Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+language:
+- en
+- tr
+tags:
+- traffic
+- sign
+- trafficsign
+- detection
+- yolo8
+- object
+- recognition
+---
+# 🚦 Traffic Sign Recognition ML Model (YOLOv8)
+
+## 🧠 Model Summary
+
+This machine learning model is developed to **detect and classify traffic signs** using the **YOLOv8 (You Only Look Once v8)** object detection architecture. Trained on a dataset containing over **30,000 labeled images of traffic signs**, this model can accurately identify a wide variety of road signs for use in autonomous driving, smart city solutions, and advanced driver-assistance systems (ADAS).
+
+- **Architecture**: YOLOv8
+- **Task**: Object Detection & Multi-class Classification
+- **Dataset**: 30,000+ labeled traffic sign images
+- **Fine-tunable**: ✅ Yes
+- **License**: MIT
+
+---
+
+## 🚀 Usage Example
+
+```python
+from ultralytics import YOLO
+
+# Load the trained YOLOv8 model
+model = YOLO("path/to/best.pt")  # Replace with actual model path
+
+# Run inference on a test image
+results = model("path/to/traffic_image.jpg")
+
+# Visualize results
+results.show()
+
+# Access predictions
+for r in results:
+    boxes = r.boxes
+    for box in boxes:
+        print(f"Class: {int(box.cls[0])}, Confidence: {box.conf[0]:.2f}")