# 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

---

## How to use

> ⚠️ **Hardware requirement:** the model currently runs **only on Qualcomm NPUs** (e.g., Snapdragon-powered AIPC).  
> Apple NPU support is planned next.

### 1) Install Nexa-SDK

- Download and follow the steps under "Deploy Section" Nexa's model page:  [Download Windows arm64 SDK](https://sdk.nexa.ai/model/YOLOv12%E2%80%91N)
- (Other platforms coming soon)

### 2) Get an access token
Create a token in the Model Hub, then log in:

```bash
nexa config set license '<access_token>'
```

### 3) Run the model
Running:

```bash
nexa infer NexaAI/yolov12-npu
```

---

## 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)