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InsightFace Ready-to-deploy Model

List of Supported Models

Now FastDeploy supports the deployment of the following models

  • ArcFace
  • CosFace
  • PartialFC
  • VPL

Export ONNX Model

Taking ArcFace as an example: Visit ArcFace official github repository, follow the guidelines to download pt model files, and employ torch2onnx.py to get the file in onnx format.

  • Download ArcFace model files

    Link: https://pan.baidu.com/share/init?surl=CL-l4zWqsI1oDuEEYVhj-g code: e8pw  
  • Export files in onnx format

    PYTHONPATH=. python ./torch2onnx.py ms1mv3_arcface_r100_fp16/backbone.pth --output ms1mv3_arcface_r100.onnx --network r100 --simplify 1

Download Pre-trained ONNX Model

For developers' testing, models exported by InsightFace are provided below. Developers can download and use them directly. (The accuracy of the models in the table is sourced from the official library) The accuracy metric is sourced from the model description in InsightFace. Refer to the introduction in InsightFace for more details.

Model Size Accuracy (AgeDB_30)
CosFace-r18 92MB 97.7
CosFace-r34 131MB 98.3
CosFace-r50 167MB 98.3
CosFace-r100 249MB 98.4
ArcFace-r18 92MB 97.7
ArcFace-r34 131MB 98.1
ArcFace-r50 167MB -
ArcFace-r100 249MB 98.4
ArcFace-r100_lr0.1 249MB 98.4
PartialFC-r34 167MB -
PartialFC-r50 249MB -

Detailed Deployment Tutorials

Release Note