Update README.md

README.md

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 ---
 title: YOLOv8m Defence
-emoji: 🌍
-colorFrom: pink
-colorTo: pink
+emoji: 🛡️
+colorFrom: red
+colorTo: yellow
 sdk: gradio
 sdk_version: 5.34.2
 app_file: app.py
 pinned: false
 license: apache-2.0
-short_description: Deployment of the spencercdz/YOLOv8m_defence model.
+short_description: YOLOv8m object detection for defense and security.
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# YOLOv8m Defence
+
+This Space demonstrates the **YOLOv8m Defence** model for real-time object detection in defense and security applications.
+
+## Model Information
+
+- **Model**: [spencercdz/YOLOv8m_defence](https://huggingface.co/spencercdz/YOLOv8m_defence)
+- **Architecture**: YOLOv8 Medium (YOLOv8m)
+- **Framework**: Ultralytics YOLOv8
+- **License**: Apache 2.0
+
+## Features
+
+- Real-time object detection and classification
+- Optimized for defense and security scenarios
+- Support for image and video inputs
+- Interactive web interface powered by Gradio
+
+## Usage
+
+1. Upload an image
+2. The model will automatically detect and classify objects
+3. View results with bounding boxes and confidence scores
+4. Download processed outputs if needed
+
+## Model Performance
+
+The YOLOv8m architecture provides an excellent balance between speed and accuracy, making it suitable for real-time applications while maintaining high detection performance.
+
+## Technical Details
+
+- **Input**: Images
+- **Output**: Annotated images with detected objects
+- **Processing**: GPU-accelerated inference when available
+
+## Contact
+
+For questions or issues, please open a discussion in the Community tab or contact the model author.