/real-time-deep-face-recognition

using facenet algorithm

Primary LanguagePythonMIT LicenseMIT

real-time-deep-face-recogniton

Real-time face recognition program using Google's facenet.

Inspiration

Dependencies

Pre-trained models

Face alignment using MTCNN

How to use

  • First, we need align face data. So, if you run 'Make_aligndata.py' first, the face data that is aligned in the 'output_dir' folder will be saved.
  • Second, we need to create our own classifier with the face data we created.
    (In the case of me, I had a high recognition rate when I made 30 pictures for each person.)
    Your own classifier is a ~.pkl file that loads the previously mentioned pre-trained model ('20170511-185253.pb') and embeds the face for each person.
    All of these can be obtained by running 'Make_classifier.py'.
  • Finally, we load our own 'my_classifier.pkl' obtained above and then open the sensor and start recognition.
    (Note that, look carefully at the paths of files and folders in all .py)

Result