---
language:
- zgh
- tzm
- shi
- gha
- shy
- mzb
task_categories:
- image-to-text
tags:
- ocr
- tifinagh
- tamazight
- document-understanding
- vision-language
pretty_name: Tifinagh OCR 39k
size_categories:
- 10K<n<100K
license: apache-2.0
---

# Tifinagh OCR Dataset (39k Synthetic Samples)

## 📌 Description
This dataset is a comprehensive collection of **39,104 synthetic images** designed for training and evaluating OCR and vision-language models for the **Tifinagh script**. It features a wide variety of fonts, background colors, and text styles in a rectangular format.

## 📊 Dataset Composition
- **39,1K images** in PNG format.
- **Diversity:** Includes multiple background/text color combinations and various font styles (from: IRCAM, Tawalt, Madghis Madi).
- **Format:** Optimized rectangular images (Dynamic scaling with centered text).

## 🧩 Features
Each sample in the `metadata.jsonl` contains:
- `file_name`: Path to the image file.
- `text`: Ground-truth Tifinagh transcription.
- `background_color`: Color of the image background.
- `text_color`: Color of the rendered text.
- `pic_ID`: Unique image identifier.

> [!NOTE]
> The metadata has been **shuffled randomly** to allow a diverse preview of different fonts and styles in the Hugging Face dataset explorer.

## 🎯 Use Cases
- Tifinagh OCR training and evaluation.
- Document understanding for Amazigh languages.
- Vision-language model validation.
- Robustness testing across different typographic styles.

## 🛠 Usage
```python
from datasets import load_dataset

dataset = load_dataset("Tamazight/Tifinagh-OCR-39K")

sample = dataset["train"][0]
print(sample["text"])
sample["image"].show()
```

## 📜 Metadata & Credits
- **Creation Year:** 2024
- **License:** [apache-2.0](https://choosealicense.com/licenses/apache-2.0/)
- **Creator:** Aksel Tinfat for [@Tamazight](https://huggingface.co/Tamazight) project on Hugging Face.