# Text Detection Dataset 
This dataset is a comprehensive collection of Arabic and English text detection samples designed for benchmarking and evaluating text detection models. The dataset combines samples from multiple open-source datasets to provide diverse text detection challenges across different domains, scripts, and image conditions.

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## 📁 Dataset Structure
- Images are stored in .jpg format in the "Text Detection Images" folder
- Accompanied by a CSV file (textdetectionannotations.csv) with bounding box coordinates and image characteristics.

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## 📚 Data Sources and Attribution

This dataset is compiled from samples taken from the following sources:

- **SROIE Dataset v2**: Scene text detection samples from [Kaggle - urbikn](https://www.kaggle.com/datasets/urbikn/sroie-datasetv2)
- **ICDAR2013**: International Conference on Document Analysis and Recognition 2013 dataset samples
- **EvArEST Dataset**: Arabic scene text samples from [HGamal11/EvArEST-dataset-for-Arabic-scene-text](https://github.com/HGamal11/EvArEST-dataset-for-Arabic-scene-text)
- **Arabic Documents OCR Dataset**: Document text detection samples from [Kaggle - humansintheloop](https://www.kaggle.com/datasets/humansintheloop/arabic-documents-ocr-dataset/data)

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## 📊Dataset Statistics
| Metric         | Value                                  |
|----------------|----------------------------------------|
| Total Images   | 725     |
| Languages      | English and Arabic                      |
| Image Format   | `.jpg`                                 |
| Annotation Type| Bounding Box Coordinates in Polygon format              |
| Source Datasets| 4 (SROIE, ICDAR2013, EvArEST, Arabic Documents OCR) |

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## 📊 Data Insights

**🌍Dataset Characteristics**
| Characteristic    | Values                                  |
|----------------|----------------------------------------|
| Dataset Name      | SROIE, ICDAR2013, EvArEST, Arabic Documents OCR |
| Image Category    | receipt, scene_text|
| Language          | Arabic, English |
| Image Quality      
| - Blurry          | True, False |
| - Noisy           | True, False |
| - Rotated         | True, False |
| Contrast Level    | low, medium, high |
| Brightness Level  | low, medium, high |
| Resolution Category | low, medium, high |
| Complexity Level  | low, medium, high |



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# 🛠️ How to Use
You can load the dataset using:

```python
from datasets import load_dataset

ds = load_dataset("BatSilver/TextDetectionData")
```