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Facenet for face verification using pytorch

  • Pytorch implementation of the paper: "FaceNet: A Unified Embedding for Face Recognition and Clustering".
  • Training of network is done using triplet loss.
  • This work is modified in some functionality from the original work by Taebong Moon and then retrained for the purpose of completing my BS degree. The full report can be found at this folder: full-and-paper-report
  • To use the pretrained model please refer to this repo: https://github.com/khrlimam/res-facenet
  • If you wish to try the demo app please clone this repo and follow the installation instruction: https://github.com/khrlimam/demo-facenet

How to train/validate model

Results

  • Accuracy on VGGFace2 and LFW datasets

accuracy

  • Triplet loss on VGGFace2 and LFW datasets

loss

  • ROC curve on LFW datasets for validation

roc curve

  • True counts on each threshold

True counts on each threshold

  • Test the model on 30 pair of images with threshold 1.5 Test Result on 30 pair of images

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FaceNet for face recognition using pytorch

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