update regarding the download script

added the download section using our GitHub hosted script

README.md

@@ -1,78 +1,87 @@
 ---
 license: cc-by-4.0
 ---
----
+
 # ReefNet Dataset
 
-The ReefNet dataset is a comprehensive, curated collection of (annotated) coral reef images sourced from the CoralNet platform.
-The ReefNet dataset is designed for training and evaluating machine learning models for coral classification on a global scale.
-Furthermore, ReefNet's consolidated labelset and rich metadata facilitate straigforward extraction of custom datasets to support coral classification tasks across different geographic regions.
+The ReefNet dataset is a comprehensive, curated collection of annotated coral reef images sourced from the CoralNet platform. It is designed for training and evaluating machine learning models for coral classification on a global scale. ReefNet's consolidated label set and rich metadata facilitate the straightforward extraction of custom datasets to support coral classification tasks across different geographic regions.
 
 ## Dataset Structure
 
 The dataset is organized as follows:
 
+- **`All_ReefNet_annotations.csv` (2.98 GB)**  
+  Contains all annotations available in the main ReefNet dataset, along with the associated metadata.
+
+- **`Metadata_All_ReefNet_annotations.xlsx` (11 KB)**  
+  Contains metadata for the `All_ReefNet_annotations.csv` file, describing the meaning of the column names.
+
+- **`ReefNet_RSG-TestDataset_annotations.csv` (2.42 MB)**  
+  Contains the annotations of the Red Sea Global (RSG) test dataset, which is used in Experiment 2 of the main paper. This dataset was collected by Red Sea Global (RSG) in the Al-Wajh lagoon in the Red Sea (26.4°N, 36.4°E) in 2022 and was previously stored as a private source within CoralNet.
+
+- **`ReefNet_RSG-TestDataset_images.zip` (1.21 GB)**  
+  Contains the images from the Red Sea Global (RSG) test dataset. This dataset is used in Experiment 2 of the main paper as the test dataset and was collected by Red Sea Global (RSG) in the Al-Wajh lagoon in the Red Sea.
+
+- **`Metadata_ReefNet_by_CoralNet_sources.xlsx` (33 KB)**  
+  Provides an overview of the CoralNet sources from which the ReefNet dataset was compiled, including attribution to the original creators and metadata such as geographic location and average image resolution. The first sheet explains the content and column names of the other sheets.
+
+- **`ReefNet_labelmapping.xlsx` (79 KB)**  
+  Provides an overview of the label set mapping performed to consolidate the ReefNet dataset from the separate CoralNet sources. The first sheet provides metadata explaining the meaning of the content and column names of the other sheets.
+
+- **`ReefNet_RSG-TestDataset_labelmapping.xlsx` (33 KB)**  
+  Details the label set mapping performed for Experiment 2 in the main paper, merging labels from the main ReefNet dataset with the RSG-TestDataset. The first sheet explains the meaning of the content and column names of the other sheets.
+
+- **`sources_data.csv` (12.8 KB)**  
+  This file provides detailed information about all the sources used in the ReefNet dataset, including key metadata and URLs. The columns in this file include:
+  
+  - **Source**: The name of the source from CoralNet.
+  - **URL**: The direct link to the source on CoralNet.
+  - **ImagesURL**: The base URL structure for accessing the images associated with each source.
+  - **ImagesNumber**: The total number of images with confirmed annotations available for that source.
+  - **FirstImageNumber**: The starting index or identifier for the first image in the source.
+
+  This file is crucial for users who wish to download images directly from CoralNet using their own methods or with the provided script, ensuring that all images are correctly linked to their respective annotations.
+
+## Download Instructions
+
+### Hugging Face Files
+
+You can download the following files directly from Hugging Face:
+
 - `All_ReefNet_annotations.csv` (2.98 GB)
-  - Contains the all annotations available in the main ReefNet dataset, together with the associated metadata.
- 
 - `Metadata_All_ReefNet_annotations.xlsx` (11 KB)
-  - Contains metadata for the `All_ReefNet_annotations.csv` file describing the meaning of the column names.
-  
 - `ReefNet_RSG-TestDataset_annotations.csv` (2.42 MB)
-  - Contains the annotations of the Red Sea Global (RSG) test dataset. This newly released dataset is used in experiment 2 of the main paper as the test dataset.
-    This dataset was collected by Red Sea Global (RSG) in the Al-Wajh lagoon in the Red Sea (26.4°N, 36.4°E) in 2022 and was previously stored as a private source within CoralNet.
-  
 - `ReefNet_RSG-TestDataset_images.zip` (1.21 GB)
-  - Contains the annotations of the Red Sea Global (RSG) test dataset. This newly released dataset is used in experiment 2 of the main paper as the test dataset.
-    This dataset was collected by Red Sea Global (RSG) in the Al-Wajh lagoon in the Red Sea (26.4°N, 36.4°E) in 2022 and was previously stored as a private source within CoralNet.
-
 - `Metadata_ReefNet_by_CoralNet_sources.xlsx` (33 KB)
-  - Provides an overview of the CoralNet sources the ReefNet dataset was compiled from, including attribution to the original creators and metadata such as the Geographic location or average image resolution.
-    The first sheet of the file provides metadata explaining the meaning of the content and column names of the other sheets.
-  
 - `ReefNet_labelmapping.xlsx` (79 KB)
-  - Provides an overview of the labelset mapping that was performed to consolidate the ReefNet dataset from the separate CoralNet sources.
-    The first sheet of the file provides metadata explaining the meaning of the content and column names of the other sheets.
-    
 - `ReefNet_RSG-TestDataset_labelmapping.xlsx` (33 KB)
-  - Provides an overview of the labelset mapping that was performed for experiment 2 in the main paper to merge labels from the main ReefNet dataset to the RSG-TestDataset.
-    The first sheet of the file provides metadata explaining the meaning of the content and column names of the other sheets.
-    
-## Download Instructions
-
-### Hugging Face Files
 
