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README.md
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README.md

English | 简体中文

PaddleSeg Model Deployment

Model Description

FastDeploy currently supports the deployment of the following models

【Attention】For PP-Matting、PP-HumanMatting and ModNet deployment, please refer to Matting Model Deployment

Prepare PaddleSeg Deployment Model

For the export of the PaddleSeg model, refer to Model Export for more information

Attention

  • The exported PaddleSeg model contains three files, including model.pdmodel、model.pdiparams and deploy.yaml. FastDeploy will get the pre-processing information for inference from yaml files.

Download Pre-trained Model

For developers' testing, part of the PaddleSeg exported models are provided below.

  • without-argmax export mode: Not specified--input_shape，specified--output_op none
  • with-argmax export mode：Not specified--input_shape，specified--output_op argmax

Developers can download directly.

Model Parameter Size Input Shape mIoU mIoU (flip) mIoU (ms+flip)
Unet-cityscapes-with-argmax | Unet-cityscapes-without-argmax 52MB 1024x512 65.00% 66.02% 66.89%
PP-LiteSeg-B(STDC2)-cityscapes-with-argmax | PP-LiteSeg-B(STDC2)-cityscapes-without-argmax 31MB 1024x512 79.04% 79.52% 79.85%
PP-HumanSegV1-Lite-with-argmax(General Portrait Segmentation Model) | PP-HumanSegV1-Lite-without-argmax(General Portrait Segmentation Model) 543KB 192x192 86.2% - -
PP-HumanSegV2-Lite-with-argmax(General Portrait Segmentation Model) | PP-HumanSegV2-Lite-without-argmax(General Portrait Segmentation Model) 12MB 192x192 92.52% - -
PP-HumanSegV2-Mobile-with-argmax(General Portrait Segmentation Model) | PP-HumanSegV2-Mobile-without-argmax(General Portrait Segmentation Model) 29MB 192x192 93.13% - -
PP-HumanSegV1-Server-with-argmax(General Portrait Segmentation Model) | PP-HumanSegV1-Server-without-argmax(General Portrait Segmentation Model) 103MB 512x512 96.47% - -
Portait-PP-HumanSegV2-Lite-with-argmax(Portrait Segmentation Model) | Portait-PP-HumanSegV2-Lite-without-argmax(Portrait Segmentation Model) 3.6M 256x144 96.63% - -
FCN-HRNet-W18-cityscapes-with-argmax | FCN-HRNet-W18-cityscapes-without-argmax(GPU inference for ONNXRuntime is not supported now) 37MB 1024x512 78.97% 79.49% 79.74%
Deeplabv3-ResNet101-OS8-cityscapes-with-argmax | Deeplabv3-ResNet101-OS8-cityscapes-without-argmax 150MB 1024x512 79.90% 80.22% 80.47%

Detailed Deployment Tutorials