| name | synthetic-data |
| description | Generate synthetic training data using NVIDIA Cosmos world foundation models for SDG pipelines |
Synthetic Data Skill
Generate photorealistic training data using NVIDIA Cosmos world foundation models — Cosmos Transfer, Cosmos Predict, and Cosmos Reason.
Overview
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.
Pipeline Stages
| 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 |
Workflow Submission
SDG workflows can be submitted via OSMO or AzureML:
- OSMO workflows:
synthetic-data/workflows/osmo/
- AzureML jobs:
synthetic-data/workflows/azureml/
Key Files
| 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 |
Environment Requirements
All NVIDIA Cosmos containers require:
| Variable | Value |
|---|
ACCEPT_EULA | Y |
PRIVACY_CONSENT | Y |
NVIDIA_DRIVER_CAPABILITIES | all |
GPU Requirements
Each Cosmos model stage requires a minimum of 1x A100 (40 GB) GPU. H100 (80 GB) recommended for production workloads.
