Individual skill
ocr-pipeline-and-quality
OCR backends, preprocessing, caches, hOCR, tables and quality comparisons.
.ai-rulez/skills/ocr-pipeline-and-quality/SKILL.md
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- text-extraction Repository topic
- document-intelligence Repository topic
- metadata-extraction Repository topic
- pdf-extraction Repository topic
- python Repository topic
- rag Repository topic
- table-extraction Repository topic
- tesseract Repository topic
- ffi Repository topic
- golang Repository topic
- engineering Derived category
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# OCR pipeline and quality
OCR flows through preprocessing, backend execution, structured conversion, page acceptance, and caching. Backend
outputs are not interchangeable measurements.
## Backends and execution
- All backends implement `OcrBackend`. Tesseract is the default and is bound through the in-repo
`crates/xberg-tesseract` C FFI crate; there is no `leptess` dependency.
- `OcrBackendType` is `Tesseract | PaddleOCR | Candle | Custom`. Sceptre is selected by name through `Custom`, not a
dedicated enum variant.
- Run blocking OCR work through `tokio::task::spawn_blocking`, minimize runtime/FFI lock duration, and respect backend
resource limits.
- Check `PageOrientationHandling` before assuming a backend handles rotated input.