KarantaOCR-Bench / README.md
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metadata
license: odc-by
tags:
  - text
  - OCR
configs:
  - config_name: karantaocr-bench
    data_files:
      - split: diacritics
        path:
          - diacritics.jsonl
language:
  - yo
  - ig
  - sw
  - ha
  - af
  - ar
pretty_name: KarantaOCR-Bench
size_categories:
  - 1K<n<10K
task_categories:
  - text-generation

KarantaOCR - Bench

Karanta OCR Logo

KarantaOCR-Bench is a unit-test–style evaluation dataset, similar to olmOCR-bench. It consists of 70 PDF documents and 300 test cases spanning multiple document types. All the tests were manually verified by us. KarantaOCR-Bench is designed specifically to evaluate document text extraction for Documents with diacritics and special characters, covering a diverse range of document formats and languages commonly under-represented in existing OCR benchmarks.

Data Schema

Below is a schema of each test case and what it means:

  • pdf [str]: This is the name of the pdf file in the pdf directory
  • page [str]: This is the page of the document for this test case
  • id [str]: Unique ID for this test case
  • type [str]: This is the test type; a description of each test type can be found in the next section
  • max_diffs [int]: This is the maximum allowable difference in the OCR outputs and test case for it to pass
  • text [str]: This is the text span that we search for in the OCR outputt.
  • case_sensitive [bool]: This indicates whether the test case is case sensitive or not
  • checked [str]: This indicates whether or not we have verified this test case manually
  • url [str]: The original file name of the document
  • before [str]: This only applies to text-order tests and this is the text span that should exist before
  • after [str]:This only applies to text-order tests and this is the text span that should exist after

Test Case Types

KarantaOCR-Bench is designed to augment OlmoOCR test with an additional test category for Diacritics and Special Chars:

  • Presence: Presence tests check whether a provided span of text exists in the OCR output. Matches are evaluated with a tolerance defined by the max_diffs field, allowing for limited character-level differences.

Results

JSONL File KarantaOCR (3B) RoLMOCR (7B) NanoNetsOCR-2 (3B) OLMOCR-2 (7B)
Diacritics & Special Characters 61.6 53.6 55.1 55.5

How to Run the Benchmark on your Model

We are working on a comprehensive guide on how to evaluate your models on this benchmark.

Coming Soon...

Citation Information

Coming soon ...