def mobilefacenet_train(resume=False):
x = inputs = tf.keras.layers.Input(shape=(112, 96, 3))
x = mobilefacenet(x)
if not resume:
x = tf.keras.layers.Dense(cls_num)(x)
outputs = tf.nn.softmax(x)
return tf.keras.models.Model(inputs, outputs)
else:
y = tf.keras.layers.Input(shape=(cls_num, ))
outputs = ArcFace_v2(n_classes=cls_num)((x, y))
return tf.keras.models.Model([inputs, y], outputs)
def mobilefacenet_train(softmax=False):
if RESUME:
model = keras.models.load_model(LOAD_MODEL_PATH)
inputs = model.input
x = model.output
else:
x = inputs = tf.keras.layers.Input(shape=(112, 96, 3))
x = mobilefacenet(x)
if softmax:
x = tf.keras.layers.Dense(cls_num)(x)
outputs = tf.keras.layers.Activation('softmax',
dtype='float32',
name='predictions')(x)
return tf.keras.models.Model(inputs, outputs)
else:
y = tf.keras.layers.Input(shape=(cls_num, ), name="target")
outputs = ArcFace_v2(n_classes=cls_num)((x, y))
return tf.keras.models.Model([inputs, y], outputs)