class_docstr: Flip the images and gt boxes randomly.
  
  Args:
      thresh: Probability for random flip.
  
  Returns:
      img(np.ndarray): Distorted image.
      data(dict): Image info and label info.
class_docstr_tok: ["Flip","the","images","and","gt","boxes","randomly",".","Args",":","thresh",":","Probability","for","random","flip",".","Returns",":","img","(","np.ndarray",")",":","Distorted","image",".","data","(","dict",")",":","Image","info","and","label","info","."]
code: def __init__(self, thresh: float = 0.5):
      self.thresh = thresh
  
imports: import os
  import random
  from typing import Callable
  import cv2
  import PIL
  import numpy
  import paddlehub.vision.transforms.functional
  from paddlehub.vision.utils import box_crop, box_iou_xywh
label_desc: Use image node_id 1 to create a new RandomFlip object  with example: obj = RandomFlip(thresh)