| | ---
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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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| |
|
| | # 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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| |
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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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| |
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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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| |
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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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| | |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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| | ```
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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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| |
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| | Input image:
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| |
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| | 
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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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| |
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| | Output image:
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| |
|
| | 
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| | |
