Update README.md

README.md

@@ -1,32 +1,35 @@
 ---
 license: mit
 tags:
-- YOLO
-- YOLOv11
-- license-plate
-- brazil
-- computer-vision
-- OCR
-- automatic-license-plate-recognition
+  - YOLO
+  - YOLOv11
+  - license-plate
+  - brazil
+  - computer-vision
+  - OCR
+  - automatic-license-plate-recognition
 ---
+
 ![YOLOv11](https://img.shields.io/badge/YOLO-v11-blue)
 ![Brazil Plates](https://img.shields.io/badge/Plates-Brazil-green)
 ![License](https://img.shields.io/badge/License-MIT-orange)
 ![Hugging Face](https://img.shields.io/badge/🤗%20Hugging%20Face-Model-yellow)
 
-**Felipe Dutra** 🇧🇷  
+## 👨‍💻 Author
+**Felipe Dutrain de Sales** 🇧🇷  
 Machine Learning & Computer Vision Developer  
-Hugging Face: https://huggingface.co/felipedutrain  
-GitHub: [FelipeSales18](https://github.com/FelipeSales18)
+🤗 Hugging Face: https://huggingface.co/felipedutrain  
+🐙 GitHub: https://github.com/FelipeSales18  
 
+---
 
 # 🇧🇷 Brazilian License Plate Detector — YOLOv11 (Mercosul + Legacy)
 
 ## 🚘 About the Model
 This model is trained to detect **Brazilian vehicle license plates**, including:
 
-✅ MERCOSUL format (ABC1D23)  
-✅ Legacy format (ABC-1234)
+✅ **MERCOSUL format** (ABC1D23)  
+✅ **Legacy format** (ABC-1234)
 
 It was trained using **YOLOv11 (Ultralytics)** and returns bounding boxes for license plates in images and videos.
 
@@ -40,7 +43,7 @@ It was trained using **YOLOv11 (Ultralytics)** and returns bounding boxes for li
 
 ## ⚡ Quick Inference
 
-### Python
+### ✅ Python
 ```python
 from ultralytics import YOLO