---
license: agpl-3.0
language:
- en
base_model:
- YOLO11
pipeline_tag: object-detection
tags:
- Axera
- YOLO11-OBB
- NPU
- Ultralytics
- Oriented Object Detection
- Rotated Bounding Box
---

# YOLO11-OBB

This version of **YOLO11-OBB** (Oriented Bounding Box) has been converted to run on the Axera NPU using **w8a16** quantization. It is optimized for detecting rotated objects such as ships, harbors, vehicles, and other DOTA-style targets with oriented bounding boxes.

Compatible with Pulsar2 version: 6.0.

## Convert tools links

For those who are interested in model conversion, you can try to export axmodel through:

- [The repo of AXera Platform](https://github.com/AXERA-TECH/ax-samples), where you can get the detailed guide.
- [Pulsar2 Link, How to Convert ONNX to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html)

## Support Platform

This repository currently provides axmodels for the following Axera platforms only:

- **AX650N/AX8850**
  - [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
  - [M.2 Accelerator card](https://docs.m5stack.com/en/ai_hardware/LLM-8850_Card)
- **AX637**

## Model files

The converted axmodels are organized by target platform:

```text
yolo11_obb/
├── 650/
│   ├── yolo11n-obb_640x640_npu1.axmodel
│   ├── yolo11n-obb_640x640_npu3.axmodel
│   ├── yolo11s-obb_640x640_npu1.axmodel
│   ├── yolo11s-obb_640x640_npu3.axmodel
│   ├── yolo11m-obb_640x640_npu1.axmodel
│   ├── yolo11m-obb_640x640_npu3.axmodel
│   ├── yolo11l-obb_640x640_npu1.axmodel
│   ├── yolo11l-obb_640x640_npu3.axmodel
│   ├── yolo11x-obb_640x640_npu1.axmodel
│   └── yolo11x-obb_640x640_npu3.axmodel
├── 637/
│   ├── yolo11n-obb_640x640_npu1.axmodel
│   ├── yolo11s-obb_640x640_npu1.axmodel
│   ├── yolo11m-obb_640x640_npu1.axmodel
│   ├── yolo11l-obb_640x640_npu1.axmodel
│   └── yolo11x-obb_640x640_npu1.axmodel
├── ax_infer.py
├── boats.jpg
└── result_yolo11_obb_ax.jpg
```

## Performance Statistics

Latency data is left blank and can be filled in after benchmark testing.

### AX650N/AX8850

| Model | Latency(ms) npu1 | Latency(ms) npu3 |
| :--- | :---: | :---: |
| **yolo11n-obb** | 3.491 | 1.383 |
| **yolo11s-obb** | 9.008 | 3.240 |
| **yolo11m-obb** | 26.086 | 8.958 |
| **yolo11l-obb** | 33.724 | 11.496 |
| **yolo11x-obb** | 73.796 | 25.168 |

### AX637

| Model | Latency(ms) |
| :--- | :---: |
| **yolo11n-obb** | 4.191 |
| **yolo11s-obb** | 11.068 |
| **yolo11m-obb** | 27.316 |
| **yolo11l-obb** | 35.625 |
| **yolo11x-obb** | 79.141 |

## How to use

Download all files from this repository to the device, then choose the axmodel that matches your target platform.

### Python env requirement

#### pyaxengine

https://github.com/AXERA-TECH/pyaxengine

```bash
wget https://github.com/AXERA-TECH/pyaxengine/releases/download/0.1.3.rc2/axengine-0.1.3-py3-none-any.whl
pip install axengine-0.1.3-py3-none-any.whl
```

### Inference on board

Input image:

![](boats.jpg)

Run with an AX650N/AX8850 model:

```bash
python3 ax_infer.py -m 650/yolo11m-obb_640x640_npu3.axmodel -i boats.jpg
```

Run with an AX637 model:

```bash
python3 ax_infer.py -m 637/yolo11m-obb_640x640_npu1.axmodel -i boats.jpg
```

Example output from AX637:

```bash
root@ax637:~/11obb# python3 ax_infer.py -m yolo11m-obb_640x640_npu3.axmodel -i boats.jpg
[INFO] Available providers:  ['AxEngineExecutionProvider']
[INFO] Using provider: AxEngineExecutionProvider
[INFO] Chip type: ChipType.M57H
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Engine version: 2.12.0s
[INFO] Model type: 0 (single core)
[INFO] Compiler version: 6.0 93b95f7f
Load model: 844.4 ms
Forward+post: 194.9 ms
Found 167 oriented objects.
  ship                 conf=0.84 cx=1707.6 cy=792.9 w=105.7 h=34.9 theta=+26.0
  ship                 conf=0.84 cx=1790.4 cy=573.8 w=117.8 h=36.5 theta=+24.5
  ship                 conf=0.84 cx=1723.6 cy=760.6 w=108.8 h=31.4 theta=+24.5
  ship                 conf=0.84 cx=1782.8 cy=620.8 w=112.0 h=35.7 theta=+25.0
  ship                 conf=0.82 cx=1487.2 cy=694.4 w=97.2 h=31.3 theta=+21.0
  ...
  harbor               conf=0.29 cx=824.3 cy=184.2 w=230.5 h=521.3 theta=+24.0
  ship                 conf=0.29 cx=1219.5 cy=246.9 w=85.7 h=24.0 theta=+23.0
  ship                 conf=0.29 cx=1652.9 cy=276.2 w=80.3 h=26.1 theta=+20.5
  ship                 conf=0.29 cx=1190.1 cy=307.0 w=91.3 h=28.6 theta=+21.0
  harbor               conf=0.27 cx=1535.8 cy=388.2 w=221.8 h=953.5 theta=+20.5
  ship                 conf=0.26 cx=1517.0 cy=274.2 w=84.8 h=24.2 theta=+21.5
  ship                 conf=0.26 cx=1522.8 cy=252.3 w=89.5 h=29.9 theta=+19.5
Saved: result_yolo11_obb_ax.jpg
```

Output image:

![](result_yolo11_obb_ax.jpg)