---
license: bsd-3-clause
language:
- en

pipeline_tag: depth-estimation  
tags:
- IGEV++
---

# IGEV++   

This version of RT IGEV 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/gangweiX/IGEV-plusplus)

- [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)
- AX8850
  - [M.2 Accelerator card](https://docs.m5stack.com/en/ai_hardware/LLM-8850_Card)
 
|Chips|Models |Time|
|--|--|--|
|AX650|rt_sceneflow|142.0 ms |
|AX637|rt_sceneflow(分成三段 rt_p1 + rt_iterfn + rt_up)|123.0 + 29.3*18 + 9.1 = 659.5 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_ax.py
```

Output image:  
ONNX result  
![](ONNX-Disparity-Map-rt.png)

AXmodel result  
![](AXModel-Disparity-Map-rt.png)