def __call__(self, image, label):
    'Call function of RandomMirrow_pair.\n\n        :param image: usually the feature image, for example, the LR image for super solution dataset,\n        the initial image for the segmentation dataset, and etc\n        :type image: PIL image\n        :param label: usually the label image, for example, the HR image for super solution dataset,\n        the mask image for the segmentation dataset, and etc\n        :type lebel: PIL image\n        :return: the image after transform\n        :rtype: list, erery item is a PIL image, the first one is feature image, the second is label image\n        '
    flip = ((np.random.choice(2) * 2) - 1)
    channels_image = image.shape[(- 1)]
    channels_label = label.shape[(- 1)]
    if (channels_image == 3):
        image = image[:, :, ::flip]
    else:
        image = image[:, ::flip]
    if (channels_label == 3):
        label = label[:, :, ::flip]
    else:
        label = label[:, ::flip]
    return (image, label)
Call function of RandomMirrow_pair.

:param image: usually the feature image, for example, the LR image for super solution dataset,
the initial image for the segmentation dataset, and etc
:type image: PIL image
:param label: usually the label image, for example, the HR image for super solution dataset,
the mask image for the segmentation dataset, and etc
:type lebel: PIL image
:return: the image after transform
:rtype: list, erery item is a PIL image, the first one is feature image, the second is label image
def __call__(self, image, label):
    'Call function of RandomMirrow_pair.\n\n        :param image: usually the feature image, for example, the LR image for super solution dataset,\n        the initial image for the segmentation dataset, and etc\n        :type image: PIL image\n        :param label: usually the label image, for example, the HR image for super solution dataset,\n        the mask image for the segmentation dataset, and etc\n        :type lebel: PIL image\n        :return: the image after transform\n        :rtype: list, erery item is a PIL image, the first one is feature image, the second is label image\n        '
    flip = ((np.random.choice(2) * 2) - 1)
    channels_image = image.shape[(- 1)]
    channels_label = label.shape[(- 1)]
    if (channels_image == 3):
        image = image[:, :, ::flip]
    else:
        image = image[:, ::flip]
    if (channels_label == 3):
        label = label[:, :, ::flip]
    else:
        label = label[:, ::flip]
    return (image, label)