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Face Recognition

This repository contains the code for face recognition used in CaterPillar. This can be tested on a local machine using a webcam. The directory structure is as follow:

  • dataset/ : Face dataset. Has a "unknown" folder that contains random faces. New folder is added to this directory whenever a new user is added.
  • face_detection_model/ : Contains a pre-trained Caffe deep learning model provided by OpenCV to detect faces. This model detects and localizes faces in an image.
  • output/ : contains output pickle files.
  • images/ : Test images will be uploaded here for recognition
  • extract_embeddings.py : Extract images into 128D vector
  • openface_nn4.small2.v1.t7: A Torch deep learning model which produces the 128-D facial embeddings
  • train_model.py : Takes 128D vectors as input to train a linear SVM model for recognition
  • recognize.py : Recognize images
  • recognize_video.py : Recognize video
  • collect_image.py : Starts the webcam and collect images of faces for training/recognition

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