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README.md

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+# YOLOv12-N
+
+## Model Description
+**YOLOv12-N** is a variant of the 12th-generation YOLO (You Only Look Once) real-time object detector.  
+It builds on prior YOLO models with improved backbone/neck architectures, updated training strategies, and optimizations for both high-performance GPUs and edge devices.
+
+## Features
+- **Real-time object detection** optimized for low-latency inference.
+- **High accuracy** across diverse categories and challenging environments.
+- **Lightweight variants** suitable for mobile and embedded deployment.
+- **Scalable**: runs from smartphones to multi-GPU servers.
+- **Extensible**: fine-tuning supported for domain-specific datasets.
+
+## Use Cases
+- Autonomous driving and ADAS (Advanced Driver Assistance Systems)
+- Surveillance and security monitoring
+- Industrial automation and defect detection
+- Retail analytics and inventory monitoring
+- Sports analytics and event detection
+
+## Inputs and Outputs
+**Input**:
+- RGB images or video frames (any resolution; auto-resized during preprocessing).
+
+**Output**:
+- Bounding boxes `(x, y, w, h)`
+- Class labels
+- Confidence scores
+
+## License
+- Licensed under [AGPL-3.0](https://github.com/ultralytics/ultralytics?tab=AGPL-3.0-1-ov-file#readme) (same as Ultralytics YOLO).
+
+## References
+- Original repo: [https://github.com/sunsmarterjie/yolov12](https://github.com/sunsmarterjie/yolov12)
+- Ultralytics YOLO family: [https://github.com/ultralytics/ultralytics](https://github.com/ultralytics/ultralytics)