model.py 文件源码

def build(nc, w, h,
          loss='categorical_crossentropy',
          # optimizer='adadelta'):
          optimizer='adam',
          metrics=None,
          **kwargs):
    data_shape = w * h if None not in (w, h) else -1  # TODO: -1 or None?
    inp = Input(shape=(h, w, 3), name='image')
    enet = encoder.build(inp)
    enet = decoder.build(enet, nc=nc)
    name = 'enet_unpooling'

    # TODO: need to remove data_shape for multi-scale training
    enet = Reshape((data_shape, nc))(enet)

    enet = Activation('softmax', name='output')(enet)
    model = Model(inputs=inp, outputs=enet)

    if metrics is None:
        metrics = ['accuracy']
    model.compile(optimizer=optimizer, loss=loss, metrics=metrics)

    return model, name