def download_mobilenet_v2_model():
    IMG_SHAPE = (IMAGE_SIZE, IMAGE_SIZE, 3)
    base_model = tf.keras.applications.MobileNetV2(input_shape=IMG_SHAPE, include_top=False, weights='imagenet')
    model = tf.keras.Sequential([base_model, tf.keras.layers.Conv2D(32, 3, activation='relu'), tf.keras.layers.Dropout(0.2), tf.keras.layers.GlobalAveragePooling2D(), tf.keras.layers.Dense(5, activation='softmax')])
    print('Number of layers in the base model: ', len(base_model.layers))
    return (base_model, model)
def download_mobilenet_v2_model():
    IMG_SHAPE = (IMAGE_SIZE, IMAGE_SIZE, 3)
    base_model = tf.keras.applications.MobileNetV2(input_shape=IMG_SHAPE, include_top=False, weights='imagenet')
    model = tf.keras.Sequential([base_model, tf.keras.layers.Conv2D(32, 3, activation='relu'), tf.keras.layers.Dropout(0.2), tf.keras.layers.GlobalAveragePooling2D(), tf.keras.layers.Dense(5, activation='softmax')])
    print('Number of layers in the base model: ', len(base_model.layers))
    return (base_model, model)