Vision Models
Collection
Common computer vision class models, such as the YOLO family
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21 items
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Updated
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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).
For developers interested in custom model conversion or optimization:
.axmodel.| Chips | SuperPoint (640x480) |
|---|---|
| AX650 | 27.443 ms |
| AX637 | 96.118 ms |
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
python3 infer.py --model ./ax650/compiled.axmodel --img1 1.ppm --img2 2.ppm --output output.jpg
Base model
magic-leap-community/superpoint