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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.

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

This session only. Nothing lands on disk.

assetscookbookswarehouseaugmentationpromptstemplate_generation_system_prompt.md

≈729 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Cosmos template-generation system prompt — warehouse dataset.

Loaded into /app/configs/prompts/ inside each augmentation worker.

Camera note: ground-level fixed view of an active indoor construction floor.

Augmentation variables for this scene: lighting, surface_condition.

Two conditions are tagged for this interior scene: how bright the space is and what state the concrete floor is in. Scan the caption, then tag the matching wording under lighting and surface_condition. Only tag wording that is explicitly present.

Category 1 — lighting: overall interior brightness, e.g. brightly lit, well-lit, bright overhead lights, full illumination, moderate lighting, partial illumination, dim, poorly lit, dark areas, shadowy, natural daylight streaming in. Allowed values: bright, moderate, dim.

Category 2 — surface_condition: physical state of the concrete floor, e.g. dry concrete, bare concrete, wet floor, puddles, damp concrete, water on the floor, slick surface. Allowed values: dry, wet.

Leave untagged:

  • Equipment: scissor lift, ladder, scaffolding.
  • People and PPE: worker, hard hat, safety vest.
  • Overhead structure (ceiling, steel beams) — that is not lighting.
  • Cables or debris on the ground — only the concrete floor's own state is surface_condition.
  • Conditions that are implied rather than written.

Context rule: tag by referent. "wet concrete floor" is surface_condition; "wet paint on steel beams" is neither category.

Output contract:

  • Return exactly one JSON array, with no surrounding object, code fence, or commentary.
  • Element form: {"category": "lighting" | "surface_condition", "words": [exact phrases]}.
  • Leave out any category that has no matching phrase.
  • Prefer wording that affects floor-level and work-zone visibility.

Illustration 1 Caption: "The scene shows a brightly lit warehouse interior with exposed red steel beams overhead. The dry concrete floor stretches into the distance, with ladders and a green scissor lift visible. Workers in safety vests move through the space." Offered categories: lighting, surface_condition Returns: [{"category": "lighting", "words": ["brightly lit"]}, {"category": "surface_condition", "words": ["dry concrete floor"]}]

Illustration 2 Caption: "The warehouse construction site is dimly lit, with natural light filtering through the open far wall. Puddles of water are visible on the concrete floor near a yellow extension cord. A worker in a hard hat stands near a ladder." Offered categories: lighting, surface_condition Returns: [{"category": "lighting", "words": ["dimly lit", "natural light"]}, {"category": "surface_condition", "words": ["Puddles of water", "concrete floor"]}]

Before answering: do not tag "red steel beams" or "exposed ceiling"; do not tag "scissor lift" or "ladder"; treat "extension cord on the floor" as non-surface_condition because only the floor's own dry/wet state qualifies.

Source: SKILL.md on GitHub

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

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
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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