_time_distributed_2d.py 文件源码

def TimeDistributedResNet50(inputs, blocks=None, include_top=True, classes=1000, *args, **kwargs):
    """
    Constructs a time distributed `keras.models.Model` according to the ResNet50 specifications.

    :param inputs: input tensor (e.g. an instance of `keras.layers.Input`)

    :param blocks: the network’s residual architecture

    :param include_top: if true, includes classification layers

    :param classes: number of classes to classify (include_top must be true)

    Usage:

        >>> import keras_resnet.models

        >>> shape, classes = (224, 224, 3), 1000

        >>> x = keras.layers.Input(shape)

        >>> y = keras_resnet.models.TimeDistributedResNet50(x)

        >>> y = keras.layers.TimeDistributed(keras.layers.Flatten())(y.output)

        >>> y = keras.layers.TimeDistributed(keras.layers.Dense(classes, activation="softmax"))(y)

        >>> model = keras.models.Model(x, y)

        >>> model.compile("adam", "categorical_crossentropy", ["accuracy"])
    """
    if blocks is None:
        blocks = [3, 4, 6, 3]

    return TimeDistributedResNet(inputs, blocks, block=keras_resnet.blocks.time_distributed_bottleneck_2d, include_top=include_top, classes=classes, *args, **kwargs)