AXERA-TECH/yolo26-pose
By AXERA-TECH · ↓ 1 · ♥ 0 · Updated 2026-01-26
What's in this repo
This page lists the files in AXERA-TECH/yolo26-pose, including yolo26l-pose_640x640.onnx, yolo26m-pose_640x640.onnx, yolo26n-pose_640x640.onnx and more.
- 5 ONNX models (.onnx files)
- 34 files, including 20 .axmodel, 5 .onnx, 3 .py, 2 .jpg, 1 .md, 1 .tar
- Last updated 2026-01-26
ONNX files
| File | Size | Download |
|---|---|---|
| yolo26l-pose_640x640.onnx | — | Download |
| yolo26m-pose_640x640.onnx | — | Download |
| yolo26n-pose_640x640.onnx | — | Download |
| yolo26s-pose_640x640.onnx | — | Download |
| yolo26x-pose_640x640.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
YOLO26-Pose
This version of YOLOv26-Pose has been converted to run on the Axera NPU using w8a16 quantization.
Compatible with Pulsar2 version: 4.2.
Convert tools links:
For those who are interested in model conversion, you can try to export axmodel through:
- The repo of AXera Platform, where you can get the detailed guide.
- Pulsar2 Link, How to Convert ONNX to axmodel
Support Platform
- AX650N/AX8850
- AX630C
- AX615
- AX637
Performance Statistics
AX650N(NPU1)
| Model | FPS | CMM(MB) | Latency(ms) |
|---|---|---|---|
| yolo26n-pose | 240.21 | 5.71 | 4.163 |
| yolo26s-pose | 99.30 | 17.90 | 10.070 |
| yolo26m-pose | 36.96 | 37.82 | 27.053 |
| yolo26l-pose | 28.88 | 39.25 | 34.620 |
| yolo26x-pose | 13.50 | 79.61 | 74.072 |
AX650N(NPU3)
| Model | FPS | CMM(MB) | Latency(ms) |
|---|---|---|---|
| yolo26n-pose | 655.74 | 3.80 | 1.525 |
| yolo26s-pose | 283.45 | 11.27 | 3.528 |
| yolo26m-pose | 107.57 | 28.98 | 9.296 |
| yolo26l-pose | 83.59 | 35.22 | 11.963 |
| yolo26x-pose | 39.80 | 72.24 | 25.128 |
AX630C
| Model | Latency(ms) npu1 | Latency(ms) npu2 |
|---|---|---|
| yolo26n-pose | 11.003 | 7.203 |
| yolo26s-pose | 24.157 | 17.120 |
AX615
| Model | Latency(ms) npu1 | Latency(ms) npu2 |
|---|---|---|
| yolo26n-pose | 19.542 | 11.446 |
| yolo26s-pose | 57.481 | 28.553 |
AX637
| Model | Latency(ms) |
|---|---|
| yolo26n-pose | 4.595 |
| yolo26s-pose | 11.848 |
How to use
Download all files from this repository to the device
python env requirement
pyaxengine
https://github.com/AXERA-TECH/pyaxengine
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
others
Maybe None.
Inference with AX650 Host, such as M4N-Dock(爱芯派Pro)
Input image:
run
python ax_infer_pose.py --model-path yolo26l-pose_npu3.axmodel --test-img bus.jpg
(ax_env) root@ax650:~/ax650# python ax_infer.py --model-path yolo26l-pose_npu3.axmodel --test-img bus.jpg
[INFO] Available providers: ['AxEngineExecutionProvider']
[INFO] Using provider: AxEngineExecutionProvider
[INFO] Chip type: ChipType.MC50
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Engine version: 2.12.0s
[INFO] Model type: 2 (triple core)
[INFO] Compiler version: 5.1-patch1-dirty 9164b433-dirty
[YOLO26-Pose] [16:47:23.013] [DEBUG] Load model time = 838.91 ms
[YOLO26-Pose] [16:47:23.070] [DEBUG] Pre-process time = 16.87 ms
[YOLO26-Pose] [16:47:23.109] [DEBUG] Forward time = 39.14 ms
[YOLO26-Pose] [16:47:23.113] [DEBUG] Post-process time = 2.97 ms
[YOLO26-Pose] [16:47:23.117] [INFO] Draw Results (4 persons):
[YOLO26-Pose] [16:47:23.117] [INFO] (221, 406, 345, 859) -> person: 0.92
[YOLO26-Pose] [16:47:23.120] [INFO] (668, 391, 807, 880) -> person: 0.92
[YOLO26-Pose] [16:47:23.122] [INFO] (47, 397, 243, 901) -> person: 0.90
[YOLO26-Pose] [16:47:23.123] [INFO] (0, 439, 78, 949) -> person: 0.69
[YOLO26-Pose] [16:47:23.151] [INFO] Saved to result_yolo26_pose.jpg
Output image:
Model info
Created: 2026-01-20
Updated: 2026-01-26
View on Hugging Face