def get_small_model_with_other_model_as_layer():
inp_mask = Input(shape=(128, 128, 3))
pretrain_model_mask = MobileNet(input_shape=(128, 128, 3), include_top=False, weights='imagenet', pooling='avg')
try:
pretrain_model_mask.name = 'mobilenet'
except:
pretrain_model_mask._name = 'mobilenet'
x = pretrain_model_mask(inp_mask)
out = Dense(2, activation='sigmoid')(x)
model = Model(inputs=inp_mask, outputs=[out])
return model
def get_small_model_with_other_model_as_layer():
from keras.layers import Input, Dense
from keras.models import Model
from keras.applications.mobilenet import MobileNet
inp_mask = Input(shape=(128, 128, 3))
pretrain_model_mask = MobileNet(input_shape=(128, 128, 3),
include_top=False,
weights='imagenet',
pooling='avg')
pretrain_model_mask.name = 'mobilenet'
x = pretrain_model_mask(inp_mask)
out = Dense(2, activation='sigmoid')(x)
model = Model(inputs=inp_mask, outputs=[out])
return model