Package-axera / README.md
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---
license: agpl-3.0
language:
- en
pipeline_tag: object-detection
tags:
- Axera
- NPU
- Object Detection
---
# Axera-Package
This version of **Axera-Package** has been converted to run on the Axera NPU using **w8a16** quantization. It is mainly used for package detection in conventional scenarios.
## Supported Classes
This model is trained to detect the following **2 classes**:
1. **package**
2. **package-bag**
Compatible with Pulsar2 version: 5.0.
## Convert tools links:
For those who are interested in model conversion, you can try to export axmodel through:
- [The repo of AXera Platform](https://github.com/AXERA-TECH/ax-samples), where you can get the detailed guide.
- [Pulsar2 Link, How to Convert ONNX to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html)
## Support Platform
https://docs.m5stack.com/zh_CN/ai_hardware/AI_Pyramid-Pro
- **AX650N/AX8850**
- [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
- [AI Pyramid](https://docs.m5stack.com/zh_CN/ai_hardware/AI_Pyramid-Pro)
- [M.2 Accelerator card](https://docs.m5stack.com/en/ai_hardware/LLM-8850_Card)
- **AX620E**
- [爱芯派2](https://axera-pi-2-docs-cn.readthedocs.io/zh-cn/latest/index.html)
- [Module-LLM](https://docs.m5stack.com/zh_CN/module/Module-LLM)
## How to use
Download all files from this repository to the device.
### python env requirement
#### pyaxengine
https://github.com/AXERA-TECH/pyaxengine
```bash
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
```
### Inference with AX650 Host, such as M4N-Dock(爱芯派Pro)
Input image:
![](package.jpg)
run
```bash
python3 ax_pkg_infer.py --model ./AX650/ax_ax650_package_algo_model_V2.0.0.axmodel --img package.jpg
```
```bash
root@ax650:~/pkg# python3 ax_pkg_infer.py --model ./AX650/ax_ax650_package_algo_model_V2.0.0.axmodel --img package.jpg
[INFO] Available providers: ['AxEngineExecutionProvider']
[INFO] Using provider: AxEngineExecutionProvider
[INFO] Chip type: ChipType.MC50
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Engine version: 2.10.1s
[INFO] Model type: 2 (triple core)
[INFO] Compiler version: 6.0 79a1e641
Input_name: images, Output_name: ['output0', 'output1']
Preprocess time: 7.43 ms
Inference time: 17.77 ms
Total detect 1 objects
0: package 0.915 [603.0, 258.0, 722.0, 446.0]
```
Output image:
![](out.jpg)