odia-ocr-benchmark / README.md
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---
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
```python
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