FastDeploy/examples/vision/classification/paddleclas/README.md

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PaddleClas Model Deployment

Model Description

• PaddleClas Release/2.4

Now FastDeploy supports the deployment of the following models

• PP-LCNet Models
• PP-LCNetV2 Models
• EfficientNet Models
• GhostNet Models
• MobileNet Models(including v1,v2,v3)
• ShuffleNet Models
• SqueezeNet Models
• Inception Models
• PP-HGNet Models
• ResNet Models（including vd series）

Prepare PaddleClas Deployment Model

For PaddleClas model export, refer to Model Export

Attention：The model exported by PaddleClas contains two files, including inference.pdmodel and inference.pdiparams. However, it is necessary to prepare the generic inference_cls.yaml file provided by PaddleClas to meet the requirements of deployment. FastDeploy will obtain from the yaml file the preprocessing information required during inference. FastDeploy will get the preprocessing information needed by the model from the yaml file. Developers can directly download this file. But they need to modify the configuration parameters in the yaml file based on personalized needs. Refer to the configuration information in the infer section of the PaddleClas model training config.

Download Pre-trained Model

For developers' testing, some models exported by PaddleClas (including the inference_cls.yaml file) are provided below. Developers can download them directly.

Model	Parameter File Size	Input Shape	Top1	Top5
PPLCNet_x1_0	12MB	224x224	71.32%	90.03%
PPLCNetV2_base	26MB	224x224	77.04%	93.27%
EfficientNetB7	255MB	600x600	84.3%	96.9%
EfficientNetB0_small	18MB	224x224	75.8%	75.8%
GhostNet_x1_3_ssld	29MB	224x224	75.7%	92.5%
GhostNet_x0_5	10MB	224x224	66.8%	86.9%
MobileNetV1_x0_25	1.9MB	224x224	51.4%	75.5%
MobileNetV1_ssld	17MB	224x224	77.9%	93.9%
MobileNetV2_x0_25	5.9MB	224x224	53.2%	76.5%
MobileNetV2_ssld	14MB	224x224	76.74%	93.39%
MobileNetV3_small_x0_35_ssld	6.4MB	224x224	55.55%	77.71%
MobileNetV3_large_x1_0_ssld	22MB	224x224	78.96%	94.48%
ShuffleNetV2_x0_25	2.4MB	224x224	49.9%	73.79%
ShuffleNetV2_x2_0	29MB	224x224	73.15%	91.2%
SqueezeNet1_1	4.8MB	224x224	60.1%	81.9%
InceptionV3	92MB	299x299	79.14%	94.59%
PPHGNet_tiny_ssld	57MB	224x224	81.95%	96.12%
PPHGNet_base_ssld	274MB	224x224	85.0%	97.35%
ResNet50_vd	98MB	224x224	79.12%	94.44%

Detailed Deployment Documents

• Python Deployment
• C++ Deployment
• Serving Deployment