用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/microsoft/physical-ai-toolchain --skill synthetic-data命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Generate, transfer, and consume environment-specific Azure, AKS, OSMO, ACR, and Azure ML deployment bundles. Use when: discovering deployed environment details; creating OSMO image manifests or platform values; preparing a HiL host; uploading or downloading deployment files through Azure Key Vault; or deploying with generated environment configuration.
Start and interact with the Dataset Analysis Tool (dataviewer) for browsing, annotating, and exporting robotic training episodes
Submit, monitor, analyze, and evaluate LeRobot imitation learning training jobs on OSMO with Azure ML MLflow integration and inference evaluation - Brought to you by microsoft/physical-ai-toolchain
基于 SOC 职业分类
正在显示 SKILL.md
| name | synthetic-data |
| description | Generate synthetic training data using NVIDIA Cosmos world foundation models for SDG pipelines |
Generate photorealistic training data using NVIDIA Cosmos world foundation models — Cosmos Transfer, Cosmos Predict, and Cosmos Reason.
The Synthetic Data domain provides SDG pipelines that transform simulation-rendered frames into photorealistic training data, predict future environment states, and curate output for training quality.
| Stage | Model | Purpose |
|---|---|---|
| Transfer | Cosmos Transfer 2.5 | Convert Isaac Sim renders to photorealistic images |
| Predict | Cosmos Predict 2.5 | Generate future frame sequences from observations |
| Reason | Cosmos Reason 2 | Assess data quality and filter training samples |
SDG workflows can be submitted via OSMO or AzureML:
synthetic-data/workflows/osmo/synthetic-data/workflows/azureml/| File | Purpose |
|---|---|
synthetic-data/README.md | Domain overview and directory structure |
synthetic-data/workflows/osmo/sdg-pipeline.yaml | End-to-end OSMO SDG pipeline |
synthetic-data/cosmos/configs/README.md | Model configuration reference |
synthetic-data/specifications/synthetic-data.specification.md | SDG pipeline specification |
synthetic-data/specifications/cosmos-integration.specification.md | Cosmos model integration specification |
All NVIDIA Cosmos containers require:
| Variable | Value |
|---|---|
ACCEPT_EULA | Y |
PRIVACY_CONSENT | Y |
NVIDIA_DRIVER_CAPABILITIES | all |
Each Cosmos model stage requires a minimum of 1x A100 (40 GB) GPU. H100 (80 GB) recommended for production workloads.