Updated README

README.md

@@ -1,41 +1,53 @@
-# 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.
----
-
-## 📊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:
-
-```python
-from datasets import load_dataset
-
-ds = load_dataset("Ejada/TextRecognitionData")
+# 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](https://github.com/HGamal11/EvArEST-dataset-for-Arabic-scene-text)
+- **Doctors Handwritten Prescription BD Dataset**: Medical prescription samples from [Kaggle - mamun1113](https://www.kaggle.com/datasets/mamun1113/doctors-handwritten-prescription-bd-dataset)
+- **AHAWP Per User Dataset**: Handwritten Arabic text samples from [Kaggle - mohammedfa](https://www.kaggle.com/datasets/mohammedfa/ahawp-per-user)
+
+*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:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("Ejada/TextRecognitionData")
 ```