Skip to content

Instantly share code, notes, and snippets.

Embed
What would you like to do?
model = Sequential()
model.add(VGG16(weights="imagenet", include_top=False, input_shape=(HEIGHT, WIDTH, CHANNEL)))
model.add(Flatten())
model.add(Dense(128, activation="relu"))
model.add(Dense(64, activation="relu"))
model.add(Dense(64, activation="relu"))
model.add(Dense(4, activation="sigmoid"))
model.layers[-6].trainable = False
model.summary()
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment