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/physical-ai-video-data-augmentation

@0482ebc
by NVIDIA Corporationnvidia/skills3.5k stars
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Use when running video data augmentation and auto-labeling workflows on OSMO: flow selection, preflight, submit-time interpolation, monitoring, and output retrieval. Trigger keywords: video data augmentation, data enrichment, auto labeling, VDA demo, OSMO workflow, pseudo labeling.

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Use this Skill: https://skilld.dev/gh/nvidia/skills/physical-ai-video-data-augmentation

This session only. Nothing lands on disk.

referencesflowsaugmentation_and_al.md

≈638 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Augmentation + Auto-Labeling

Table of Contents

Runs augmentation on source video(s) and then auto-labels augmented outputs. Original-video auto-labeling is not part of this flow.

When to use

  • User wants synthetic variants plus labels for those variants.
  • User does not need labels on source/original video path in the same run.
  • User wants a smaller graph than e2e while keeping augmentation + AL.

Graph

setup_group
  setup
    -> stages scripts + cookbook configs + generated per-video configs + .env
      ▼
augmentation_group
  cosmos_worker_0
    -> augmented outputs
      ▼
auto_labeling_augmented_group
  pl_augmented_worker_0
    -> pseudo-labeled augmented outputs

Inputs

Input Source Required by
Source video <storage_url>/datasets/<dataset>/<video>.mp4 setup, cosmos_worker_0
Cosmos cache <storage_url>/data/models/cosmos_transfer cosmos_worker_0
Auto-labeling cache <storage_url>/data/models/auto_labeling pl_augmented_worker_0
VLM endpoint default in-cluster NIM or explicit override augmentation + AL workers
LLM endpoint default in-cluster NIM or explicit override augmentation + AL workers

Submit

Use the shared submit command and the common optional-overrides block in the SKILL.md "Submit (all flows)" section, with workflow YAML assets/configs/osmo/augmentation_and_al.yaml. This flow runs augmentation first, then auto-labels the augmented outputs, so the full canonical single-flag submit shape applies (including both cache URL values).

Output layout

<storage_url>/datasets/<dataset>-outputs/<run_id>/
├─ setup_b0/
└─ outputs/
   ├─ augmented/<video>_aug0/
   └─ pseudo_labeled_augmented/<video>_aug0/

Troubleshooting

  • Completion evidence requirement: include a side-by-side input vs augmented video artifact, augmentation summary (setup_b0/configs/manifest.yaml sampled_vars for <video>_aug0), and augmented auto-labeling artifact summary from outputs/pseudo_labeled_augmented/<video>_aug0 using the workspace-local run copy under media/vda/runs/<run_id>/.
  • If submit fails with missing cache wiring, run setup_model_cache.yaml and rerun pre_submit_guard.py.
  • If workers stall on endpoints, verify vlm_url/llm_url health and /v1 availability before resubmitting.

Source: SKILL.md on GitHub

Third-party checks

2 warnings3mo3 checks · Risk SAFE
  • Gen Agent Trust Hub3mo

    The skill is a workflow orchestrator for video data augmentation and auto-labeling on the NVIDIA OSMO platform. It manages the end-to-end pipeline, including credential verification, configuration generation, worker execution, and result retrieval. No security issues or malicious patterns were detected; all external dependencies and network operations are associated with trusted vendors and the skill's primary functionality.

  • Socket3mo

    3 alerts: gptAnomaly

  • Snyk3mo

    Risk: MEDIUM · 1 issue

Provenance

Signed by skilld at 0482ebc. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 4 months ago

Capability

Other metadata
metadata
{
  "owner": "NVIDIA",
  "service": "data",
  "version": "1.0.0",
  "reviewed": "2026-05-26",
  "author": "NVIDIA",
  "tags": [
    "physical-ai",
    "video-data-augmentation",
    "auto-labeling",
    "cosmos"
  ]
}

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