tao-train-depth-anything-v2

Depth Net Mono Monocular depth estimation using Metric Depth Anything v2 or Relative Depth Anything architectures. Predicts per-pixel depth from single RGB images. Pretrained checkpoint loading varies by model variant and use case — see the Pretrained checkpoint loading — use case matrix in references/parameters.md . The mono and stereo skills both invoke the unified TAO depth_net CLI inside the container; the mono/stereo family is selected via model.model_type (see references/parameters.md ). For TAO Deploy TensorRT actions ( gen_trt_engine , TensorRT evaluate , and TensorRT inference ), read references/tao-deploy-depth-anything-v2.md first. The deploy spec template lives in this skill's references/spec_template_deploy.yaml . PyT actions packaged by this model skill: train , evaluate , inference , export , and quantize . The PyT depth_net entrypoint does not accept a PyT-side gen_trt_engine action in the current TAO image. The gen_trt_engine action metadata must run with the TAO Deploy container, and the deploy workflow remains the deploy-specific entrypoint. 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. Use automl_policy: on by default and only expose on / off in new launch prompts. Treat phrases like "turn off AutoML", "disable AutoML", "no HPO", or "plain training" as automl_policy: off for this run only. When automl_policy: on , 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. Workflow Show more Installs 588 Repository nvidia/skills GitHub Stars 1.9K First Seen Jun 8, 2026 Security Audits Gen Agent Trust Hub Pass Socket Pass Snyk Warn