was loaded via
load_model; propagates into JobResults and BenchmarkResult via the
existing output path. None on the injected-model test path where no
SHA is known.
_model.load_metrabs_model now returns a LoadedModel dataclass so the
estimator can bundle the TF handle with the pinned SHA without
re-hashing the tarball on every daemon startup. All test fakes and
the integration smoke tests updated to unwrap .model.
Bumps the optional schema_version field on VideoPredictions and
BenchmarkResult to default=CURRENT_VERSION so fresh writes stamp the
latest version; legacy payloads without it are migrated on load via
the chain registered in the previous commit.
Levi Neuwirth