vgg_preprocessing.py 文件源码

def _mean_image_subtraction(image, means):
    """Subtracts the given means from each image channel.

    For example:
        means = [123.68, 116.779, 103.939]
        image = _mean_image_subtraction(image, means)

    Note that the rank of `image` must be known.

    Args:
        image: a tensor of size [height, width, C].
        means: a C-vector of values to subtract from each channel.

    Returns:
        the centered image.

    Raises:
        ValueError: If the rank of `image` is unknown, if `image` has a rank other
            than three or if the number of channels in `image` doesn't match the
            number of values in `means`.
    """
    if image.get_shape().ndims != 3:
        raise ValueError('Input must be of size [height, width, C>0]')
    num_channels = image.get_shape().as_list()[-1]
    if len(means) != num_channels:
        raise ValueError('len(means) must match the number of channels')

    channels = tf.split(2, num_channels, image)
    for i in range(num_channels):
        channels[i] -= means[i]
    return tf.concat(channels, axis=2)