image_output_1.png
from keras import Sequential

from keras.applications.vgg19 import VGG19

from keras.layers import Flatten, Dense

vgg19 = VGG19(weights='imagenet', include_top=False, input_shape=(128, 128, 3))
for layer in vgg19.layers:
    layer.trainable = False
model = Sequential()
model.add(vgg19)
model.add(Flatten())
model.add(Dense(2, activation='sigmoid'))
model.summary()