-You can download the following files directly from Hugging Face:
+### Downloading Images and Annotations
 
-- `ReefNet_CN_annotations.csv`
-- `ReefNet_RSG_annotations.csv`
-- `Supplementary Materials 1 CoralNet sources used in ReefNet.xlsx`
-- `Supplementary Materials 2 ReefNet dataset structure.xlsx`
-- `Supplementary Materials 3 ReefNet Training and Validation data distribution.xlsx`
+To download the full set of images from CoralNet and the associated annotations, please use the download script provided in our GitHub repository. This script is designed to handle the specific structure of image storage on CoralNet and will automate the process for you.
 
-### Google Drive File
+You can find the script and detailed instructions in our GitHub repository here:
 
-Due to its size, the `ReefNet_CN_images.zip` file is hosted on Google Drive. You can download it using the following link:
+- **[ReefNet Image Download Script on GitHub](https://github.com/ReefNet-Project/coralnet_crawler)**
 
-[ReefNet_CN_images.zip](https://drive.google.com/file/d/1adETkbevDTDSCZEbmSNdwhzAM-4bp5IF/view?usp=sharing)
+Follow the instructions in the repository to download the images and annotations efficiently. The script ensures that all images are correctly organized and matched with the provided annotations.
 
 ## Usage
 
-To use this dataset, please ensure that you download all necessary files, including the images from Google Drive. The annotations are provided in CSV format, which can be easily read and processed using various data analysis tools and libraries.
+To use this dataset, please ensure that you download all necessary files, including the images from CoralNet. The annotations are provided in CSV format, which can be easily read and processed using various data analysis tools and libraries.
 
 <!-- ## Citation
 
 If you use this dataset in your research, please cite it as follows:
 
 @dataset{reefnet2024,
-author = {Your Name and Collaborators},
-title = {ReefNet: Annotated Coral Image Dataset for Machine Learning},
+author = {Yahia Battach, Brian Owain Nieuwenhuis, Xiang Li, et al.},
+title = {ReefNet: A Large-scale, Taxonomically Enriched Dataset and Benchmark for Coral Reef Classification},
 year = 2024,
 publisher = {Hugging Face},
-url = {https://huggingface.co/datasets/reefnet}
+url = {https://huggingface.co/datasets/ReefNet/ReefNet-1.0}
 } -->
 
-
 ## Contact
 
 For any questions or issues regarding the dataset, please contact: