| # 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) |