YOLOv8

This version of YOLOv8 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	yolov8s
AX650	3.6 ms
AX630C	TBD ms

How to use

Download all files from this repository to the device

root@ax650:~/YOLO11-Pose# tree
.
|-- ax650
|   `-- yolov8s.axmodel
|-- ax_yolov8
|-- football.jpg
`-- yolov8_out.jpg

Inference

Input image:

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

root@ax650:~/samples/AXERA-TECH/YOLOv8# ./ax_yolov8 -m ax650/yolov8s.axmodel -i football.jpg
--------------------------------------
model file : ax650/yolov8s.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:3.96 ms
--------------------------------------
Repeat 1 times, avg time 3.64 ms, max_time 3.64 ms, min_time 3.64 ms
--------------------------------------
detection num: 7
 0:  93%, [ 757,  215, 1131, 1156], person
 0:  93%, [   0,  354,  311, 1104], person
 0:  93%, [1351,  342, 1627, 1032], person
 0:  91%, [ 488,  478,  661,  998], person
32:  87%, [ 773,  889,  829,  939], sports ball
32:  77%, [1231,  876, 1280,  922], sports ball
 0:  60%, [1840,  690, 1906,  809], person
--------------------------------------

Output image:

Inference with M.2 Accelerator card

(base) axera@raspberrypi:~/lhj/YOLOv8 $ ./axcl_aarch64/axcl_yolov8 -m ax650/yolov8s.axmodel -i football.jpg 
--------------------------------------
model file : ax650/yolov8s.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: 3
    name: /model.22/Concat_output_0 
        1 x 80 x 80 x 144

    name: /model.22/Concat_1_output_0 
        1 x 40 x 40 x 144

    name: /model.22/Concat_2_output_0 
        1 x 20 x 20 x 144

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

Engine push input is done. 
--------------------------------------
post process cost time:0.98 ms 
--------------------------------------
Repeat 1 times, avg time 3.75 ms, max_time 3.75 ms, min_time 3.75 ms
--------------------------------------
detection num: 7
 0:  93%, [ 757,  215, 1131, 1156], person
 0:  93%, [   0,  354,  311, 1104], person
 0:  93%, [1351,  342, 1627, 1032], person
 0:  91%, [ 488,  478,  661,  998], person
32:  87%, [ 773,  889,  829,  939], sports ball
32:  77%, [1231,  876, 1280,  922], sports ball
 0:  60%, [1840,  690, 1906,  809], person
--------------------------------------

Output image: