Update README.md

README.md

@@ -8,14 +8,20 @@ pretty_name: CSIRO Crown-of-Thorns Starfish (COTS) Detection Dataset — YOLO Fo
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-# CSIRO Crown-of-Thorns Starfish (COTS) Detection Dataset — YOLO Format
+# 🪸 CSIRO Crown-of-Thorns Starfish (COTS) Detection Dataset — YOLO Format 
+
+[![Hugging Face Spaces](https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/eloise54/cots_detection_project)
 
 This dataset is a **modified version** of the [CSIRO COTS and COTS Scars Dataset](https://data.csiro.au/collection/csiro:64235), originally released under the [Creative Commons Attribution 4.0 License (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/).
 
+The original dataset contains images and annotations for **Crown-of-Thorns Starfish (COTS)** and **COTS scars**, collected to support coral reef monitoring and control efforts on the Great Barrier Reef (GBR). 
+
+These starfish are coral predators, and their outbreaks can severely damage reef ecosystems.
+
 >**Please cite the original dataset authors if you use this dataset in your work.**
 
 
-## 🙏 Citation
+# 🙏 Citation
 
 ```bibtex
 @dataset{csiro_cots_2024,
@@ -29,18 +35,42 @@ This dataset is a **modified version** of the [CSIRO COTS and COTS Scars Dataset
 }
 ```
 
-# 🪸 About the Dataset
+# 🔧 How to use this dataset ?
+
+#### Training
+
+```
+git clone https://huggingface.co/datasets/eloise54/cots_yolo_dataset
+pip install ultralytics
+```
+
+In a python file:
+
+```
+from ultralytics import YOLO
+
+# Dowload pretrained model
+import urllib.request
+url = 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11m.pt'
+urllib.request.urlretrieve(url, 'yolo11m.pt')
+
+# Load a pretrain model
+model = YOLO('yolo11m.pt')
+results = model.train(data='data/cots_yolo_dataset/cots_yolo_dataset.yaml', epochs=20, task='detect')
+```
+
+Example of inference without downloading everything : [notebook link](https://gitlab.com/robotics2ai/cots_detection_project/-/blob/main/yolo_predict_and_display.ipynb?ref_type=heads)
 
-The original dataset contains images and annotations for **Crown-of-Thorns Starfish (COTS)** and **COTS scars**, collected to support coral reef monitoring and control efforts on the Great Barrier Reef (GBR). These starfish are coral predators, and their outbreaks can severely damage reef ecosystems.
 
 
-# Example of use with finetuned yolo11m  
+# 🤗 Example of use with finetuned yolo11m  
 
-⚡ Demo on Hugging Face Spaces:
+Demo on Hugging Face Spaces:
 
 [![Hugging Face Spaces](https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/eloise54/cots_detection_project)
 
-Gitlab repository containing full training pipeline:
+Gitlab repository containing full training pipeline: 
+
 * original [CSIRO COTS and COTS Scars Dataset](https://data.csiro.au/collection/csiro:64235) download
 * modifications done to make this current dataset
 * yolov11m finetuning
@@ -50,8 +80,7 @@ Gitlab repository containing full training pipeline:
 
 
 
-
-## 🔧 Modifications
+# 🔧 Modifications
 
 Here is the list of the modification made on the original [CSIRO COTS and COTS Scars Dataset](https://data.csiro.au/collection/csiro:64235):
 
@@ -74,32 +103,6 @@ cots_yolo_dataset/
 └── cots_yolo_dataset.yaml
 ```
 
-## How to use this dataset ?
-
-### Training
-
-```
-git clone https://huggingface.co/datasets/eloise54/cots_yolo_dataset
-pip install ultralytics
-```
-
-In a python file:
-
-```
-from ultralytics import YOLO
-
-# Dowload pretrained model
-import urllib.request
-url = 'https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo11m.pt'
-urllib.request.urlretrieve(url, 'yolo11m.pt')
-
-# Load a pretrain model
-model = YOLO('yolo11m.pt')
-results = model.train(data='data/cots_yolo_dataset/cots_yolo_dataset.yaml', epochs=20, task='detect')
-```
-
-### Inference without downloading everything
 
-[notebook link](https://gitlab.com/robotics2ai/cots_detection_project/-/blob/main/yolo_predict_and_display.ipynb?ref_type=heads)