def distorted_bounding_box_crop(image, bbox, min_object_covered=0.1, aspect_ratio_range=(0.75, 1.33), area_range=(0.05, 1.0), max_attempts=100, scope=None):
 with tf.name_scope(scope, 'distorted_bounding_box_crop', [image, bbox]):
  sample_distorted_bounding_box = tf.image.sample_distorted_bounding_box(tf.shape(image), bounding_boxes=bbox, min_object_covered=min_object_covered, aspect_ratio_range=aspect_ratio_range, area_range=area_range, max_attempts=max_attempts, use_image_if_no_bounding_boxes=True)
  (bbox_begin, bbox_size, distort_bbox) = sample_distorted_bounding_box
  cropped_image = tf.slice(image, bbox_begin, bbox_size)
  return (cropped_image, distort_bbox)

def distorted_bounding_box_crop ( image , bbox , min_object_covered = 0.1 , aspect_ratio_range = ( 0.75 , 1.33 ) , area_range = ( 0.05 , 1.0 ) , max_attempts = 100 , scope = None ) : with tf . name_scope ( scope , 'distorted_bounding_box_crop' , [ image , bbox ] ) : sample_distorted_bounding_box = tf . image . sample_distorted_bounding_box ( tf . shape ( image ) , bounding_boxes = bbox , min_object_covered = min_object_covered , aspect_ratio_range = aspect_ratio_range , area_range = area_range , max_attempts = max_attempts , use_image_if_no_bounding_boxes = True ) ( bbox_begin , bbox_size , distort_bbox ) = sample_distorted_bounding_box cropped_image = tf . slice ( image , bbox_begin , bbox_size ) return ( cropped_image , distort_bbox )
generates cropped_image using a one of the bboxes randomly distorted .