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PaddleSeg Python部署示例
在部署前，需确认以下步骤
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- 软硬件环境满足要求，参考FastDeploy环境要求
【注意】如你部署的为PP-Matting、PP-HumanMatting以及ModNet请参考Matting模型部署
本目录下提供infer.py快速完成PPHumanseg在RKNPU上部署的示例。执行如下脚本即可完成
# 下载部署示例代码
git clone https://github.com/PaddlePaddle/FastDeploy.git
cd FastDeploy/examples/vision/segmentation/paddleseg/python
# 下载图片
wget https://paddleseg.bj.bcebos.com/dygraph/pp_humanseg_v2/images.zip
unzip images.zip
# 推理
python3 infer.py --model_file ./Portrait_PP_HumanSegV2_Lite_256x144_infer/Portrait_PP_HumanSegV2_Lite_256x144_infer_rk3588.rknn \
--config_file ./Portrait_PP_HumanSegV2_Lite_256x144_infer/deploy.yaml \
--image images/portrait_heng.jpg
注意事项
RKNPU上对模型的输入要求是使用NHWC格式，且图片归一化操作会在转RKNN模型时，内嵌到模型中，因此我们在使用FastDeploy部署时，需要先调用DisableNormalizeAndPermute(C++)或`disable_normalize_and_permute(Python)，在预处理阶段禁用归一化以及数据格式的转换。