القائمة
Generate synthetic training data using NVIDIA Cosmos world foundation models for SDG pipelines
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اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
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npx skills add https://github.com/microsoft/physical-ai-toolchain --skill synthetic-dataيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
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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
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عرض 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.