core-ocr-and-kie

core-ocr-and-kie

Use this sub-skill when the task is to run or debug docTR's Python end-to-end inference pipelines:

• doctr.io.DocumentFile or a list of RGB NumPy pages -> doctr.models.ocr_predictor(...) -> Document.
• doctr.io.DocumentFile or a list of RGB NumPy pages -> doctr.models.kie_predictor(...) -> KIEDocument.
• Predictor-level flags for rotated/skewed pages, orientation/language detection, layout detection, table detection, ignored layout regions, batching, and device movement.
• Sanity-checking output object shapes, page counts, geometry conventions, and the no-download/random-weight caveat.

Do not use this sub-skill for raw file loading/export format details, model zoo catalogs/custom weights/ONNX export, CLI wrappers, training, datasets, or evaluation scripts. Route those tasks to sibling sub-skills:

• Document loading and result export/render details: document-io-and-exports
• Architecture catalogs, custom models, optimization, export, vocab whitelisting: models-and-customization
• doctr-cli and bundled command-line helpers: cli-and-scripts
• Datasets, training, metrics, and evaluation: datasets-training-and-evaluation

Read first

1. For API recipes and option interactions, read references/ocr-kie-workflows.md.
2. For failure diagnosis, read references/troubleshooting.md.
3. For a safe import/factory/optional-forward smoke check, run or adapt scripts/ocr_api_smoke.py.

Operating rules

• Prefer explicit det_arch, reco_arch, pretrained, pretrained_backbone, assume_straight_pages, and batch-size choices when reproducibility matters.
• Treat pretrained=False as an API/shape smoke mode only; randomly initialized detection and recognition models do not produce useful OCR.
• Be explicit about network/cache behavior: pretrained model weights and some orientation helpers may download on first use unless already cached or disabled.
• Validate outputs before downstream use: Document.pages for OCR, KIEDocument.pages[*].predictions for KIE, optional page.layout, optional page.tables, and relative geometries.