odia-ocr-benchmark / README.md
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metadata
license: cc-by-4.0
task_categories:
  - image-to-text
language:
  - or
tags:
  - ocr
  - odia
  - oriya
  - indic
  - benchmark
size_categories:
  - n<1K

Odia OCR Benchmark Dataset

Description

A curated benchmark dataset for evaluating OCR models on Odia (Oriya) text recognition. Contains handwritten, printed, scene text, newspaper, books, and digital categories, including both short samples and long-text examples for OCR evaluation.

Dataset Structure

  • image: The input image (PIL Image)
  • ground_truth: The correct Odia text transcription
  • category: Type of text (handwritten, printed, scene_text, newspaper, books, digital)
  • text_length: short (1-3 words), medium (4-10 words), long (10+ words)
  • source: Original dataset source or "manual"

Usage

from datasets import load_dataset

dataset = load_dataset("Iftesha/odia-ocr-benchmark")

# Access a sample
sample = dataset["train"][0]
image = sample["image"]
text = sample["ground_truth"]

Categories

Category Description
handwritten Handwritten Odia text (word/short phrase level)
printed Printed/typed Odia text
scene_text Text in natural scenes (signboards, posters, etc.)
newspaper Odia newspaper clippings (including long text)
books Scanned Odia book pages (including long text)
digital Screenshots from Odia digital content

Sources

  • OdiaGenAIOCR/odia-ocr-merged (handwritten)
  • darknight054/indic-mozhi-ocr with config oriya (printed)
  • darknight054/indicstr12-crops with config odia (scene_text)
  • newspaper: Odia newspaper scans/clippings
  • books: Odia book page images
  • digital: odia digital content

Notes

  • Includes long-text samples for paragraph-level OCR evaluation.
  • The source field records origin for each sample.

License

CC-BY-4.0