AXERA-TECH/superpoint
By AXERA-TECH · ↓ 7 · ♥ 0 · Updated 2025-12-29
What's in this repo
This page lists the files in AXERA-TECH/superpoint, including superpoint_no_borders.onnx.
- 1 ONNX models (.onnx files)
- 12 files, including 2 .ppm, 2 .axmodel, 1 .md, 1 .tar, 1 .json, 1 .py
- Last updated 2025-12-29
ONNX files
| File | Size | Download |
|---|---|---|
| superpoint_no_borders.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
SuperPoint
This repository contains the SuperPoint model converted to run on the Axera NPU. SuperPoint is a self-supervised framework for training interest point detectors and descriptors, suitable for a large number of multiple-view geometry problems in computer vision.
This version has been quantized using w8a16 and is optimized for use with Pulsar2 (version 4.2).
Convert Tools Links
For developers interested in custom model conversion or optimization:
- AXera Platform GitHub Repo: Comprehensive guides and sample code for AXera chips.
- Pulsar2 Documentation: Official guide on converting ONNX models to
.axmodel.
Supported Platforms
- AX650
- AX637
| Chips | SuperPoint (640x480) |
|---|---|
| AX650 | 27.443 ms |
| AX637 | 96.118 ms |
How to Use
Download the model files and the inference binary to your Axera-powered device:
root@ax650:~/SuperPoint-Demo# tree
.
|-- ax650
| `-- compiled.axmodel
|-- infer.py
|-- 1.ppm
|-- 2.ppm
`-- output.jpg
Inference
python3 infer.py --model ./ax650/compiled.axmodel --img1 1.ppm --img2 2.ppm --output output.jpg
Output image
Model info
Created: 2025-12-29
Updated: 2025-12-29
View on Hugging Face