Adding_Flatten_Fully_Connected_Layer.py

# adding a flatten layer to CNN
cnn.add(tf.keras.layers.Flatten())

# adding fully connected layers
cnn.add(tf.keras.layers.Dense(128, activation='relu'))
cnn.add(tf.keras.layers.Dense(64, activation='relu'))

# output layer -> 6 Neurons for 6 different classes
# activation function used for multiclass classification is softmax, for binary use sigmoid as activation fxn
cnn.add(tf.keras.layers.Dense(6, activation='softmax'))