class_docstr: Randomly crop while centered on uncertain area by a certain probability.
  
  Args:
      crop_size (tuple|list): The size you want to crop from image.
      p (float): The probability centered on uncertain area.
class_docstr_tok: ["Randomly","crop","while","centered","on","uncertain","area","by","a","certain","probability",".","Args",":","crop_size","(","tuple|list",")",":","The","size","you","want","to","crop","from","image",".","p","(","float",")",":","The","probability","centered","on","uncertain","area","."]
code: def __init__(
      self, crop_size=((320, 320), (480, 480), (640, 640)), prob=0.5
  ):
      self.crop_size = crop_size
      self.prob = prob
  
imports: import os
  import random
  import string
  import cv2
  import numpy
  from paddleseg.transforms import functional
  from paddleseg.cvlibs import manager
  from paddleseg.utils import seg_env
  from PIL import Image
label_desc: Use image node_id 1 to create a new RandomCropByAlpha object  with example: obj = RandomCropByAlpha(crop_size, prob)