def _check_bbox_area(min_y, min_x, max_y, max_x, delta=0.05):
    'Adjusts bbox coordinates to make sure the area is > 0.\n\n  Args:\n    min_y: Normalized bbox coordinate of type float between 0 and 1.\n    min_x: Normalized bbox coordinate of type float between 0 and 1.\n    max_y: Normalized bbox coordinate of type float between 0 and 1.\n    max_x: Normalized bbox coordinate of type float between 0 and 1.\n    delta: Float, this is used to create a gap of size 2 * delta between\n      bbox min/max coordinates that are the same on the boundary.\n      This prevents the bbox from having an area of zero.\n\n  Returns:\n    Tuple of new bbox coordinates between 0 and 1 that will now have a\n    guaranteed area > 0.\n  '
    height = (max_y - min_y)
    width = (max_x - min_x)

    def _adjust_bbox_boundaries(min_coord, max_coord):
        max_coord = tf.maximum(max_coord, (0.0 + delta))
        min_coord = tf.minimum(min_coord, (1.0 - delta))
        return (min_coord, max_coord)
    (min_y, max_y) = tf.cond(tf.equal(height, 0.0), (lambda : _adjust_bbox_boundaries(min_y, max_y)), (lambda : (min_y, max_y)))
    (min_x, max_x) = tf.cond(tf.equal(width, 0.0), (lambda : _adjust_bbox_boundaries(min_x, max_x)), (lambda : (min_x, max_x)))
    return (min_y, min_x, max_y, max_x)
Adjusts bbox coordinates to make sure the area is > 0.

Args:
  min_y: Normalized bbox coordinate of type float between 0 and 1.
  min_x: Normalized bbox coordinate of type float between 0 and 1.
  max_y: Normalized bbox coordinate of type float between 0 and 1.
  max_x: Normalized bbox coordinate of type float between 0 and 1.
  delta: Float, this is used to create a gap of size 2 * delta between
    bbox min/max coordinates that are the same on the boundary.
    This prevents the bbox from having an area of zero.

Returns:
  Tuple of new bbox coordinates between 0 and 1 that will now have a
  guaranteed area > 0.
def _check_bbox_area(min_y, min_x, max_y, max_x, delta=0.05):
    'Adjusts bbox coordinates to make sure the area is > 0.\n\n  Args:\n    min_y: Normalized bbox coordinate of type float between 0 and 1.\n    min_x: Normalized bbox coordinate of type float between 0 and 1.\n    max_y: Normalized bbox coordinate of type float between 0 and 1.\n    max_x: Normalized bbox coordinate of type float between 0 and 1.\n    delta: Float, this is used to create a gap of size 2 * delta between\n      bbox min/max coordinates that are the same on the boundary.\n      This prevents the bbox from having an area of zero.\n\n  Returns:\n    Tuple of new bbox coordinates between 0 and 1 that will now have a\n    guaranteed area > 0.\n  '
    height = (max_y - min_y)
    width = (max_x - min_x)

    def _adjust_bbox_boundaries(min_coord, max_coord):
        max_coord = tf.maximum(max_coord, (0.0 + delta))
        min_coord = tf.minimum(min_coord, (1.0 - delta))
        return (min_coord, max_coord)
    (min_y, max_y) = tf.cond(tf.equal(height, 0.0), (lambda : _adjust_bbox_boundaries(min_y, max_y)), (lambda : (min_y, max_y)))
    (min_x, max_x) = tf.cond(tf.equal(width, 0.0), (lambda : _adjust_bbox_boundaries(min_x, max_x)), (lambda : (min_x, max_x)))
    return (min_y, min_x, max_y, max_x)