smart-ocr

Multilingual OCR processes mixed-language documents by recognizing text across 100+ languages simultaneously. It applies language detection and recognition models to scanned materials, accurately extracting foreign text while preserving the original reading order and positional data.

Parsing receipts and business cards from photos requires layout-aware OCR that identifies text regions using bounding boxes. By reconstructing the document layout and sorting text by reading order, the extracted data remains structured for downstream reporting or search indexing.

PaddleOCR supports layout reconstruction for scanned documents by outputting bounding boxes and sorting text by reading order. This layout-aware processing includes image preprocessing steps that clean visual noise, ensuring structured text extraction from complex scanned forms and PDFs.

You can get confidence scores and bounding boxes from OCR text extraction to evaluate recognition accuracy. These metadata outputs accompany the extracted text, allowing you to filter low-confidence characters and verify positional data for screenshots, photos, and scanned pages.

Converting scanned PDF pages to images for OCR processing involves rendering each page into an image format before text recognition. This optional PDF-to-image conversion step allows the OCR engine to apply preprocessing and extract text from visually embedded scanned document content.