Depth Net Fast Stereo

Real-time stereo depth estimation using FastFoundationStereo (FFS) — the bp2 commercial distilled variant of FoundationStereo. Predicts disparity maps from rectified stereo image pairs with per-layer pruned widths for real-time inference.

The mono / stereo / fast-stereo skills share the unified TAO depth_net CLI; FFS is selected via model.model_type: FastFoundationStereo. FFS differs from FoundationStereo only in pruned per-layer widths and a serialized forward path; everything else (entrypoint, action verbs, dataset classes, deploy chain) is identical to depth-net-stereo.

For TAO Deploy TensorRT actions (gen_trt_engine, TensorRT evaluate, TensorRT inference), read references/tao-deploy-fast-foundation-stereo.md first. The deploy spec template lives at references/spec_template_deploy.yaml.

Train Action Policy

This model is AutoML-enabled at the model layer. Before handling any train-stage request, read references/skill_info.yaml and resolve the run override from either an explicit automl_policy value or the user's workflow request. Treat phrases like "turn off AutoML", "disable AutoML", "no HPO", or "plain training" as automl_policy: off for this run only; otherwise default to auto. When automl_policy: auto, automl_enabled: true, and both schemas/train.schema.json and references/spec_template_train.yaml are packaged, route the train action through tao-skill-bank:tao-run-automl by default with this model's skill_dir. Preserve workflow/application overrides for datasets, specs, output directories, GPU/platform settings, parent checkpoints, and automl_policy. Use direct model training only when automl_policy: off or the packaged train schema/template is missing; in the missing-schema case, report that AutoML is enabled but not runnable for this model until schemas are generated.

Non-train actions such as evaluate, inference, export, and deploy flows stay in this model skill. The per-run automl_policy override does not change model metadata.

Two Use Cases

FFS ships with a pre-trained bp2 commercial checkpoint (model_best_bp2_serialize.pth).