run_me.py 文件源码

def get_model():
    input_shape = (image_size, image_size, 3)

    model = Sequential()

    model.add(Conv2D(32, kernel_size=(3, 3), padding='same',
                     input_shape=input_shape))
    model.add(Activation('relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))

    model.add(Conv2D(64, kernel_size=(3, 3), padding='same'))
    model.add(Activation('relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))

    model.add(Conv2D(128, kernel_size=(3, 3), padding='same'))
    model.add(Activation('relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))

    model.add(Conv2D(n_classes, kernel_size=(3, 3), padding='same'))
    model.add(Activation('relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))

    model.add(GlobalAveragePooling2D())

    print (model.summary())
    #sys.exit(0) #

    model.compile(loss=keras.losses.mean_squared_error,
            optimizer= keras.optimizers.Adadelta())

    return model