---
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

```python
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"]
```

## 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

## Citation

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

```bibtex
@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.