---

name: data-preparation description: "Prepare and validate PaddleGAN dataset layouts, dataroot mappings, and preprocessing inputs for translation, super-resolution, and lip-sync workflows." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Data Preparation

Use this sub-skill when the task is about making PaddleGAN data usable before training or inference.

It covers:

• CycleGAN / U-GAT-IT style unpaired layouts
• Pix2Pix-style paired layouts with split AB images
• custom paired or unpaired image folders
• DIV2K cropping and other SR inputs
• LRS2 preprocessing for Wav2Lip
• REDS and Vimeo90K sequence expectations
• RealSR synthetic degradation outputs
• config dataroot and related path updates

Entry points

• references/dataset-layouts.md
• references/preprocessing-scripts.md
• references/troubleshooting.md

Bundled helpers

• scripts/check_dataset_layout.py
• scripts/process_div2k_data.py

Route elsewhere

• train/evaluate/resume command construction → training-configs
• export/static inference/deployment outputs → deployment-export
• benchmark execution and performance harnesses → out of scope

Guardrails

• Do not run downloads, training, inference, or face/video preprocessing by default.
• Prefer explicit local paths over hidden repository defaults.
• If a dataset layout is ambiguous, validate the directory tree first with scripts/check_dataset_layout.py.