model.py 文件源码

def create_image_model_squeezenet(images_shape, repeat_count):
    print('Using SqueezeNet')
    inputs = Input(shape=images_shape)

    visual_model = get_squeezenet(1000, dim_ordering='tf', include_top=False)
    # visual_model.load_weights('squeezenet/model/squeezenet_weights_tf_dim_ordering_tf_kernels.h5')

    x = visual_model(inputs)
    x = GlobalMaxPooling2D()(x)
    x = RepeatVector(repeat_count)(x)

    return Model(inputs, x, 'image_model')