nsorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Dropout
    
    # Build a convolutional neural network model
    model = Sequential([
        Conv2D(32, (3, 3), activation='relu', input_shape=(150, 150, 3)),
        MaxPooling2D(pool_size=(2, 2)),
        Conv2D(64, (3, 3), activation='relu'),
        MaxPooling2D(pool_size=(2, 2)),
        Conv2D(128, (3, 3), activation='relu'),
        MaxPooling2D(pool_size=(2, 2)),
        Flatten(),
        Dense(128, activation='relu'),
        Dro