Update README.md

README.md

@@ -16,11 +16,14 @@ size_categories:
 
 <!-- Provide a quick summary of the dataset. -->
 
-The "FracAtlas" dataset is a collection of musculoskeletal radiographs for fracture classification, localization, and segmentation. 
-It includes 4,083 X-Ray images for bones with annotations in multiple formats.The annotations include labels, classes, and etc. 
+The "FracAtlas" dataset is a collection of musculoskeletal radiographs for bone fracture classification, localization, and segmentation. 
+It includes 4,083 X-Ray images (717 fracture images) with corresponding annotations in multiple formats. The annotations include segmentations, width, and etc in COCO, VGG, YOLO, and Pascal VOC format. 
 The dataset is intended for use in deep learning tasks in medical imaging, specifically targeting the understanding of bone fractures. 
 It is freely available under a CC-BY 4.0 license.
 
+This script provides a Hugging Face `datasets` loader for the FracAtlas dataset. The generated dataset includes high-quality X-Ray images and incorporated detailed annotations from COCO JSON format for segmentation
+and bounding box information, as well as additional localization data from PASCAL VOC XML files. The loader handles downloading and preparing the dataset, making it readily available for machine learning models and analysis
+tasks in medical imaging, especially focusing on the detection and understanding of bone fractures.
 
 - **Curated by:** Abedeen, Iftekharul; Rahman, Md. Ashiqur; Zohra Prottyasha, Fatema; Ahmed, Tasnim; Mohmud Chowdhury, Tareque; Shatabda, Swakkhar
 - **License:** cc-by-2.5
@@ -47,25 +50,28 @@ The "FracAtlas" dataset can be used to develop multiple machine learning or dee
 
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
 
+### Original Dataset Schema
 The original zip file contains 3 subfolders “images”, “Annotations”, “utilities” and a “dataset.csv” file. 
 In the "image" folder, it contains 2 subfolders: "Fractured" and "Non-fractured", and each image is stored in corresponding folder in JPG format.
 In the "Annotations" folder, it contains 4 subfolders: "COCO JSON", "PASCAL VOC", "VGG JSON", and "YOLO". Annotations are stored in their corresponding folders. More details can be read in ### Annotations section.
-In the "utilities" folder, it contains several programming scripts that could be used to convert the raw files to a more readable format. None of them were used in this dataset.
-The "dataset.csv" contains many basic variables for each image: \
- - image_id [string]: The unique identifier for each radiograph image in the dataset. \
- - hand [int]: A binary indicators (1 or 0) marking the presence of hand in the radiograph \
- - leg [int] : A binary indicators (1 or 0) marking the presence of leg in the radiograph \
- - hip [int] : A binary indicators (1 or 0) marking the presence of hip in the radiograph \
- - shoulder [int]: A binary indicator (1 or 0) marking the shoulder in the radiograph \
- - mixed [int]: A binary indicator of whether the image contains multiple body parts \
- - hardware [int]: A binary indicator marking the presence of medical hardware (i.e. screws or plates) in the image \\
- - multiscan [int]: A binary indicator signifies whether the image is part of a set of multiple scans \
- - fractured [int]: A binary indicator of whether there is a fracture present in the image \
- - fracture_count [int]: The number of fractures present in the image \
- - frontal [int]: A binary indicator denoting the front orientation of the radiograph \
- - lateral[int]: A binary indicator denoting the side orientation of the radiograph \
- - oblique [int]: A binary indicator denoting denoting the angled orientation of the radiograph 
-
+In the "utilities" folder, it contains several programming scripts that could be used to convert the raw files to a more readable format. None of them were used in this dataset loader.
+The "dataset.csv" contains many basic variables for each image: <br />
+ - image_id [string]: The unique identifier for each radiograph image in the dataset. <br />
+ - hand [int]: A binary indicators (1 or 0) marking the presence of hand in the radiograph <br />
+ - leg [int] : A binary indicators (1 or 0) marking the presence of leg in the radiograph <br />
+ - hip [int] : A binary indicators (1 or 0) marking the presence of hip in the radiograph <br />
+ - shoulder [int]: A binary indicator (1 or 0) marking the shoulder in the radiograph <br />
+ - mixed [int]: A binary indicator of whether the image contains multiple body parts <br />
+ - hardware [int]: A binary indicator marking the presence of medical hardware (i.e. screws or plates) in the image <br />
+ - multiscan [int]: A binary indicator signifies whether the image is part of a set of multiple scans <br />
+ - fractured [int]: A binary indicator of whether there is a fracture present in the image <br />
+ - fracture_count [int]: The number of fractures present in the image <br />
+ - frontal [int]: A binary indicator denoting the front orientation of the radiograph <br />
+ - lateral[int]: A binary indicator denoting the side orientation of the radiograph <br />
+ - oblique [int]: A binary indicator denoting denoting the angled orientation of the radiograph <br />
+
+### Updated Dataset Schema
+In this dataset loader, certain existed variables are modified into specific Huggingface feature, such 
 Above are the data that could be directly extracted from the downloaded files. Other than the above-mentioned features, this huggingface dataset also extract infomation from annotations files to present a more systematic and clean FracAtlas dataset.
 Other variables are extracted from the annotations files:
  - Image [image]: A PIL image object denoting each X-ray image \