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Pipeline for training face recognition models (based on pytorch 1.1)

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Face Recognition Pipeline

  1. Download and extract dataset (MS1M refined by Insightface, more info here)

  2. Prepare dataset python tools/process_records.py --folder "path to extracted dataset"

  3. Update/create configuration file. Set up path to extracted dataset in configuration file (folder: "extracted dataset")

  4. Train model python train.py --config "configuration file"

  5. Test model python test.py --config "configuration file"

Results on trained models:

Models LFW CFP_FP AGEDB_30
MobileNet 0.9958 0.9573 0.9650
Resnet34 0.9975 0.9764 0.9760
SEResNeXt50 0.9975 0.9877 0.9792

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Pipeline for training face recognition models (based on pytorch 1.1)

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