|
|
--- |
|
|
license: mit |
|
|
language: |
|
|
- en |
|
|
base_model: |
|
|
- magic-leap-community/superpoint |
|
|
pipeline_tag: image-feature-extraction |
|
|
tags: |
|
|
- Axera |
|
|
- NPU |
|
|
- Pulsar2 |
|
|
- SuperPoint |
|
|
- Computer-Vision |
|
|
--- |
|
|
|
|
|
# SuperPoint |
|
|
|
|
|
This repository contains the **[SuperPoint](https://arxiv.org/abs/1712.07629)** 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](https://github.com/AXERA-TECH/ax-samples): Comprehensive guides and sample code for AXera chips. |
|
|
- [Pulsar2 Documentation](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html): 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: |
|
|
|
|
|
```bash |
|
|
root@ax650:~/SuperPoint-Demo# tree |
|
|
. |
|
|
|-- ax650 |
|
|
| `-- compiled.axmodel |
|
|
|-- infer.py |
|
|
|-- 1.ppm |
|
|
|-- 2.ppm |
|
|
`-- output.jpg |
|
|
``` |
|
|
# Inference |
|
|
|
|
|
```bash |
|
|
python3 infer.py --model ./ax650/compiled.axmodel --img1 1.ppm --img2 2.ppm --output output.jpg |
|
|
``` |
|
|
|
|
|
## Output image |
|
|
 |
