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name: layout-models description: "Routes LayoutParser model-zoo inference, backend selection, and lp:// configuration workflows." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

Layout Models

Use this sub-skill when the request is about layout-detection model wrappers, backend selection, or lp:// model paths.

What belongs here

• AutoLayoutModel
• Detectron2LayoutModel
• EfficientDetLayoutModel
• PaddleDetectionLayoutModel
• LayoutModelConfig and lp:// parsing
• model catalogs, label maps, downloads, and cache handling
• choosing CPU vs CUDA for torch-backed models

What does not belong here

• Geometry and layout transforms: use layout-objects
• File loading and PDF parsing: use layout-io
• Rendering regions on images: use visualization
• OCR extraction and response parsing: use ocr

Read these files

• references/guide.md for model-path syntax, backend behavior, and troubleshooting notes
• ../visualization/SKILL.md when the request is about showing predictions
• ../layout-objects/SKILL.md when the request is about post-processing the returned layouts

Fast path

1. Decide whether the user wants a specific backend or automatic backend selection.
2. Check that the relevant backend package is installed before instantiating a backend-specific class.
3. Use the lp:// path form that matches the target dataset and model family.
4. Override label_map only when the catalog does not match the target task.
5. Set device='cpu' explicitly if you do not want the torch-backed classes to choose CUDA on a GPU machine.

Common user requests

• "Load a PubLayNet layout model"
• "Use AutoLayoutModel for this lp:// path"
• "Why does a model backend ImportError happen?"
• "What backend does this lp:// config pick?"
• "How do I install EfficientDet / Detectron2 / PaddleDetection support?"

Minimal smoke

The bundled inspector checks backend availability without downloading model weights:

python ../../scripts/inspect_backends.py

Failure clues

• Missing backend imports usually mean the backend package is not installed in the active environment.
• Unexpected CUDA selection usually means torch sees a GPU-capable build.
• Download/cache issues generally come from PathManager or the model URL, not from the post-processing code.
• If AutoLayoutModel cannot find an exact backend match, it falls back to the dataset name when possible.

Output discipline

When answering, name the backend class, dataset, model family, and lp:// form the user should use. If a backend is optional or unavailable, say which alternate backend can still satisfy the task and what remains unverified.