PAIDF Augmentation Pipeline Skill

Unified pipeline for augmenting camera data through NVIDIA generative AI models with automated captioning, generation, and quality evaluation. BYOM (bring-your-own-model): every model is reached over a remote HTTP endpoint described by one entry in the config's endpoints: list; adding a model is usually a config change, not code.

Purpose

Use this skill to drive the PAIDF augmentation pipeline end to end:

• Select the right model — Cosmos Transfer 2.5 (transform a video), Cosmos Predict 2.5 (generate/extend video), image-edit (edit an image), or image-to-video (animate a first frame: Cosmos3 or Veo 3.1).
• Author and validate YAML configs against the PipelineConfig Pydantic schema.
• Configure captioning (VLM, LLM, deterministic VLM-template, text, or file) and evaluators (hallucination check, attribute verification, VLM verification).
• Launch and run inference inside the paidf-augmentation:1.1.0 Docker container (remote-API only — no local model weights).

Use this skill when running inference, authoring or editing configs, debugging validation or runtime errors, adding data samples, configuring captioning, tuning generation parameters, registering BYOM endpoints/adapters, or setting up evaluators. Trigger keywords: augmentation, cosmos transfer, cosmos predict, image edit, image-to-video, veo, image attribute augmentation, defect image generation, captioning, attribute verification, config validation.

Do not use this skill for training or fine-tuning models, deploying clusters or NIM endpoints, or unrelated application/database development.

Prerequisites