metadata
license: mit
language:
- en
base_model:
- Ultralytics/YOLO11
pipeline_tag: object-detection
tags:
- Ultralytics
- YOLO11
YOLO11
This version of YOLO11 has been converted to run on the WaveMatrix 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, which you can get the how to build the
ax_yolo11The repo of axcl-samples, which you can get the how to build the
axcl_yolo11
Support Platform
- WM9955
- Demo board
- M.2 Accelerator card
| Chips | cost |
|---|---|
| WM9955 | 25 ms |
How to use
Download all files from this repository to the device
(axcl) wavematrix@raspberrypi:~/samples/WaveMatrix/YOLO11 $ tree -L 2
.
├── wm9955
│ ├── yolo11s.axmodel
│ └── yolo11x.axmodel
├── ax_aarch64
│ └── ax_yolo11
├── axcl_aarch64
│ └── axcl_yolo11
├── axcl_x86_64
│ └── axcl_yolo11
├── config.json
├── cut-onnx.py
├── football.jpg
├── README.md
├── ssd_horse.jpg
├── yolo11_config.json
├── yolo11_out.jpg
├── yolo11s-cut.onnx
└── yolo11-test.py
6 directories, 15 files
Inference
Input image:
Inference with WM9955 Host, such as demo board
root@wm9955:~/samples/WaveMatrix/YOLO11# ./ax_aarch64/ax_yolo11 -m wm9955/yolo11x.axmodel -i football.jpg
--------------------------------------
model file : wm9955/yolo11x.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:4.20 ms
--------------------------------------
Repeat 1 times, avg time 24.56 ms, max_time 24.56 ms, min_time 24.56 ms
--------------------------------------
detection num: 9
0: 94%, [ 757, 220, 1127, 1154], person
0: 94%, [ 0, 357, 314, 1112], person
0: 93%, [1353, 339, 1629, 1037], person
0: 91%, [ 494, 476, 659, 1001], person
32: 86%, [1231, 877, 1281, 922], sports ball
32: 73%, [ 774, 887, 828, 938], sports ball
32: 66%, [1012, 882, 1051, 927], sports ball
0: 54%, [ 0, 543, 83, 1000], person
0: 46%, [1837, 696, 1877, 814], person
--------------------------------------
Output image:
Inference with M.2 Accelerator card
(axcl) wavematrix@raspberrypi:~/samples/WaveMatrix/YOLO11 $ ./axcl_aarch64/axcl_yolo11 -m wm9955/yolo11x.axmodel -i football.jpg
--------------------------------------
model file : wm9955/yolo11x.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.23/Concat_output_0
1 x 80 x 80 x 144
name: /model.23/Concat_1_output_0
1 x 40 x 40 x 144
name: /model.23/Concat_2_output_0
1 x 20 x 20 x 144
==================================================
Engine push input is done.
--------------------------------------
post process cost time:1.38 ms
--------------------------------------
Repeat 1 times, avg time 24.73 ms, max_time 24.73 ms, min_time 24.73 ms
--------------------------------------
detection num: 9
0: 94%, [ 757, 220, 1127, 1154], person
0: 94%, [ 0, 357, 314, 1112], person
0: 93%, [1353, 339, 1629, 1037], person
0: 91%, [ 494, 476, 659, 1001], person
32: 86%, [1231, 877, 1281, 922], sports ball
32: 73%, [ 774, 887, 828, 938], sports ball
32: 66%, [1012, 882, 1051, 927], sports ball
0: 54%, [ 0, 543, 83, 1000], person
0: 46%, [1837, 696, 1877, 814], person
--------------------------------------