README.md

PaddleSeg Model Deployment

FastDeploy currently supports the deployment of the following models

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

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.

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%