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new structure for vgg-face model

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Sefik Ilkin Serengil 2024-01-08 16:57:07 +00:00
parent d498d510bd
commit 19f057a712
1 changed files with 17 additions and 1 deletions
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18
deepface/basemodels/VGGFace.py
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@ -19,7 +19,9 @@ if tf_version == 1:
Flatten,
Dropout,
Activation,
Lambda,
)
from keras import backend as K
else:
from tensorflow.keras.models import Model, Sequential
from tensorflow.keras.layers import (
@ -29,7 +31,9 @@ else:
Flatten,
Dropout,
Activation,
Lambda,
)
from tensorflow.keras import backend as K
# ---------------------------------------
@ -98,6 +102,18 @@ def loadModel(
model.load_weights(output)
vgg_face_descriptor = Model(inputs=model.layers[0].input, outputs=model.layers[-2].output)
# 2622d dimensional model
# vgg_face_descriptor = Model(inputs=model.layers[0].input, outputs=model.layers[-2].output)
# 4096 dimensional model offers 6% to 14% increasement on accuracy!
# - softmax causes underfitting
# - added normalization layer to avoid underfitting with euclidean
# as described here: https://github.com/serengil/deepface/issues/944
base_model_output = Sequential()
base_model_output = Flatten()(model.layers[-5].output)
base_model_output = Lambda(lambda x: K.l2_normalize(x, axis=1), name="norm_layer")(
base_model_output
)
vgg_face_descriptor = Model(inputs=model.input, outputs=base_model_output)
return vgg_face_descriptor