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---
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license: bsd-3-clause
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language:
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- en
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base_model:
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- deeplabv3plus_mobilenet
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pipeline_tag: image-segmentation
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tags:
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- deeplabv3plus
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---
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# DeepLabv3Plus
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This version of deeplabv3plus_mobilenet has been converted to run on the Axera NPU using **w8a16** quantization.
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Compatible with Pulsar2 version: 5.0-patch1
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## Convert tools links:
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For those who are interested in model conversion, you can try to export axmodel through
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- [The repo of original](https://github.com/VainF/DeepLabV3Plus-Pytorch.git)
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- [Pulsar2 Link, How to Convert ONNX to axmodel](https://pulsar2-docs.readthedocs.io/en/latest/pulsar2/introduction.html)
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## Support Platform
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- AX650
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- [M4N-Dock(爱芯派Pro)](https://wiki.sipeed.com/hardware/zh/maixIV/m4ndock/m4ndock.html)
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- [M.2 Accelerator card](https://axcl-docs.readthedocs.io/zh-cn/latest/doc_guide_hardware.html)
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- AX637
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|Chips|Models |Time|
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|--|--|--|
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|AX650|deeplabv3plus_mobilenet_u16|13.4 ms |
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|AX637|deeplabv3plus_mobilenet_u16|39.4 ms |
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## How to use
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Download all files from this repository to the device
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### python env requirement
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#### pyaxengine
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https://github.com/AXERA-TECH/pyaxengine
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```
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wget https://github.com/AXERA-TECH/pyaxengine/releases/download/0.1.3.rc2/axengine-0.1.3-py3-none-any.whl
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pip install axengine-0.1.3-py3-none-any.whl
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```
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#### others
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Maybe None.
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#### Inference with AX650 Host, such as M4N-Dock(爱芯派Pro)
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Input image:
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run
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```
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python3 infer.py --img samples/1_image.png --model models-ax637/deeplabv3plus_mobilenet_u16.axmodel
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```
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Output image:
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