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README.md

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-# 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.
-
----
-
-## 📁 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.
-
----
-
-## 📚 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)
-
----
-
-## 📊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) |
-
----
-
-## 📊 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 |
-
-
-
----
-
-# 🛠️ How to Use
-You can load the dataset using:
-
-```python
-from datasets import load_dataset
-
-ds = load_dataset("Ejada/TextDetectionData")
+# 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.
+
+---
+
+## 📁 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.
+
+---
+
+## 📚 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)
+
+---
+
+## 📊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) |
+
+---
+
+## 📊 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 |
+
+
+
+---
+
+# 🛠️ How to Use
+You can load the dataset using:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("BatSilver/TextDetectionData")
 ```