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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.

Ask your Agent

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

This session only. Nothing lands on disk.

referencesflowse2e_super_resolution.md

≈631 tokens on demand. Your agent reads this file only when SKILL.md points to it.

E2E (Super-Resolution Gated)

Table of Contents

Runs full VDA graph in sequential order where original auto-labeling (with SR enabled in setup .env) gates augmentation, then labels augmented outputs.

When to use

  • User requests SR-gated end-to-end execution.
  • User prefers deterministic sequencing over parallel throughput.
  • Hardware/resources favor sequential stage progression.

Graph

setup_group
  setup (SUPER_RESOLUTION_ENABLED=true)
      ▼
auto_labeling_original_group
  pl_original_worker_0
      ▼
augmentation_group
  cosmos_worker_0
      ▼
auto_labeling_augmented_group
  pl_augmented_worker_0

Inputs

Input Source Required by
Source video <storage_url>/datasets/<dataset>/<video>.mp4 setup + original AL + augmentation
Cosmos cache <storage_url>/data/models/cosmos_transfer cosmos_worker_0
Auto-labeling cache <storage_url>/data/models/auto_labeling pl_original_worker_0, pl_augmented_worker_0
VLM endpoint default in-cluster NIM or explicit override all workers
LLM endpoint default in-cluster NIM or explicit override all 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/e2e_super_resolution.yaml. This flow runs the SR-gated sequential pipeline, 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/
   ├─ pseudo_labeled/<video>/
   ├─ 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 auto-labeling artifact summaries for both outputs/pseudo_labeled/<video> and outputs/pseudo_labeled_augmented/<video>_aug0 using the workspace-local run copy under media/vda/runs/<run_id>/.
  • If this mode appears parallel, confirm you submitted e2e_super_resolution.yaml (not e2e.yaml).
  • If augmentation starts before original AL completion, inspect group/task dependencies in rendered workflow.

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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