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 AXera Platform, which you can get the detial of guide

• Pulsar2 Link, How to Convert ONNX to axmodel

Support Platform

• AX650
  • M4N-Dock(爱芯派Pro)
  • M.2 Accelerator card
• AX630C
  • 爱芯派2
  • Module-LLM
  • LLM630 Compute Kit

Chips	cost
AX650	25 ms
AX630C	TBD ms

How to use

Download all files from this repository to the device

root@ax650:~/YOLO11-Pose# tree
.
|-- ax650
|   `-- yolo11x-pose.axmodel
|-- ax_yolo11_pose
|-- football.jpg
`-- yolo11_pose_out.jpg

Inference

Input image:

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

root@ax650:~/YOLO11-Pose# ./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: