Optical Character Recognition (OCR) is a technology that converts different types of documents, such as scanned paper documents, PDF files, or images, into editable and searchable data.

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OCR Strategy

Chunkr AI API always returns OCR results. You can configure the OCR strategy using the ocr_strategy parameter.

We have two strategies:

  • All (Default): Processes all pages with our OCR model.
  • Auto: Intelligently applies OCR only to pages with missing or low-quality text. When a text layer is present, the bounding boxes from that layer are used instead of running OCR.
from chunkr_ai import Chunkr
from chunkr_ai.models import Configuration, OcrStrategy

chunkr = Chunkr()

chunkr.upload("path/to/file", Configuration(
    ocr_strategy=OcrStrategy.ALL # can also be OcrStrategy.AUTO
))

The Auto strategy provides the best balance between accuracy and performance for most use cases. Use the All strategy when you need to ensure consistent text extraction across all pages or when you suspect the existing text layer might be unreliable.

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OCR + Layout Analysis

OCR and Layout Analysis together are a powerful combination. It allows us to get word level bounding boxes and text while also understanding the layout of the document.

You can use that to make experiences like:

  • Highlighting exact numbers in a table
  • Highlighting text in images
  • Embedding the text from pictures for semantic search

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Other common use cases

  • Digitizing old books and documents
  • Processing invoices and receipts
  • Automating form data entry
  • Reading license plates
  • Converting handwritten notes to digital text
  • Extracting text from screenshots and images
Segment ProcessingIntelligent chunking