Update README.md

README.md

@@ -44,6 +44,30 @@ This dataset is intentionally provided as a **single training split** containing
 You are responsible for creating appropriate validation and test splits using the provided training data. We recommend using 70-80% for training, 10-15% for validation, and 10-15% for testing, depending on your requirements.
 
 
+# <span style="font-size: 1.5em; font-weight: bold;">Key features</span>
+- 72,317 images of close-up eyes, people's faces, and real-life scenes.
+- All bounding boxes have been **completely re-annotated manually** with **Roboflow** to ensure maximum accuracy.
+- Annotations provided in **ready-to-use COCO format** for easy integration with most object detection frameworks.
+- **Single Training Split:** The dataset is provided as a single training split to allow maximum flexibility in creating custom train/validation/test splits for different research needs.
+- <u>Various Image acquisition conditions</u>:
+   - Single person (1 or 2 eyes), whole people, groups, ...
+   - Open and closed eyes.
+   - Diversity of lighting and poses.
+
+
+# <span style="font-size: 1.5em; font-weight: bold;">Repository File Structure</span>
+The repository contains the following files. The standard structure for a COCO dataset on Hugging Face is automatically created when loaded.
+
+```text
+Eyes-Detection/
+├── README.md                 # This dataset card
+├── dataset_info.json         # Dataset metadata for Hugging Face
+├── annotations.coco.json     # Annotations in COCO format
+├── images.zip                # All images in a single compressed archive
+├── README.dataset.txt        # Marginal info
+└── LICENSE                   # The CC BY-NC-SA 4.0 license file
+``` 
+
 
 # <span style="font-size: 1.5em; font-weight: bold;">Loading the Dataset with Hugging Face 🤗</span>
 This dataset is in COCO format and can be easily loaded using the <u>datasets library</u> distributed by HuggingFace.  
@@ -101,17 +125,6 @@ coco_dataset = CocoDetection(
 ```  
   
 
-# <span style="font-size: 1.5em; font-weight: bold;">Key features</span>
-- 72,317 images of close-up eyes, people's faces, and real-life scenes.
-- All bounding boxes have been **completely re-annotated manually** with **Roboflow** to ensure maximum accuracy.
-- Annotations provided in **ready-to-use COCO format** for easy integration with most object detection frameworks.
-- **Single Training Split:** The dataset is provided as a single training split to allow maximum flexibility in creating custom train/validation/test splits for different research needs.
-- <u>Various Image acquisition conditions</u>:
-   - Single person (1 or 2 eyes), whole people, groups, ...
-   - Open and closed eyes.
-   - Diversity of lighting and poses.
-
-
 # <span style="font-size: 1.5em; font-weight: bold;">Preprocessing e Augmentation applied</span>
 
 1. **<u>Preprocessing</u>**:
@@ -129,20 +142,6 @@ coco_dataset = CocoDetection(
    - Cutout: 7 boxes, each with a size of 2%.
 
 
-# <span style="font-size: 1.5em; font-weight: bold;">Repository File Structure</span>
-The repository contains the following files. The standard structure for a COCO dataset on Hugging Face is automatically created when loaded.
-
-```text
-Eyes-Detection/
-├── README.md                 # This dataset card
-├── dataset_info.json         # Dataset metadata for Hugging Face
-├── annotations.coco.json     # Annotations in COCO format
-├── images.zip                # All images in a single compressed archive
-├── README.dataset.txt        # Marginal info
-└── LICENSE                   # The CC BY-NC-SA 4.0 license file
-``` 
-
-
 
 # <span style="font-size: 1.5em; font-weight: bold;">License - CC BY-NC-SA 4.0</span>