physical-ai-video-data-augmentation

Orchestrate NVIDIA OSmo VDA workflows with preflight checks and cache management.

Updated Apr 16, 2026
One-click install
npx skills add https://github.com/sayalinvidia/sayali-skills-test --skill physical-ai-video-data-augmentation
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: physical-ai-video-data-augmentation
Source: https://github.com/sayalinvidia/sayali-skills-test/tree/main/skills/physical-ai-video-data-augmentation
Command: npx skills add https://github.com/sayalinvidia/sayali-skills-test --skill physical-ai-video-data-augmentation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pyyaml, omegaconf, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill coordinates the end-to-end orchestration of NVIDIA's Video Data Augmentation (VDA) workflows on OSMO, enabling safe preflight checks, dataset and model cache setup, and deterministic submit-time interpolation across flows.

Core Features & Use Cases

  • Orchestrates setup, augmentation, auto-labeling, and end-to-end pipelines with a single submission surface.
  • Manages prerequisites: credential wiring, cache prep, and pre-submit guard checks to reduce run-time errors.
  • Provides post-run artifact staging, monitoring, and evidence collection to assess augmentation impact.

Quick Start

Provide dataset, run_id, storage_url, and gpu_platform, then submit a VDA workflow using a single --set-string payload.

Frequently Asked Questions about physical-ai-video-data-augmentation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I orchestrate video data augmentation workflows on NVIDIA OSMO?

Orchestrating VDA workflows on NVIDIA OSMO involves coordinating preflight checks, dataset cache setup, and submit-time interpolation using a single --set-string payload submission contract to ensure safe end-to-end runs.

What is submit-time interpolation in VDA pipeline orchestration?

Submit-time interpolation in VDA orchestration is the deterministic process of resolving configuration variables at run submission, enforcing a single --set-string payload contract to safely interpolate parameters across auto-labeling, augmentation, and E2E flows.

Can I use s3 or azure backends for dataset storage with OSMO VDA workflows?

Yes, OSMO VDA workflows support dataset storage across s3, azure, and gs backends, validating storage URLs and handling credentials to safely manage datasets stored in various cloud storage_url locations.

How do I run preflight checks before submitting an augmentation pipeline?

Preflight checks are executed during orchestration setup to validate dataset URLs, verify credential wiring, and prepare model caches, reducing run-time errors before you submit the VDA workflow payload.

What are the prerequisites for running end-to-end VDA workflows?

Prerequisites for running VDA workflows include providing the dataset, run_id, storage_url, and gpu_platform parameters, along with proper credential wiring and cache preparation managed through pre-submit guard checks.

Does OSMO VDA orchestration support auto-labeling flows?

Yes, OSMO VDA orchestration supports auto-labeling flows alongside augmentation and E2E pipelines, coordinating them through a single submission surface with strict guardrails and post-run artifact staging.