Text Recognition Dataset
This dataset is a comprehensive collection of Arabic and English text recognition samples designed for benchmarking and evaluating text recognition models. The dataset combines multiple sources to provide diverse text recognition challenges across different domains, scripts, and image conditions.
📁 Dataset Structure
- Images are stored in .png format ()
- Accompanied by a CSV file (TextRecognitionAnnotations.csv) with ground truth annotations and text characteristics.
📚 Data Sources and Attribution
This dataset is compiled from samples taken from the following sources:
- EvArEST Dataset: Arabic scene text samples from HGamal11/EvArEST-dataset-for-Arabic-scene-text
- Doctors Handwritten Prescription BD Dataset: Medical prescription samples from Kaggle - mamun1113
- AHAWP Per User Dataset: Handwritten Arabic text samples from Kaggle - mohammedfa
Note: This dataset contains selected samples from the above sources, with additional text characteristics and annotations added for comprehensive text recognition evaluation.
📊Dataset Statistics
| Metric | Value |
|---|---|
| Total Images | 3243 |
| Languages | English and Arabic |
| Image Format | .png |
📊 Data Insights
🌍Text Characteristics
| Characteristic | Values |
|---|---|
| Language | Arabic, English |
| Type of Word | String, Number, Character and Mixed |
| Text Type | Typed and Handwritten |
| Image Category | scene_text, medical_prescription, handwritten |
🛠️ How to Use
You can load the dataset using:
from datasets import load_dataset
ds = load_dataset("BatSilver/TextRecognitionData")