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YOLO11-Pose

Object Detection
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YOLO11-POSE
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YOLO11-Pose
File size: 4,770 Bytes
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---
license: mit
language:
- en
base_model:
- Ultralytics/YOLO11
pipeline_tag: object-detection
tags:
- Ultralytics
- YOLO11
- YOLO11-POSE
---

# YOLO11-POSE

This version of YOLO11-POSE has been converted to run on the Axera NPU using **w8a16** quantization.

This model has been optimized with the following LoRA: 

Compatible with Pulsar2 version: 3.4

## Convert tools links:

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

- [The repo of ax-samples](https://github.com/AXERA-TECH/ax-samples), which you can get the how to build the `ax_yolo11_pose`

- [The repo of axcl-samples](https://github.com/AXERA-TECH/axcl-samples), which you can get the how to build the `axcl_yolo11_pose`

- [Pulsar2 Link, How to Convert ONNX to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html) 


## Support Platform

- AX650
  - [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
  - [M.2 Accelerator card](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html)
- AX630C
  - [爱芯派2](https://axera-pi-2-docs-cn.readthedocs.io/zh-cn/latest/index.html)
  - [Module-LLM](https://docs.m5stack.com/zh_CN/module/Module-LLM)
  - [LLM630 Compute Kit](https://docs.m5stack.com/zh_CN/core/LLM630%20Compute%20Kit)
  
|Chips|cost|
|--|--|
|AX650| 25 ms |
|AX630C| TBD ms |

## How to use

Download all files from this repository to the device

```
(axcl) axera@raspberrypi:~/samples/AXERA-TECH/YOLO11-Pose $ tree -L 2
.
β”œβ”€β”€ ax620e
β”‚Β Β  └── yolo11s-pose.axmodel
β”œβ”€β”€ ax650
β”‚Β Β  └── yolo11x-pose.axmodel
β”œβ”€β”€ ax_aarch64
β”‚Β Β  └── ax_yolo11_pose
β”œβ”€β”€ axcl_aarch64
β”‚Β Β  └── axcl_yolo11_pose
β”œβ”€β”€ axcl_x86_64
β”‚Β Β  └── axcl_yolo11_pose
β”œβ”€β”€ config.json
β”œβ”€β”€ football.jpg
β”œβ”€β”€ README.md
β”œβ”€β”€ yolo11_pose_config.json
β”œβ”€β”€ yolo11_pose_out.jpg
β”œβ”€β”€ yolo11s-pose-cut.onnx
└── yolo11s-pose.onnx

6 directories, 12 files
```

### Inference

Input image:
![](./football.jpg)

#### Inference with AX650 Host, such as M4N-Dock(爱芯派Pro)

```
root@ax650:~/YOLO11-Pose# ./ax_aarch64/ax_yolo11_pose -m ax650/yolo11x-pose.axmodel -i football.jpg
--------------------------------------
model file : ax650/yolo11x-pose.axmodel
image file : football.jpg
img_h, img_w : 640 640
--------------------------------------
Engine creating handle is done.
Engine creating context is done.
Engine get io info is done.
Engine alloc io is done.
Engine push input is done.
--------------------------------------
post process cost time:1.40 ms
--------------------------------------
Repeat 1 times, avg time 25.21 ms, max_time 25.21 ms, min_time 25.21 ms
--------------------------------------
detection num: 6
 0:  94%, [1350,  337, 1632, 1036], person
 0:  93%, [ 492,  477,  658, 1000], person
 0:  92%, [ 756,  219, 1126, 1154], person
 0:  91%, [   0,  354,  314, 1108], person
 0:  73%, [   0,  530,   81, 1017], person
 0:  54%, [ 142,  589,  239, 1013], person
--------------------------------------
```

Output image:
![](./yolo11_pose_out.jpg)

#### Inference with M.2 Accelerator card

```
(axcl) axera@raspberrypi:~/samples/AXERA-TECH/YOLO11-Pose $ chmod +x axcl_aarch64/axcl_yolo11_pose
(axcl) axera@raspberrypi:~/samples/AXERA-TECH/YOLO11-Pose $ ./axcl_aarch64/axcl_yolo11_pose -m ax650/yolo11x-pose.axmodel -i football.jpg
--------------------------------------
model file : ax650/yolo11x-pose.axmodel
image file : football.jpg
img_h, img_w : 640 640
--------------------------------------
axclrtEngineCreateContextt is done.
axclrtEngineGetIOInfo is done.

grpid: 0

input size: 1
    name:   images
        1 x 640 x 640 x 3


output size: 6
    name: /model.23/Concat_1_output_0
        1 x 80 x 80 x 65

    name: /model.23/Concat_2_output_0
        1 x 40 x 40 x 65

    name: /model.23/Concat_3_output_0
        1 x 20 x 20 x 65

    name: /model.23/cv4.0/cv4.0.2/Conv_output_0
        1 x 80 x 80 x 51

    name: /model.23/cv4.1/cv4.1.2/Conv_output_0
        1 x 40 x 40 x 51

    name: /model.23/cv4.2/cv4.2.2/Conv_output_0
        1 x 20 x 20 x 51

==================================================

Engine push input is done.
--------------------------------------
post process cost time:0.43 ms
--------------------------------------
Repeat 1 times, avg time 25.05 ms, max_time 25.05 ms, min_time 25.05 ms
--------------------------------------
detection num: 6
 0:  94%, [1350,  337, 1632, 1036], person
 0:  93%, [ 492,  477,  658, 1000], person
 0:  92%, [ 756,  219, 1126, 1154], person
 0:  91%, [   0,  354,  314, 1108], person
 0:  73%, [   0,  530,   81, 1017], person
 0:  54%, [ 142,  589,  239, 1013], person
--------------------------------------
```