Datasets:
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-ocrwith configoriya(printed)darknight054/indicstr12-cropswith configodia(scene_text)newspaper: Odia newspaper scans/clippingsbooks: Odia book page imagesdigital: odia digital content
Notes
- Includes long-text samples for paragraph-level OCR evaluation.
- The
sourcefield records origin for each sample.
License
CC-BY-4.0