reflow_ml_ops

ML inference and decode actors for Reflow — runs model manifests through the LiteRT boundary, decodes tensors into typed detection / landmark / ROI packets.

Most users should depend on reflow_rt with the ml feature, which re-exports this crate as reflow_rt::ml_ops. Direct use is appropriate when assembling ML pipelines without the full bundled runtime.

What it provides

• Inference actor driven by model manifests from reflow_asset_registry.
• Detection, classification, and landmark decode actors producing reflow_media_types packets.
• Swappable backend via reflow_litert — mock by default, real LiteRT with external-litert.

Typical pipeline

preprocessed_tensor -> tpl_ml_inference -> decode -> taskpack -> output

Model behavior comes from manifests and per-node configuration. Taskpacks are reusable graph exports, not privileged runtime code.

License

MIT OR Apache-2.0.