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layout-parser

layout-parser

Routes LayoutParser workflows for document layout objects, document I/O, visualization, OCR, and layout-detection model wrappers.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: layout-parser description: "Routes LayoutParser workflows for document layout objects, document I/O, visualization, OCR, and layout-detection model wrappers." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

LayoutParser

LayoutParser is a document-image analysis toolkit for layout objects, page/token loading, OCR parsing, visualization, and layout-detection model wrappers.

Use this root skill as a router. Read the owning sub-skill for detailed API notes, workflow steps, and troubleshooting.

Install and first checks

Base install:

pip install layoutparser

OCR support:

pip install "layoutparser[ocr]"

Layout-model support:

pip install "layoutparser[layoutmodels]"
pip install "layoutparser[effdet]"
pip install "layoutparser[paddledetection]"

Detectron2 still uses its own backend install path:

pip install layoutparser torchvision
pip install "detectron2@git+https://github.com/facebookresearch/detectron2.git@v0.5#egg=detectron2"

For local inspection from a checkout, prefer an isolated environment and an editable install in that private environment rather than mutating the source repository.

Minimal import checks:

python -c "import layoutparser as lp; print(lp.__version__)"
python -c "from layoutparser import Layout, Rectangle; print(Layout([Rectangle(0, 0, 10, 10)]))"

If backend availability is uncertain, run the bundled inspector:

python scripts/inspect_backends.py

For a local smoke check that stays inside synthetic data, use:

python scripts/smoke_layoutparser_core.py

Route map

layout-objects

Read this for:

  • Interval, Rectangle, Quadrilateral, TextBlock, and Layout
  • coordinate transforms, padding, shifting, scaling, cropping
  • union, intersect, relative_to, condition_on, is_in
  • Layout sorting, filtering, serialization, and line/category grouping

layout-io

Read this for:

  • load_json, load_dict, load_csv, load_dataframe, load_pdf
  • JSON/CSV/DataFrame round-trips and PDF token extraction
  • page metadata, block_type, and layout export/import issues
  • COCO-style annotation conversion patterns

visualization

Read this for:

  • draw_box and draw_text
  • color maps, alpha handling, font settings, vertical text, and layout overlays
  • turning detected or loaded layouts into readable page visuals

layout-models

Read this for:

  • AutoLayoutModel
  • Detectron2LayoutModel, EfficientDetLayoutModel, and PaddleDetectionLayoutModel
  • lp:// config parsing, model catalogs, label maps, and backend selection
  • model download, cache, and device-selection behavior

ocr

Read this for:

  • TesseractAgent, TesseractFeatureType
  • GCVAgent, GCVFeatureType
  • OCR response parsing, saved-response loading, and text aggregation
  • credential and binary requirements for live OCR

Root references

  • Read references/api-reference.md for the top-level public API map.
  • Read references/workflows.md for cross-sub-skill document workflows.
  • Read references/repo-provenance.md before checking staleness or refreshing.
  • Read references/repo-routing-metadata.json only when verifying managed repo-skills-router placement.

When to jump to troubleshooting

Read references/troubleshooting.md when you see any of these:

  • missing optional backend imports
  • pkg_resources / setuptools issues around google-cloud-vision==1
  • tesseract or credential problems
  • pdf2image / poppler problems
  • InvalidShapeError, NotSupportedShapeError, or layout validation errors
  • model download, cache, or lp:// parsing failures

Notes for future agents

  • This skill is public runtime guidance; do not rely on the original checkout remaining available.
  • Runtime links should stay inside this generated skill tree.
  • Use the sub-skill that matches the user’s primary workflow first, then cross- reference the others when a task spans multiple layers.
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