Agent skill · nvidia
cdf-defect-image-generation
Generate synthetic PCB inspection images on Kubernetes with the SMT Defect Image Generation (DIG) DAG in CDF Orchestration. The DAG renders components in simulation, turns the renders into realistic golden images (sim2real), and uses AnomalyGen to add texture defects such as solder bridges, excess solder or missing components. Simulation can also render shift, tombstone and sideflip pose defects. Use it to build DIG payloads, pick a pipeline mode (full, simulation, sim2real or defect-only), check GPU readiness, follow a run, and match each defect image to its golden and simulated source. Not for running Simulation, Augmentation or AnomalyGen on their own.
What it needs
About 9k tokens when loaded.
What this skill does
CDF Orchestration — SMT Defect Image Generation Run defectimagegenerationsmtdagk8s: CDF Simulation renders PCB components, CDF Augmentation turns the renders into realistic clean (golden) images, and CDF AnomalyGen adds texture defects. Simulation can also render pose defects (shift, tombstone, sideflip). One DAG serves every mode; pipelinemode selects which stages run. Requirements Execution needs an authorized Kubernetes connection, a reachable Airflow 3 controller with the DIG DAG loaded, and storage and model access for the chosen mode. The payload checker needs a trusted CDF Orchestration checkout and its Airflow Python environment. Explaining the workflow or drafting JSON needs neither. Execution readiness also requires the companion script skills/cdf-orchestration-preflight/scripts/storagecheck.py in the product checkout. If it is unavailable, report the missing dependency as a readiness blocker; do not skip the storage mapping check. In that checkout, the payload contract is defined by airflow/dags/workflows/defectimagegenerationdag/callables/smt/models.py and airflow/dags/workflows/defectimagegenerationdag/callables/smt/configgeneration.py. The component templates that payload overrides merge into are in airflow/dags/workflows/defectimagegenerationdag/configs/smt/. Available scripts Script Purpose --- --- scripts/payload.py Check a payload with the DAG's own model and compiler, then print job counts, output paths and effective AnomalyGen staging. Submits nothing and accesses no storage or cluster. Instructions 1. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/cdf-defect-image-generation