Real-time face recognition program using Google's facenet.
- I refer to the facenet repository of davidsandberg.
- also, shanren7 repository was a great help in implementing.
- Inception_ResNet_v1 CASIA-WebFace-> 20170511-185253
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)