augmentation.py 文件源码

def flip_randomly_left_right_image_with_annotation(image_tensor, annotation_tensor):
    """Accepts image tensor and annotation tensor and returns randomly flipped tensors of both.
    The function performs random flip of image and annotation tensors with probability of 1/2
    The flip is performed or not performed for image and annotation consistently, so that
    annotation matches the image.

    Parameters
    ----------
    image_tensor : Tensor of size (width, height, 3)
        Tensor with image
    annotation_tensor : Tensor of size (width, height, 1)
        Tensor with annotation

    Returns
    -------
    randomly_flipped_img : Tensor of size (width, height, 3) of type tf.float.
        Randomly flipped image tensor
    randomly_flipped_annotation : Tensor of size (width, height, 1)
        Randomly flipped annotation tensor

    """

    # Random variable: two possible outcomes (0 or 1)
    # with a 1 in 2 chance
    random_var = tf.random_uniform(maxval=2, dtype=tf.int32, shape=[])


    randomly_flipped_img = control_flow_ops.cond(pred=tf.equal(random_var, 0),
                                                 fn1=lambda: tf.image.flip_left_right(image_tensor),
                                                 fn2=lambda: image_tensor)

    randomly_flipped_annotation = control_flow_ops.cond(pred=tf.equal(random_var, 0),
                                                        fn1=lambda: tf.image.flip_left_right(annotation_tensor),
                                                        fn2=lambda: annotation_tensor)

    return randomly_flipped_img, randomly_flipped_annotation