Datasets:

OdiaGenAIOCR
/

odia_ocr_benchmark_data

license: cc-by-nc-sa-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

id: Unique identifier for each sample
image: The input image (PIL Image)
ground_truth: The correct Odia text transcription
category: Type of text (handwritten, printed, scene_text, newspaper, books, digital)

Usage

from datasets import load_dataset

dataset = load_dataset("OdiaGenAIOCR/odia_ocr_benchmark_data")

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

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

Citation

If you find this repository useful, please consider giving 👏 and citing:

@misc{odia_lipi_ocr_2026,
    author = {
        Iftesha Najnin
        Sk Shahid 
        Shantipriya Parida 
    },
    title = {Odia Lipi: An Open-Source OCR Dataset for the Odia Language},
    year = {2026},
    publisher = {Hugging Face},
    journal = {Hugging Face Datasets},
    howpublished = {\url{https://huggingface.co/OdiaGenAI}},
}

Notes

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

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.