train_segmenter.py 文件源码

def model(flags):

    inputs = Input(shape=(flags['image_size'] + (3,)))
    x = inputs

    x, sources = downsamples(x, [40, 40, 80, 100, 100, 100, 80, 80])
    x = mix(x, 100)
    x = Dropout(0.1)(x)
    x = upsamples(x, sources, [100] * 8)

    x = Conv2D(30, (1, 1), padding='valid', activation='relu')(x)
    x = Conv2D(30, (1, 1), padding='valid', activation='relu')(x)
    x = Conv2D(len(flags['example']['y']), (1, 1), padding='valid',
               activation='sigmoid')(x)

    mod = Model(inputs=inputs, outputs=x)

    return mod