Update README.md

README.md

@@ -7,13 +7,60 @@ dataset_info:
     dtype: string
   splits:
   - name: train
-    num_bytes: 1759539306.0
+    num_bytes: 1759539306
     num_examples: 2160000
   download_size: 1866820804
-  dataset_size: 1759539306.0
+  dataset_size: 1759539306
 configs:
 - config_name: default
   data_files:
   - split: train
     path: data/train-*
+language:
+- ar
 ---
+# Arabic OCR Dataset
+
+## Overview
+The Arabic OCR Dataset is a comprehensive resource aimed at enhancing Optical Character Recognition (OCR) capabilities for the Arabic language. The dataset consists of over 2 million labeled images of Arabic text extracted from diverse sources, ideal for training and benchmarking Arabic OCR models.
+
+## Dataset Details
+- **Dataset Size**: ~2.16 million labeled samples
+- **Total File Size**: 1.87 GB
+- **Format**: Parquet
+- **Modalities**: Images and Text
+- **Languages**: Arabic
+
+## Structure
+Each entry in the dataset includes:
+- `image`: An image file containing Arabic text.
+- `text`: Corresponding Arabic text as ground truth.
+
+The images vary in width from 29px to 222px, containing text samples ranging from 7 to 10 characters in length.
+
+## Intended Uses
+This dataset is designed for:
+- Training state-of-the-art Arabic OCR models.
+- Evaluating performance of OCR systems.
+- Research in Arabic Natural Language Processing (NLP).
+
+## Limitations
+- Text length is limited to short to medium-length Arabic text snippets.
+- Variability in image quality may affect OCR performance.
+
+## How to Use
+### Loading the Dataset
+```python
+from datasets import load_dataset
+
+# Load Arabic OCR Dataset
+dataset = load_dataset("mssqapi/Arabic-OCR-Dataset")
+```
+
+### Accessing Data Samples
+```python
+# Example of accessing data sample
+sample = dataset['train'][0]
+print(sample['text'])
+display(sample['image'])
+```