Comments (3)
I have not used any classifier. There is this function in webcam script which uses model to generate encodings for webcam feed. Then these encodings are matched with the encodings of images present in our database.
Refer this notebook to understand it: https://github.com/gemaatienza/Deep-Learning-Coursera/blob/master/4.%20Convolutional%20Neural%20Networks/Face%20Recognition%20for%20the%20Happy%20House%20-%20v3.ipynb
Also watch this video: https://www.youtube.com/watch?v=0NSLgoEtdnw&list=PLkDaE6sCZn6Gl29AoE31iwdVwSG-KnDzF&index=36
from facenet-real-time-face-recognition.
okay now got it. Thank you for your explanation.
Can you please tell me that if I train my model on triplet loss and then i want to classify faces using softmax classifier is this possible?
if yes then can you please tell me how can I implement that?
from facenet-real-time-face-recognition.
You can try to add extra softmax layer as output layer and train it by freezing previous layers. But, to train softmax layer you must have a lot of image data for training.
from facenet-real-time-face-recognition.
Related Issues (16)
- Genral Question HOT 1
- Align and detection on new images do not work HOT 1
- Possible GPU issue HOT 1
- Not able to train the model. The below Error occurs during training.
- Not able to train the model, size mismatch
- Model labels ? HOT 1
- I cann't slove this issue while running train_triplet.py
- requirements.txt
- pretrain weight ? HOT 1
- AttributeError: 'NoneType' object has no attribute 'shape' HOT 4
- Repository not working with python2.7
- Training fail HOT 1
- Testing fail HOT 10
- Training fails with large epochs
- training fail HOT 2
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