---
license: bsd-3-clause
language:
- en
base_model:
- deeplabv3plus_mobilenet
pipeline_tag: image-segmentation
tags:
- deeplabv3plus
---

# DeepLabv3Plus   

This version of deeplabv3plus_mobilenet has been converted to run on the Axera NPU using **w8a16** quantization.

Compatible with Pulsar2 version: 5.0-patch1

## Convert tools links:

For those who are interested in model conversion, you can try to export axmodel through 

- [The repo of original](https://github.com/VainF/DeepLabV3Plus-Pytorch.git)

- [Pulsar2 Link, How to Convert ONNX to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html) 


## Support Platform

- AX650
  - [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
  - [M.2 Accelerator card](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html)
- AX637
 
|Chips|Models |Time|
|--|--|--|
|AX650|deeplabv3plus_mobilenet_u16|13.4 ms |
|AX637|deeplabv3plus_mobilenet_u16|39.4 ms |


## 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:

![](samples/1_image.png)

run 
```
python3 infer.py --img samples/1_image.png --model models-ax637/deeplabv3plus_mobilenet_u16.axmodel
```

Output image:

![](output-ax.png)