physical-ai-defect-image-generation
Installation
SKILL.md
Physical AI Defect Image Generation
Table of Contents
- Supported Flows
- Disambiguation (full table in
references/disambiguation.md) - Step 0: Select Flow, Cookbook, and Gather Inputs
- Common Preconditions (long-form in
references/preconditions.md) - Flow walkthroughs (one entry per flow; details in
references/flows/) - OSMO Monitoring
- 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.