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physical-ai-defect-image-generation

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Use when the user wants to orchestrate defect image generation with NVIDIA Cosmos AnomalyGen (Cosmos-Predict2-derived) on OSMO for PCBA, metal surface, and glass inspection. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and AnomalyGen to create initial PCBA datasets. The Day 1 path performs inference and labeling on real images. This skill helps with first-time asset setup, creation of finetuning checkpoints, and configuring deployment. Trigger keywords: defect image generation, dig workflow, dig pipeline, defect image detection workflow, aoi pipeline, aoi anomalygen, usd2roi anomalygen, day 0 pcba, day 1 pcba, day 1 real-photo alignment, day 1 manual roi, metal surface anomaly, glass defect, anomalygen finetune, setup_pcb, setup_metal, setup_glass, setup_pretrained, dig setup, dig datasets, dig pretrained checkpoint, dig image-edit endpoint, cosmos defect generation, cosmos-predict2 defect, cosmos-anomalygen, cosmos predict2 finetune.

skills/physical-ai-defect-image-generation/SKILL.md

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Repository last updated
Nov 6, 2026
License
Apache-2.0

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# Physical AI Defect Image Generation


## Table of Contents

- [Supported Flows](#supported-flows)
- [Disambiguation](#disambiguation-handle-vague-requests-before-committing) (full table in `references/disambiguation.md`)
- [Step 0: Select Flow, Cookbook, and Gather Inputs](#step-0-select-flow-cookbook-and-gather-inputs)
- [Common Preconditions](#common-preconditions-all-flows) (long-form in `references/preconditions.md`)
- [Flow walkthroughs](#flow-walkthroughs) (one entry per flow; details in `references/flows/`)
- [OSMO Monitoring](#osmo-monitoring)
- [Supporting files](#supporting-files)

End-to-end orchestration of defect image generation, augmentation, and labeling pipelines for AOI (Automated Optical Inspection) datasets. **AnomalyGen = Cosmos-Predict2-2B finetuned per use case** (Cosmos-AnomalyGen-PCB-2B, -Metal-2B, -Glass-2B). Every flow has a canonical OSMO workflow YAML in `assets/configs/` that chains all steps non-interactively. Use-case cookbooks in `assets/cookbooks/` provide PCBA usd2roi/image-edit configs and AnomalyGen training configs for PCBA, metal surface, and glass inspection. This skill governs flow selection, data handoffs, and submit commands; component internals live in each component's `SKILL.md`.
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